diff --git a/_cite/.cache/cache.db b/_cite/.cache/cache.db
index 83e1a82b0..201e828ec 100644
Binary files a/_cite/.cache/cache.db and b/_cite/.cache/cache.db differ
diff --git a/_config.yaml b/_config.yaml
index f9ed785a6..9269f6e68 100644
--- a/_config.yaml
+++ b/_config.yaml
@@ -41,7 +41,7 @@ defaults:
values:
layout: post
- scope:
- type: "blog"
+ type: "opensource"
values:
layout: post
@@ -57,6 +57,8 @@ collections:
output: true
blog:
output: true
+ opensource:
+ output: true
# jekyll plugins
plugins:
diff --git a/_data/citations.yaml b/_data/citations.yaml
index 98c74d97d..df24bc4a9 100644
--- a/_data/citations.yaml
+++ b/_data/citations.yaml
@@ -1022,7 +1022,7 @@
plugin: sources.py
file: sources.yaml
- id: doi:10.1109/TIV.2024.3467115
- title: Safety-Quantifiable Planar-Feature-based LiDAR Localization with a Prior
+ title: Safety-Quantifiable Planar-Feature-Based LiDAR Localization With a Prior
Map for Intelligent Vehicles in Urban Scenarios
authors:
- Jiachen Zhang
@@ -1030,7 +1030,7 @@
- Weisong Wen
- Li-Ta Hsu
publisher: IEEE Transactions on Intelligent Vehicles
- date: '2024-01-01'
+ date: '2025-07-01'
link: https://doi.org/g8t5zc
type: paper
image: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/images/papers/2024/Zhang2024SafetyQuantifiable.png
@@ -2670,10 +2670,10 @@
title: Online Dynamic Model Calibration for Reliable Control of Quadrotor Based
on Factor Graph Optimization
authors:
- - PEIWEN YANG
- - WEISONG WEN
- - SHIYU BAI
- - JIAHAO HU
+ - Peiwen Yang
+ - Weisong Wen
+ - Shiyu Bai
+ - Jiahao Hu
publisher: IEEE Transactions on Aerospace and Electronic Systems
date: '2025-05-01'
link: https://doi.org/g9hrnt
@@ -2824,3 +2824,191 @@
- urban canyons
plugin: sources.py
file: sources.yaml
+- id: doi:10.1109/TAES.2025.3607718
+ title: Unified Sufficient Conditions for Exact Convex Relaxation of Nonconvex Optimal
+ Control Problems
+ authors:
+ - Runqiu Yang
+ - Weisong Wen
+ - Peiwen Yang
+ - Zichen Zhao
+ - Fengtianyi Huang
+ publisher: IEEE Transactions on Aerospace and Electronic Systems
+ date: '2025-09-09'
+ link: https://doi.org/g93v27
+ type: paper
+ tags:
+ - Optimal control
+ - Convex relaxation
+ - Trajectory planning
+ - Convex optimization
+ - Mars landing
+ plugin: sources.py
+ file: sources.yaml
+- id: arXiv:2509.17198
+ title: Certifiably Optimal Doppler Positioning using Opportunistic LEO Satellites
+ authors:
+ - Baoshan Song
+ - Weisong Wen
+ - Qi Zhang
+ - Bing Xu
+ - Li-Ta Hsu
+ publisher: arXiv
+ date: '2025-09-21'
+ link: https://arxiv.org/abs/2509.17198
+ type: paper
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2509.17198v1.pdf
+ tags:
+ - LEO satellite
+ - Doppler positioning
+ - signal of opportunity
+ - convex optimization
+ - semidefinite programming
+ plugin: sources.py
+ file: sources.yaml
+- id: arxiv:2509.21496
+ title: 'Wall Inspector: Quadrotor Control in Wall-proximity Through Model Compensation'
+ authors:
+ - Peiwen Yang
+ - Weisong Wen
+ - Runqiu Yang
+ - Yingming Chen
+ - Cheuk Chi Tsang
+ publisher: arXiv
+ date: '2025-09-25'
+ link: https://arxiv.org/abs/2509.21496
+ type: paper
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2509.21496v1.pdf
+ tags:
+ - null
+ plugin: sources.py
+ file: sources.yaml
+- id: arxiv:2510.00524
+ title: Two stage GNSS outlier detection for factor graph optimization based GNSS-RTK/INS/odometer
+ fusion
+ authors:
+ - Baoshan Song
+ - Penggao Yan
+ - Xiao Xia
+ - Yihan Zhong
+ - Weisong Wen
+ - Li-Ta Hsu
+ publisher: arXiv
+ date: '2025-10-01'
+ link: https://arxiv.org/abs/2510.00524
+ type: paper
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2510.00524v1.pdf
+ tags:
+ - null
+ plugin: sources.py
+ file: sources.yaml
+- id: arxiv:2510.04278
+ title: 'Integrated Planning and Control on Manifolds: Factor Graph Representation
+ and Toolkit'
+ authors:
+ - Peiwen Yang
+ - Weisong Wen
+ - Runqiu Yang
+ - Yuanyuan Zhang
+ - Jiahao Hu
+ - Yingming Chen
+ - Naigui Xiao
+ - Jiaqi Zhao
+ publisher: arXiv
+ date: '2025-10-05'
+ link: https://arxiv.org/abs/2510.04278
+ type: paper
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2510.04278v1.pdf
+ tags:
+ - null
+ plugin: sources.py
+ file: sources.yaml
+- id: doi:10.1109/TITS.2025.3616580
+ title: Learning Safe, Optimal, and Real-Time Flight Interaction With Deep Confidence-Enhanced
+ Reachability Guarantee
+ authors:
+ - Yuanyuan Zhang
+ - Yingying Wang
+ - Penggao Yan
+ - Weisong Wen
+ publisher: IEEE Transactions on Intelligent Transportation Systems
+ date: '2025-10-09'
+ link: https://doi.org/hbbrm6
+ type: paper
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/Learning_Safe_Optimal_and_Real-Time_Flight_Interaction_With_Deep_Confidence-Enhanced_Reachability_Guarantee.pdf
+ tags:
+ - Deep reinforcement learning
+ - deep confidenceenhanced reachability guarantees
+ - joint planning and control
+ - unmanned aerial vehicles
+ plugin: sources.py
+ file: sources.yaml
+- id: arxiv:2510.08880
+ title: Online IMU-odometer Calibration using GNSS Measurements for Autonomous Ground
+ Vehicle Localization
+ authors:
+ - Baoshan Song
+ - Xiao Xia
+ - Penggao Yan
+ - Yihan Zhong
+ - Weisong Wen
+ - Li-Ta Hsu
+ publisher: arXiv
+ date: '2025-10-10'
+ link: https://arxiv.org/abs/2510.08880
+ type: paper
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2510.08880v1.pdf
+ plugin: sources.py
+ file: sources.yaml
+- id: arXiv:2512.20224
+ title: 'UrbanV2X: A Multisensory Vehicle-Infrastructure Dataset for Cooperative
+ Navigation in Urban Areas'
+ authors:
+ - Qijun Qin
+ - Ziqi Zhang
+ - Yihan Zhong
+ - Feng Huang
+ - Xikun Liu
+ - Runzhi Hu
+ - Hang Chen
+ - Wei Hu
+ - Dongzhe Su
+ - Jun Zhang
+ - Hoi-Fung Ng
+ - Weisong Wen
+ publisher: arXiv
+ date: '2025-12-23'
+ link: https://arxiv.org/abs/2512.20224
+ type: paper
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2512.20224v1.pdf
+ - type: source
+ text: code
+ link: https://polyu-taslab.github.io/UrbanV2X/
+ tags:
+ - Multisensor Fusion
+ - Roadside Infrastructure
+ - SLAM
+ - Autonomous Driving
+ plugin: sources.py
+ file: sources.yaml
diff --git a/_data/sources.yaml b/_data/sources.yaml
index 83c1f39f4..a90c86e4c 100644
--- a/_data/sources.yaml
+++ b/_data/sources.yaml
@@ -2119,3 +2119,108 @@
- Doppler measurement model
- geometry distribution
- urban canyons
+
+- id: doi:10.1109/TAES.2025.3607718
+ type: paper
+ date: 2025-09-09
+ # image: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/images/papers/Snipaste_2025-09-07_15-21-25.png
+ # buttons:
+ # - type: manubot
+ # text: paper
+ # link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2404.14724v2.pdf
+ tags:
+ - Optimal control
+ - Convex relaxation
+ - Trajectory planning
+ - Convex optimization
+ - Mars landing
+
+- id: arXiv:2509.17198
+ type: paper
+ date: 2025-09-21
+ # image: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/images/papers/Snipaste_2025-09-07_15-21-25.png
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2509.17198v1.pdf
+ tags:
+ - LEO satellite
+ - Doppler positioning
+ - signal of opportunity
+ - convex optimization
+ - semidefinite programming
+
+- id: arxiv:2509.21496
+ type: paper
+ date: 2025-09-25
+ # image: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/images/papers/Snipaste_2025-09-07_15-21-25.png
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2509.21496v1.pdf
+ tags:
+ -
+
+- id: arxiv:2510.00524
+ type: paper
+ date: 2025-10-01
+ # image: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/images/papers/Snipaste_2025-09-07_15-21-25.png
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2510.00524v1.pdf
+ tags:
+ -
+
+
+- id: arxiv:2510.04278
+ type: paper
+ date: 2025-10-05
+ # image: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/images/papers/Snipaste_2025-09-07_15-21-25.png
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2510.04278v1.pdf
+ tags:
+ -
+
+- id: doi:10.1109/TITS.2025.3616580
+ type: paper
+ date: 2025-10-09
+ # image: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/images/papers/Snipaste_2025-09-07_15-21-25.png
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/Learning_Safe_Optimal_and_Real-Time_Flight_Interaction_With_Deep_Confidence-Enhanced_Reachability_Guarantee.pdf
+ tags:
+ - Deep reinforcement learning
+ - deep confidenceenhanced reachability guarantees
+ - joint planning and control
+ - unmanned aerial vehicles
+
+
+- id: arxiv:2510.08880
+ type: paper
+ date: 2025-10-10
+ # image: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/images/papers/Snipaste_2025-09-07_15-21-25.png
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2510.08880v1.pdf
+
+- id: arXiv:2512.20224
+ type: paper
+ date: 2025-12-23
+ # image: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/images/papers/Snipaste_2025-09-07_15-21-25.png
+ buttons:
+ - type: manubot
+ text: paper
+ link: https://github.com/PolyU-TASLAB/polyu-taslab.github.io/raw/main/research/papers/2512.20224v1.pdf
+ - type: source
+ text: code
+ link: https://polyu-taslab.github.io/UrbanV2X/
+ tags:
+ - Multisensor Fusion
+ - Roadside Infrastructure
+ - SLAM
+ - Autonomous Driving
\ No newline at end of file
diff --git a/_events/2025-07-05-IROS_Acceptance.md b/_events/2025-07-05-IROS_Acceptance.md
index 71d3a28e9..bfd0cfe21 100644
--- a/_events/2025-07-05-IROS_Acceptance.md
+++ b/_events/2025-07-05-IROS_Acceptance.md
@@ -1,5 +1,5 @@
---
-title: Our paper is accpeted by IEEE IROS 2025
+title: Our paper is accepted by IEEE IROS 2025
subtitle: Example news
# author: xxx
image: images/news/IROS2025_RSG_GLIO.png
diff --git a/_events/2025-09-14-Meituan_hosting_MarsTalk_at_PolyU.md b/_events/2025-09-14-Meituan_hosting_MarsTalk_at_PolyU.md
new file mode 100644
index 000000000..8c1b4c406
--- /dev/null
+++ b/_events/2025-09-14-Meituan_hosting_MarsTalk_at_PolyU.md
@@ -0,0 +1,64 @@
+---
+title: Meituan Marstalk Hosts at PolyU:Industry Leaders Discuss Future of Robotics and Intelligent Systems
+subtitle: news
+# author: Yingming Chen
+image: images/news/0914MarsTalk/marstalk.jpg
+tags: news
+order:
+---
+*Hong Kong, September 14th, 2025* – The Hong Kong Polytechnic University (PolyU) successfully hosted the Meituan Marstalk today, bringing together leading experts in robotics, automation, and artificial intelligence to explore technological breakthroughs in intelligent systems for dynamic environments.
+The ceremony featured a keynote address by representatives from HKISA, who emphasized the critical role of the new index in promoting trust and scalability in commercial and civic drone applications. The index will provide a measurable framework to evaluate drone performance, maintenance standards, and operational safety—key factors for integration into urban airspace.
+
+
+
+
+
+ HKISA presenting the DTORI indexes
+
+
+### Distinguished Speakers Share Insights on Cutting-Edge Technologies
+
+The event featured an impressive lineup of speakers from both academia and industry, highlighting the growing collaboration between universities and technology companies in advancing robotics research.
+
+Dr. Yinian Mao, Vice President of Meituan and Director of Meituan Academy of Robotics Shenzhen, delivered a keynote presentation on the company's latest innovations in autonomous systems. "The integration of robotics and AI in real-world applications is accelerating at an unprecedented pace, particularly in service delivery and urban logistics," Dr. Mao emphasized during his address.
+
+Prof. Ning Xi, Chair Professor of Robotics and Automation and Head of Department of Data and Systems Engineering at HKU, as well as Director of the Advanced Technologies Institute, provided insights into the academic research underpinning these technological advances. His presentation focused on the convergence of data science and robotic systems in creating more intelligent and adaptive machines.
+
+
+
+
+
+ Prof. Wen-Hua Chen presenting.
+
+
+### Focus on Low Altitude Economy and Drone Technology
+Prof. Wen-Hua Chen, Interim Head of Aerospace Engineering at PolyU, Chair Professor of Robotics and Autonomous Systems, and Director of the Research Centre for Low Altitude Economy, discussed the emerging opportunities in the low altitude economy sector. "Hong Kong and the Greater Bay Area are uniquely positioned to lead in the development of low altitude economy applications, from drone delivery to urban air mobility," Prof. Chen noted.
+
+Dr. Wu Haotian, Senior Director of Meituan and Head of Hardware Platform of Keeta Drone, presented practical applications of drone technology in Meituan's delivery ecosystem. The presentation showcased how autonomous drones are being deployed to navigate complex urban environments and deliver services more efficiently.
+
+Dr. Wenbo Ding, Associate Professor and Director of the Office of Research at Tsinghua SIGS, rounded out the speaker panel with insights on the research collaboration opportunities between institutions in the Greater Bay Area.
+
+### Bridging Academia and Industry Through Talent Development
+The event went beyond traditional academic presentations by incorporating practical career development opportunities for students and young professionals. Two special sessions were organized to connect talent with industry opportunities: including Express Resume Submission and Fast-track Interview Pass.
+
+
+
+
+ Conversation among leading industry participants and academic innovators.
+
+
+### TASLAB participating MarsTalk
+TASLAB members also helped hosting this event.
+
+
+
+
+
+ TASLAB group photo.
+
+
+
diff --git a/_events/2025-09-16-OHKF_RELEASES_TALKING FLIGHT.md b/_events/2025-09-16-OHKF_RELEASES_TALKING FLIGHT.md
new file mode 100644
index 000000000..542f09bc0
--- /dev/null
+++ b/_events/2025-09-16-OHKF_RELEASES_TALKING FLIGHT.md
@@ -0,0 +1,43 @@
+---
+title: OHKF Releases "Taking Flight — Forging a Future for Hong Kong’s Low-Altitude Economy" Report
+subtitle: news
+# author: Li Heng
+image: images/news/0916TALK/image1.png
+tags: news
+order:
+---
+
+## OHKF Releases "Taking Flight — Forging a Future for Hong Kong’s Low-Altitude Economy" Report
+
+### In-depth Discussion on the Future Development of Hong Kong's Low-Altitude Economy
+
+This month, Our Hong Kong Foundation (OHKF) released its latest research report entitled "Taking Flight — Forging a Future for Hong Kong’s Low-Altitude Economy."
+image1
+
+### Team Support and Key Discussion Points
+
+As a supporting team for this report, we conducted in-depth discussions focusing on the following key issues:
+
+1. The government support needed by university research teams, such as the Civil Aviation Department's review and support for research drone test flights;
+2. The critical breakthroughs required for transforming low-altitude technology research achievements into industrial applications in Hong Kong;
+3. How to strengthen collaboration between academia and industry to bring economic benefits to Hong Kong;
+4. How Hong Kong can synergize with Mainland China's low-altitude economy industry during the development process.
+
+### Academic and Industry Exchange
+
+At the same time, we invited researchers from Our Hong Kong Foundation (OHKF) to visit The Hong Kong Polytechnic University and participate in several academic and industry sharing and discussion sessions.
+
+
+
+
+
+
+---
+
+### Full Report
+
+For the full report, please visit: [https://www.ourhkfoundation.org.hk/en/media/reports/taking-flight-forging-a-future-for-hong-kongs-low-altitude-economy](https://www.ourhkfoundation.org.hk/en/media/reports/taking-flight-forging-a-future-for-hong-kongs-low-altitude-economy)
+
+We look forward to contributing further to the development of the low-altitude economy industry.
diff --git a/_events/2025-09-29-PolyU_AAE_Conducts_Drone_Test_Flight_in_Sandbox_Regulatory_Project.md b/_events/2025-09-29-PolyU_AAE_Conducts_Drone_Test_Flight_in_Sandbox_Regulatory_Project.md
new file mode 100644
index 000000000..cc6c49f25
--- /dev/null
+++ b/_events/2025-09-29-PolyU_AAE_Conducts_Drone_Test_Flight_in_Sandbox_Regulatory_Project.md
@@ -0,0 +1,53 @@
+---
+title: "PolyU AAE Conducts Drone Test Flight in Sandbox Regulatory Project"
+subtitle: "news"
+image: images/news/0929CampusFlight/Drone_Flight_2.jpg
+tags: news
+order:
+---
+
+*Hong Kong, September 29th, 2025* – The Aeronautics and Aviation Engineering (AAE) department at The Hong Kong Polytechnic University (PolyU) today conducted a drone performance test flight at the Shaw Sports Complex on campus, as part of the sandbox regulatory project for the low altitude economy. This successful event marks a new phase in PolyU AAE's initiative to advance regulatory frameworks and operational standards for unmanned aerial vehicles (UAVs) in urban environments.
+
+The test flight, carried out in collaboration with the Civil Aviation Department (CAD), evaluated key performance metrics of drones under controlled conditions, focusing on safety, efficiency, and compliance with emerging low-altitude airspace regulations. The sandbox project aims to create a scalable model for integrating drone technology into Hong Kong's transportation and logistics ecosystems.
+
+
+
+
+
+ Drone performance evaluation at Shaw Sports Complex, PolyU.
+
+
+### Sandbox Project Advances Low Altitude Economy Framework
+
+The sandbox regulatory project, led by PolyU AAE, provides a controlled environment for testing and validating drone operations, contributing to the development of standardized safety protocols and performance benchmarks. Today's test flight demonstrated the practical application of these standards, assessing factors such as flight stability, navigation accuracy, and payload capacity.
+
+"Today's test flight is a critical step forward in our low altitude economy initiatives," said a representative from the AAE department. "By working closely with regulatory bodies like CAD, we are paving the way for scalable and safe drone integration in Hong Kong and the Greater Bay Area."
+
+
+
+
+
+ AAE and CAD teams during the sandbox regulatory assessment.
+
+
+### Collaborative Efforts for Future Urban Air Mobility
+
+The event highlighted the growing collaboration between academic institutions and government agencies in shaping the future of urban air mobility. The sandbox project not only focuses on technical performance but also addresses regulatory challenges, such as airspace management and public safety.
+
+"PolyU's sandbox project serves as a model for how academia and regulators can work together to foster innovation while ensuring safety and compliance," added a CAD official. "We are excited to see these efforts translate into real-world applications."
+
+### Next Steps for Low Altitude Economy Development
+
+With the successful completion of this test flight, PolyU AAE plans to expand the sandbox project to include more complex scenarios, such as multi-drone operations and extended-visual-line-of-sight (EVLOS) flights. The department will also continue to engage industry partners and policymakers to drive the adoption of low-altitude economy solutions across the region.
+
+
+
+
+
+ Discussing future phases of the sandbox regulatory project.
+
+
+The sandbox regulatory project aligns with Hong Kong's broader goals to become a hub for technological innovation, particularly in areas such as smart city development and sustainable transportation. PolyU AAE remains at the forefront of these efforts, leveraging its expertise in aeronautics and aviation engineering to contribute to the region's economic and technological advancement.
\ No newline at end of file
diff --git a/_events/2025-09-30-SourthernPower.md b/_events/2025-09-30-SourthernPower.md
new file mode 100644
index 000000000..0348ef35f
--- /dev/null
+++ b/_events/2025-09-30-SourthernPower.md
@@ -0,0 +1,22 @@
+---
+title: TAS LAB Advances Collaboration on Offshore Wind Turbine Inspection with China Southern Power Grid
+subtitle: news
+# author: XIAO Naigui
+image: images/news/0930SouthernPower/image.png
+tags: news
+order:
+---
+
+## TAS LAB Advances Collaboration on Offshore Wind Turbine Inspection with China Southern Power Grid
+
+**Zhuhai, September 30, 2025** – A team led by Dr. Wen Weisong of the Department of Aeronautics and Civil Aviation at The Hong Kong Polytechnic University held a highly successful meeting today with the China Southern Power Grid Southern Offshore Wind Power Joint Development Co., Ltd. The meeting in Zhuhai marked a significant step forward in discussions for a joint laboratory research project.
+
+
+
+
+
+The collaboration is centered on the "UAV-based Blade and Tower Inspection" project, operating under the Guangdong-Hong Kong Joint Laboratory for Marine Infrastructure. The project aims to develop efficient, drone-based technologies for inspecting offshore wind turbines. The Hong Kong research efforts are led by Principal Investigator Dr. Wen Weisong, in partnership with his Guangdong counterpart, Lin Jinghua of the China Energy Engineering Group Guangdong Electric Power Design Institute Co., Ltd.. This collaboration also aims to jointly publish at least two academic papers, apply for one or more invention patents, and cultivate postgraduate talent.
+
+
+
diff --git a/_events/2025-10-10-ZhangyuanyuanTITS.md b/_events/2025-10-10-ZhangyuanyuanTITS.md
new file mode 100644
index 000000000..6f409e546
--- /dev/null
+++ b/_events/2025-10-10-ZhangyuanyuanTITS.md
@@ -0,0 +1,35 @@
+---
+title: Our paper is accepted by IEEE Transactions on Intelligent Transportation Systems
+subtitle: news
+# author: XIAO Naigui
+image: images/news/1010ZYYTITIS/1.png
+tags: news
+order:
+---
+
+It is great to share that our paper (“Learning Safe, Optimal, and Real-Time Flight Interaction With Deep Confidence-Enhanced Reachability Guarantee”, by Yuanyuan Zhang, Yingying Wang, Penggao Yan, and Weisong Wen) is accepted by the IEEE Transactions on Intelligent Transportation Systems. Congratulations to Yuanyuan and our collegues.
+
+
+
+
+
+**Abstract**
+
+In the low-altitude economy, ensuring the safe and agile flight of unmanned aerial vehicles (UAVs) in dynamic obstacle environments is essential for expanding interactive applications like parcel delivery. While deep reinforcement learning (DRL) shows promise for UAV motion planning and control, its trial-and-error exploration often struggles to ensure both agility and safety, especially under uncertain observational noise. Therefore, this paper proposes a deep confidence-enhanced reachability policy optimization (DCRPO) framework. By integrating safe DRL with nonlinear model predictive control (NMPC), DCRPO achieves high-level safety decisions, complex real-time joint planning and control for UAVs. Furthermore, we develop a deep confidence-enhanced reachability guarantee that constructs a set of stochastically forward-reachable planned trajectories under uncertainty, enabling robust safety collision probability certifications. This safe reachability mechanism adaptively selects belief space actions from planned actions to interact with the environment, further enhancing safety and reducing training time. In extensive experiments of UAVs traversing a fast-moving rectangular gate, the proposed method outperforms other state-of-the-art baseline methods under varying environments in terms of operational robustness. Furthermore, the proposed method significantly reduces overall collision violations and training time, greatly improving both training safety and efficiency. The demonstration video (https://youtu.be/7xkp9U7FSJg) and the source code (https://github.com/ZyyFLY/DCRPO) are also provided.
+
+
+
+
+
+ System Framework
+
+
+
+
+
+
+ Test Evaluation
+
\ No newline at end of file
diff --git a/_events/2025-10-17-Inner_Mongolia_Research_and_Industry_Exchange_Unmanned_Systems_and_Photovoltaic_Fieldwork.md b/_events/2025-10-17-Inner_Mongolia_Research_and_Industry_Exchange_Unmanned_Systems_and_Photovoltaic_Fieldwork.md
new file mode 100644
index 000000000..602ef6729
--- /dev/null
+++ b/_events/2025-10-17-Inner_Mongolia_Research_and_Industry_Exchange_Unmanned_Systems_and_Photovoltaic_Fieldwork.md
@@ -0,0 +1,49 @@
+---
+title: Inner Mongolia Research and Industry Exchange — Unmanned Systems and Photovoltaic Fieldwork
+subtitle: news
+image: images/news/1017NeiMengGuVisit/image6.jpg
+tags: news
+order:
+---
+
+## Inner Mongolia Research and Industry Exchange — Unmanned Systems and Photovoltaic Fieldwork
+
+### Team Visit to Key Institutions and Enterprises
+
+In late October, our team members visited several key organizations in Inner Mongolia, including:
+
+- Ordos Institute of Applied Technology
+- Ordos Modern Industry Institute
+- Inner Mongolia Huiju High-Tech Co., Ltd.
+- Inner Mongolia Kubuqi Desert Photovoltaic Energy Co., Ltd.
+
+
+
+
+
+
+
+
+
+
+### Academic and Industry Collaboration
+
+During these visits, we held in-depth discussions with university and enterprise partners focusing on the application of unmanned systems in academic research and local industries.
+
+### On-site Photovoltaic Cleaning and Data Collection
+
+Additionally, at one of the power stations of Inner Mongolia Kubuqi Desert Photovoltaic Energy Co., Ltd., we conducted practical drone-based photovoltaic cleaning and data collection work. This effort lays a solid foundation for future research on unmanned systems.
+
+
+
+
+
+
+---
+
+We look forward to further advancing unmanned system technologies and strengthening cooperation between academia and industry in Inner Mongolia
diff --git a/_events/2025-10-21-Attend_IROS.md b/_events/2025-10-21-Attend_IROS.md
new file mode 100644
index 000000000..15717ae3e
--- /dev/null
+++ b/_events/2025-10-21-Attend_IROS.md
@@ -0,0 +1,35 @@
+---
+title: Dr. HUANG Feng and PhD student ZHONG Yihan present their work at IEEE IROS 2025.
+subtitle: Example news
+# author: xxx
+image: images/news/IROS2025/poster_present.jpg
+tags: news
+order:
+---
+
+Our lab member Dr. HUANG Feng and PhD student ZHONG Yihan are presenting their work at IEEE IROS 2025. After 19 years, IROS returns to China, coinciding with a pivotal moment in the rapid advancement of AI and robotics—making IROS 2025 an outstanding venue for discussion and networking.. The data of our work is available at [Github](https://github.com/DarrenWong/RSG-GLIO).
+
+
+### Photos
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/_events/2025-10-30-shougang.md b/_events/2025-10-30-shougang.md
new file mode 100644
index 000000000..33e2a7fe0
--- /dev/null
+++ b/_events/2025-10-30-shougang.md
@@ -0,0 +1,34 @@
+---
+title: Shougang Jinggang Innovation Center Officials Visit Trustworthy AI and Autonomous Systems Lab at Hong Kong Polytechnic University.
+subtitle: Example news
+# author: xxx
+image: images/news/Shougang/shougang1.png
+tags: news
+order:
+---
+
+Representatives from the Shougang Jinggang Innovation Center visited The Hong Kong Polytechnic University (PolyU), where they were introduced to the research activities of the Trustworthy AI and Autonomous Systems Laboratory (TAS Lab).
+
+The delegation from the Shougang Jinggang Innovation Center expressed profound admiration for the pioneering work and cutting-edge innovations underway at the Trustworthy AI and Autonomous Systems Laboratory. They highly commended our dedication to developing safe, reliable, and ethically sound autonomous systems, noting that this mission perfectly aligns with the future direction of technology development.
+
+The Center's representatives were particularly impressed by the exhibited robots—specifically the humanoid robot, the cleaning drone, and the sophisticated V2X cooperative autonomous driving platform—which they cited as exceptional demonstrations of our team's technical excellence. To further inspire innovation and foster collaboration, the Center has extended a valued invitation for the TAS Lab to display these groundbreaking robotic systems at a dedicated exhibition space within the Shougang Jinggang Innovation Center, anticipating this partnership will be a tremendous opportunity to highlight our research achievements to a broader audience of industry leaders and potential investors.
+
+### Photos
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/_events/2025-10-31-nanjing_jiangning.md b/_events/2025-10-31-nanjing_jiangning.md
new file mode 100644
index 000000000..7ae3d9af2
--- /dev/null
+++ b/_events/2025-10-31-nanjing_jiangning.md
@@ -0,0 +1,27 @@
+---
+title: Nanjing Jiangning Economic Development Zone Officials Visit Trustworthy AI and Autonomous Systems Lab at Hong Kong Polytechnic University.
+subtitle: Example news
+# author: xxx
+image: images/news/nanjingjiangning/2.jpg
+tags: news
+order:
+---
+
+Officials from the Nanjing Jiangning Economic Development Zone visited The Hong Kong Polytechnic University, where they were introduced to the research activities of the Trustworthy AI and Autonomous Systems Laboratory. The delegation was given an overview of several innovative projects, including cleaning drones, tunnel inspection drones, humanoid robots, and end-to-end autonomous driving systems.
+
+During the visit, the officials expressed strong appreciation for the laboratory’s work, highlighting the potential applications and technological advancements demonstrated by the projects. The exchange underscored the importance of collaboration in cutting-edge research and its role in driving industrial and technological development.
+
+
+### Photos
+
+
+
+
+
+
+
+
+
+
diff --git a/_events/2025-11-03-ZhengXi_Phd_defense.md b/_events/2025-11-03-ZhengXi_Phd_defense.md
new file mode 100644
index 000000000..ba2789285
--- /dev/null
+++ b/_events/2025-11-03-ZhengXi_Phd_defense.md
@@ -0,0 +1,18 @@
+---
+title: Congratulations to the successfully PhD oral defense of Dr. ZHENG Xi!
+# author: Yixin Gao
+image: images/news/20251103_Zhengxi/zhengxi_oral_defense.jpg
+tags: news
+order:
+---
+
+Congratulations to the successfully PhD oral defense of Dr. ZHENG Xi!
+
+
+
+
+
+
+
+
diff --git a/_events/2025-11-03-hk_fangwuzhanlan.md b/_events/2025-11-03-hk_fangwuzhanlan.md
new file mode 100644
index 000000000..5247f5a5e
--- /dev/null
+++ b/_events/2025-11-03-hk_fangwuzhanlan.md
@@ -0,0 +1,30 @@
+---
+title: PolyU's TAS Lab Showcases Advanced Drone Technology at Chartered Institute of Housing Asian Pacific Branch Dinner
+subtitle:
+# author: xxx
+image: images/news/1103fangwu/fangwu1.jpg
+tags: news
+order:
+---
+
+HONG KONG – November 3, 2025 – The TAS Lab from The Hong Kong Polytechnic University (PolyU) presented its cutting-edge unmanned aerial vehicle (UAV) technology at a special exhibition during the annual dinner of The Chartered Institute of Housing (CIH) Asian Pacific Branch.
+
+The event, attended by key figures and professionals from the housing and property management industry, provided a prime opportunity for the PolyU research team to demonstrate the practical applications of their advanced drone systems.
+
+The TAS Lab's exhibition featured video presentations and our drone models WALL-E, highlighting capabilities specifically relevant to the housing sector. These included high-precision autonomous navigation for façade cleaning, AI-powered defect detection, and 3D mapping for building maintenance.
+
+The demonstration sparked significant interest among the attendees, fostering discussions on how this technology could be integrated into existing workflows for building surveys, maintenance planning, and safety compliance.
+
+### Photos
+
+
+
+
+
+
+
+
+
+
diff --git a/_events/2025-11-06-sz_chuanghuan.md b/_events/2025-11-06-sz_chuanghuan.md
new file mode 100644
index 000000000..607ed5ccf
--- /dev/null
+++ b/_events/2025-11-06-sz_chuanghuan.md
@@ -0,0 +1,20 @@
+---
+title: Professor Wen Weisong of PolyU Leads Delegation to Shenzhen Chuanghuan to Discuss Drone Pipeline Inspection Technology
+subtitle:
+# author: xxx
+# image: images/news/1103fangwu/fangwu1.jpg
+tags: news
+order:
+---
+
+SHENZHEN, China – November 6, 2025 – A research delegation from The Hong Kong Polytechnic University (PolyU), led by Professor Wen Weisong, visited the offices of [Shenzhen Chuanghuan] today to engage in high-level technical discussions and explore future collaboration.
+
+The primary focus of the meeting was the application of advanced unmanned aerial vehicle (UAV) technology for internal pipeline exploration and inspection.
+
+The PolyU team presented its latest research findings and technological breakthroughs in autonomous systems. Key discussion points included navigating drones in GPS-denied, confined spaces, 3D mapping of internal structures, and AI-powered defect detection for pipe maintenance.
+
+Representatives from Shenzhen Chuanghuan shared their industry expertise and the significant market demand for safer, more efficient inspection solutions for complex urban and industrial pipe networks.
+
+The two parties held a productive dialogue on bridging the gap between cutting-edge academic research and real-world industrial applications. Both sides identified significant synergies and expressed a strong mutual interest in a future partnership.
+
+The visit concluded with an agreement to draft a formal plan for future cooperation, potentially including joint research projects, technology trials, and the development of specialized drone platforms tailored for pipeline environments.
diff --git a/_events/2025-11-10-hk_heu_visit.md b/_events/2025-11-10-hk_heu_visit.md
new file mode 100644
index 000000000..5ca7d88c2
--- /dev/null
+++ b/_events/2025-11-10-hk_heu_visit.md
@@ -0,0 +1,55 @@
+---
+title: Harbin Engineering University Vice President YU Zhiwen Visits PolyU’s TAS Lab to Strengthen Research Ties
+subtitle:
+# author: xxx
+image: images/news/1110_heu/heu4.jpg
+tags: news
+order:
+---
+
+HONG KONG – November 10, 2025 – The TAS Lab at The Hong Kong Polytechnic University (PolyU) today welcomed a distinguished delegation from Harbin Engineering University (HEU), led by Vice President YU Zhiwen. The visit was organized to demonstrate the lab's latest advancements in autonomous systems and to deepen the research partnership between the two institutions.
+
+The visit began with a guided tour of the [FJ005 Indoor Flight Arena], the lab's state-of-the-art research and testing facility.
+
+Following the tour, the HEU delegation received a comprehensive briefing on the lab's key projects, presented by the TAS Lab's core research team:
+
+Mr. ZHU Fengchi delivered a presentation on the achievements of the Joint Laboratory and the fruitful collaboration between PolyU and HEU.
+
+
+
+
+
+Mr. LIU Xikun introduced the T2 Drone Project, providing a detailed overview and demonstration of the UAV's advanced capabilities.
+
+
+
+
+
+Mr. XIAO Naigui and Mr. HU Jiahao presented the lab's autonomous cleaning drone and gave a technical demonstration of several other specialized UAV projects.
+
+
+
+
+
+Prof. JIANG Yiping and Prof. GAO Zhen showcased the capabilities of the indoor flight arena and presented the lab's wider research outcomes in autonomous navigation and control.
+
+
+
+
+
+The demonstrations also included an introduction to the lab's Unmanned Ground Vehicle (UGV) platforms, illustrating the breadth of the TAS Lab's expertise in autonomous robotics.
+
+The session fostered a productive and in-depth discussion, with Vice President Yu and the HEU delegation engaging with the researchers on the technical innovations presented. The visit marks another significant step in the ongoing collaboration between the two universities, paving the way for continued innovation in autonomous systems.
+
+
+
+
+
+
+
+
diff --git a/_events/2025-11-11-UBeat_interviewed_Prof_Wen_Weisong.md b/_events/2025-11-11-UBeat_interviewed_Prof_Wen_Weisong.md
new file mode 100644
index 000000000..08e4cc7ea
--- /dev/null
+++ b/_events/2025-11-11-UBeat_interviewed_Prof_Wen_Weisong.md
@@ -0,0 +1,41 @@
+---
+title: Prof. Weisong Wen Interviewed by UBeat on "Drone-Based Curtain Wall Cleaning" Technology and Prospects
+subtitle:
+# author: xxx
+image: images/news/Ubeat/image1.png
+tags: news
+order:
+---
+
+## Professor Weisong Wen interviewed by UBeat on "Drone-Based Curtain Wall Cleaning" technology and prospects
+
+### Drones for glass curtain wall cleaning: all parties gearing up.
+
+UBeat recently ran the feature "Drones for glass curtain wall cleaning: all parties gearing up." In the interview, TAS Lab lead and Assistant Professor Weisong Wen outlined the technology roadmap, regulatory compliance, and application outlook for drone-based curtain wall cleaning, showcasing the team’s progress in autonomous localization, control, and operational safety.
+
+
+
+
+
+ Prof.Wen receiving the interview.
+
+### Industry pain points and opportunities
+
+* Technical challenges: Perception and localization on highly reflective glass; disturbance-rejection control for close-proximity flight; compensation for water-jet reaction forces; enclosure waterproofing and payload reliability.
+* Safety and compliance: Advanced operations permissions, exclusion zones and contingency planning, geo-fencing and wind-field assessment—prioritizing “safety first, standards-led.”
+* Application value: Reduced high-altitude work risk, improved efficiency, and strong potential for energy savings and carbon reduction.
+* Progress and plans: A staged demonstration path—building mapping → localization and pathing → on-site cleaning—while co-developing standard procedures with property managers and regulators.
+
+
+
+
+
+ PolyU JCIT Tower.
+
+
+### Link
+
+UBeat feature: [https://ubeat.com.cuhk.edu.hk/180\_%E7%84%A1%E4%BA%BA%E6%A9%9F%E6%B4%97%E7%8E%BB%E7%92%83%E5%B9%95%E7%89%86-%E5%90%84%E6%96%B9%E8%93%84%E5%8B%A2%E5%BE%85%E7%99%BC/](https://ubeat.com.cuhk.edu.hk/180_%E7%84%A1%E4%BA%BA%E6%A9%9F%E6%B4%97%E7%8E%BB%E7%92%83%E5%B9%95%E7%89%86-%E5%90%84%E6%96%B9%E8%93%84%E5%8B%A2%E5%BE%85%E7%99%BC/)
+
diff --git a/_events/2025-11-12-hk_bj_symposium.md b/_events/2025-11-12-hk_bj_symposium.md
new file mode 100644
index 000000000..15d137dd4
--- /dev/null
+++ b/_events/2025-11-12-hk_bj_symposium.md
@@ -0,0 +1,29 @@
+---
+title: Quadruped Robot Steals Spotlight at 28th Beijing-Hong Kong Economic Cooperation Symposium
+subtitle:
+# author: xxx
+image: images/news/1112HK_BJ_sym/4.jpg
+tags: news
+order:
+---
+
+HONG KONG – November 12, 2025 – The 28th Beijing-Hong Kong Economic Cooperation Symposium witnessed a showcase of technological innovation as Dr. Runqiu Yang and Mr. Zhongqi Wang from our research laboratory presented our work on quadruped robot. The robot is designed for inspection, logistics, and search-and-rescue operations, capable of carrying heavy loads for extended periods. The demonstration attracted substantial attention from government officials, industry leaders, and academic professionals.
+
+The symposium, themed "Beijing-Hong Kong Joining Hands, Connecting the World," brought together over 800 participants from government agencies, international business associations, leading enterprises, and industrial professionals. The symposium's significance was underscored by the presence of key political leaders, with Hong Kong Special Administrative Region Chief Executive John Lee and Beijing Municipal Mayor Yin Yong both delivering addresses at the opening ceremony. The symposium served as a crucial bridge for strengthening ties between the two regions' technological ecosystems. As Hong Kong Special Administrative Region Chief Executive John Lee noted in his opening address, "Beijing possesses profound historical culture and strong technological innovation capabilities, while Hong Kong enjoys the advantages of connecting the mainland with the rest of the world under the 'one country, two systems' framework."
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/_events/2025-11-18-ITSC2025-IVmeetsurban.md b/_events/2025-11-18-ITSC2025-IVmeetsurban.md
new file mode 100644
index 000000000..3b0a7c8f8
--- /dev/null
+++ b/_events/2025-11-18-ITSC2025-IVmeetsurban.md
@@ -0,0 +1,66 @@
+---
+title: 4th IV Meets Urban Workshop a Success at ITSC 2025
+subtitle: Safe And Certifiable Navigation And Control for Intelligent Vehicles In Complex Urban Scenarios
+# author: Yixin Gao
+image: images/news/ITSC2025/group_photo.jpg
+tags: news
+order:
+---
+
+**GOLD COAST, AUSTRALIA – November 18, 2025 –** The **4th Workshop on Intelligent Vehicle Meets Urban: Safe And Certifiable Navigation And Control** was successfully held at the Star Grand, Broadbeach, Gold Coast, Australia, in conjunction with the ITSC 2025 conference. The event convened leading experts and researchers to address the critical challenges of ensuring **safe, robust, and certifiable autonomous navigation** in complex urban environments.
+
+
+
+
+
+The workshop featured a series of high-impact presentations by renowned experts, whose contributions steered discussions on cutting-edge solutions for urban autonomy:
+
+* **Prof. Li-Ta Hsu** (The Hong Kong Polytechnic University)
+* **Prof. Timothy D Barfoot** (University of Toronto)
+* **Prof. Fu Zhang** (The University of Hong Kong)
+* **Prof. Yi Zhou** (Hunan University, China)
+* **Dr. Mao Shan** (The University of Sydney)
+* **Prof. Shreyas Kousik** (Georgia Institute of Technology)
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+Their talks covered essential topics from high-precision multi-sensor fusion and radar-based navigation to formal safety methods and LiDAR-centric systems for drones.
+
+
+A key highlight of the event was the dynamic poster session. Colleagues from our research group and Zhenxing Ming from University of Sydneey presented their latest findings, contributing significantly to the dialogue on next-generation intelligent vehicles. Their exhibited works covered areas such as robust localization, V2X data fusion, and integrity monitoring for autonomous navigation.
+
+
+The 4th Workshop on Intelligent Vehicle Meets Urban was a resounding success, fostering collaboration and setting new directions for research in safe and certifiable autonomous systems. The organizing committee extends its sincere gratitude to all invited speakers, poster presenters, and attendees for their active participation.
+
+
+For the detailed schedule, invited speaker abstracts, and information on accepted posters and videos, please visit the official workshop page: **[4th Workshop on IV meets Urban](https://sites.google.com/view/ivurban2025itsc)**
+
+
+
+
diff --git a/_events/2025-12-13-jj.md b/_events/2025-12-13-jj.md
new file mode 100644
index 000000000..4dffe8daf
--- /dev/null
+++ b/_events/2025-12-13-jj.md
@@ -0,0 +1,39 @@
+---
+title: TAS Team Showcases Innovative Robotics at PolyU Technology Transfer Conference
+subtitle:
+# author: xxx
+image: images/news/1213Jinjiang/1.jpg
+tags: news
+order:
+---
+
+**JINJIANG, China** – December 14, 2025 – The TAS Research Team from The Hong Kong Polytechnic University (PolyU) made a strong impression at the inaugural **"Hong Kong Polytechnic University Technology Transfer Conference & Inaugural Annual Exchange Meeting of the Institute for Technological Innovation (2025)."** Held in Jinjiang City, Fujian Province, the event drew over 3,500 participants from government, academia, and industry, focusing on advancing industry-academia-research integration and fostering an innovation ecosystem.
+
+
+
+
+
+
+
+
+
+Led by PolyU's commitment to transforming research into real-world applications, the TAS team showcased cutting-edge outputs in robotics and sensing technologies. Highlights included unmanned aerial vehicles (UAVs) for building window cleaning, quadruped robots designed for inspection and logistics, ultra-wideband (UWB) modules for precise positioning, and LiDAR scanners enabling high-resolution 3D environmental modeling. These demonstrations attracted keen interest from investors and professionals, underscoring PolyU's role in driving national innovation strategies.
+
+
+
+
+
+
+
+
+
+As PolyU President Professor Teng Jinchao emphasized, the conference marks a milestone in converting laboratory breakthroughs into market-ready products, with TAS contributions exemplifying this vision.
+
+
+
+
diff --git a/_events/2025-12-17-Ruijie_IoTJ.md b/_events/2025-12-17-Ruijie_IoTJ.md
new file mode 100644
index 000000000..b809b2932
--- /dev/null
+++ b/_events/2025-12-17-Ruijie_IoTJ.md
@@ -0,0 +1,22 @@
+---
+title: Our paper is accepted by IEEE Internet of Things Journal
+subtitle: Example news
+# author: xxx
+image: images/news/ruijie_rttlio.png
+tags: news
+order:
+---
+
+It is great to share that our paper (“RTT-LIO: A Wi-Fi RTT-aided LiDAR-Inertial Odometry via Tightly-Coupled Factor Graph Optimization in Complex Scenes”, by Ruijie Xu, Xikun Liu, Xin Wang, Weisong Wen, and Yulong Huang) is accepted by the IEEE Internet of Things Journal. Congratulations to Ruijie and etc.!
+
+## Abstract
+
+The pursuit of reliable and high-precision indoor positioning has become increasingly critical with the widespread deployment of Unmanned Autonomous Systems (UAS) across smart cities. While Wi-Fi Round-Trip-Time (RTT) technology offers promising absolute positioning capabilities, it faces challenges from signal interference and processing delays. Similarly, LiDAR-inertial odometry (LIO) systems provide accurate relative positioning, but suffer from cumulative drift over time. Although existing methods have explored loosely coupled technologies, they process sensor data separately, failing to fully exploit the complementary strengths of different sensors. This research pioneered a tightly-coupled RTT/LIO framework, encompassing novel factor graph formulations that ensure consistency between RTT and LiDAR observations, alongside LiDAR-aided RTT outlier detection and exclusion. Furthermore, we developed an innovative approach to estimate the positions of unknown access points (AP) by using prior trajectory and RTT observations. AP position estimation is based on kernel density estimation (KDE) and geometric diversity constraints (GDC) with the help of an adaptive RANSAC-based fault detection algorithm. Compared to RTT-only implementations, state-of-the-art LIO systems, and conventional loosely coupled approaches, our method demonstrated error reductions of 20-80\% in extensive experiments. The [code, Wi-Fi RTT/LiDAR/IMU dataset](https://github.com/RuijieXu0408/RTT-LIO), and [demo video](https://www.bilibili.com/video/BV1Y94MzYE7F) of our proposed methodology has been made publicly available to display our research.
+
+
+## System Framework
+
+
+
+
diff --git a/_events/2025-12-18-AirBlower_UAV_Demo_at_PolyU.md b/_events/2025-12-18-AirBlower_UAV_Demo_at_PolyU.md
new file mode 100644
index 000000000..1e3987d9a
--- /dev/null
+++ b/_events/2025-12-18-AirBlower_UAV_Demo_at_PolyU.md
@@ -0,0 +1,39 @@
+---
+title: T2 Airport Airlower UAV Demonstration at PolyU
+subtitle: news
+image: images/news/1218/silent2.jpg
+tags: news
+---
+
+## Team Demonstrates Airblower UAV Technology with Civil Aviation Department at PolyU
+
+
+
+On December 18th, our team conducted a demonstration of airblower UAV technology in collaboration with the Civil Aviation Department at The Hong Kong Polytechnic University (PolyU).
+
+
+
+
+
+
+The demonstration showcased our airblower UAV system's capabilities to representatives from Hong Kong's Civil Aviation Department (CAD), highlighting the technology's potential applications in urban environments and its compliance with aviation safety standards in enclosed areas.
+
+
+
+
+
+
+### Advancing UAV Applications in Hong Kong
+
+The UAV is the product of this collaboration with the Gammon Construction Ltd., represents an important step in advancing the in field application of our airblower UAV system at the newly built T2 airport. The demonstration provided a practical example of how this technology can be used in real-world scenarios and helped to build regulatory understanding and acceptance of specialized UAV applications in Hong Kong. The demonstration provided valuable insights into the operational parameters and safety considerations of airblower UAV technology.
+
+Our team remains committed to working closely with aviation authorities to ensure that innovative UAV solutions can be safely integrated into Hong Kong's airspace, contributing to the development of the city's low-altitude economy.
+
+
+
+
+
+
diff --git a/_events/2025-12-19-cleaning_uav_sahnghai.md b/_events/2025-12-19-cleaning_uav_sahnghai.md
new file mode 100644
index 000000000..d769c767d
--- /dev/null
+++ b/_events/2025-12-19-cleaning_uav_sahnghai.md
@@ -0,0 +1,46 @@
+---
+title: Team Successfully Demonstrates Automated Drone Building Cleaning at Shanghai Pudong Software Park
+subtitle: news
+image: images/news/1219/image1.jpg
+tags: news
+---
+
+## Team Successfully Demonstrates Automated Drone Building Cleaning at Shanghai Pudong Software Park
+
+
+
+Today, our team conducted a field demonstration of automated drone building cleaning at the Shanghai Pudong Software Park in China.
+
+
+
+
+
+
+
+
+
+
+As a key part of the launch ceremony for the Shanghai Pudong Software Park Low-Altitude Economy Service Platform, our demonstration received significant attention and support from the Shanghai Government, the Pudong New Area Government, and the Aircraft Owners and Pilots Association of China (AOPA-China).
+
+
+
+
+
+
+### Industry Breakthrough and Market Potential
+
+Conducting a demonstration in a city like Shanghai—characterized by its dense skyline and immense demand for building cleaning services—marks a significant breakthrough for our team in the field of drone-based cleaning.
+
+This milestone not only validates the maturity of our technology but also demonstrates the solution's potential for application in the complex environments of mega-cities.
+
+---
+
+Reference Press Release: https://mp.weixin.qq.com/s/HvCxbZXmLE4ve5UVuRo08g
+
+
+
+
+
diff --git a/_events/2026-01-13-Rinoai_MoU.md b/_events/2026-01-13-Rinoai_MoU.md
new file mode 100644
index 000000000..691a412e4
--- /dev/null
+++ b/_events/2026-01-13-Rinoai_MoU.md
@@ -0,0 +1,26 @@
+---
+title: PolyU AAE and Rino.ai sign MOU to advance autonomous delivery vehicle applications
+
+subtitle: news
+image: images/news/20260113_RinoaiMoU/MoU.png
+tags: news
+---
+
+## PolyU AAE and Rino.ai sign MOU to advance autonomous delivery vehicle applications
+
+We have signed an MOU with Rino.ai, a leading L4 autonomous driving company, to co-develop and pilot autonomous vehicle applications on campus. Initial focus areas include last‑mile delivery and security patrols, with solutions tailored to dynamic pedestrian and traffic flows.
+
+Rino.ai has deployed 2,000+ vehicles in 170+ cities, leads the industry in new‑order volume, and has begun large‑scale deliveries of its Robovan autonomous logistics vehicle. PolyU AAE contributes internationally recognized expertise in multi‑sensor fusion, vehicle‑dynamics optimization, and intelligent transportation, supported by PolyU’s broader strengths in EVs and smart mobility.
+
+The partnership will enhance perception, decision‑making, and planning for dense campus environments and accelerate real‑world pilots at PolyU. More details can be found in this [website](https://www.rino.ai/news/rino-ai-and-the-hong-kong-polytechnic-university-sign-memorandum.html)
+
+
+
+
+
+
+
+
+
+
diff --git a/_events/2026-01-16-linxai.md b/_events/2026-01-16-linxai.md
new file mode 100644
index 000000000..d5385d0dc
--- /dev/null
+++ b/_events/2026-01-16-linxai.md
@@ -0,0 +1,27 @@
+---
+title: TAS Team Visits LINXAI Company to Discuss Quadruped Robot Collaboration Projects
+subtitle:
+# author: xxx
+image: images/news/0116_linxai/1.jpg
+tags: news
+order:
+---
+
+**SHENZHEN, China** – January 16, 2026 – The TAS Team embarked on a productive visit to LINXAI Company, a leading innovator in robotics technology. The purpose of the visit was to engage in detailed discussions on ongoing collaboration projects centered around the quadruped robot, while also touring the company's advanced laboratory facilities. This exchange highlights PolyU's dedication to fostering industry-academia partnerships and advancing practical applications in robotics.
+
+
+
+
+
+The visit brought together TAS team members with LINXAI's engineering experts. Discussions focused on four innovative projects aimed at enhancing the capabilities of the quadruped robot:
+1. Robot Dog Following: Utilizing Ultra-Wideband (UWB) technology for precise human-following, enabling applications in logistics, security, and personal assistance.
+2. Robot Dog Vision-Based Motion Control: Integrating LiDAR sensors and Deep Reinforcement Learning (DRL) to improve terrain adaptability and gait optimization on unstructured surfaces.
+3. Guide Dog Application: Developing an intelligent system for visually impaired users, combining localization, vision-language navigation, and locomotion modules for safe mobility assistance.
+4. UAV-Robot Dog Landing: Creating an air-ground collaborative logistics system for seamless package transfer between UAVs and the quadruped robot, addressing last-mile delivery challenges.
+These projects demonstrate the platform's potential in diverse fields, ranging from disaster response and industrial inspection to assistive technologies and smart logistics.
+
+
+
+
diff --git a/_events/2026-01-18-TasFusion.md b/_events/2026-01-18-TasFusion.md
new file mode 100644
index 000000000..a4b1a002c
--- /dev/null
+++ b/_events/2026-01-18-TasFusion.md
@@ -0,0 +1,47 @@
+---
+title: PolyU TAS LAB Releases TasFusion - A GNSS/IMU Sliding-Window Optimization Framework
+subtitle: news
+image: images/opensource/TasFusion/longdata.png
+tags: news
+---
+
+## PolyU TAS LAB Releases TasFusion: A GNSS/IMU Sliding-Window Optimization Framework
+
+The PolyU Trustworthy AI and Autonomous Systems Laboratory (TAS LAB) has officially released TasFusion, an open-source ROS1 framework for multi-sensor navigation and state estimation.
+
+TasFusion provides a Ceres-based GNSS/IMU loosely coupled sliding-window optimization framework, designed for research and experimental validation in outdoor navigation scenarios. The system supports IMU pre-integration, online bias estimation, marginalization to preserve historical information, and GNSS position and velocity constraints. All major functions are configurable through ROS launch parameters, enabling flexible deployment and ablation studies.
+
+The framework is accompanied by a complete toolchain, including GNSS message definitions, NLOS exclusion utilities, NovAtel receiver drivers, and NMEA parsing scripts. TasFusion has been validated on a GNSS-IMU-4G integrated navigation module (dual-IMU, u-blox F9P-04B, and 4G link), demonstrating reliable performance with high-frequency measurements and stable telemetry in real-world environments.
+
+TasFusion was developed in the context of the AAE4203 course at The Hong Kong Polytechnic University and is further supported by the Research Center for Autonomous System in Smart Transportation, PolyU-Wuxi Technology and Innovation Research Institute, reflecting close integration between education, research, and applied engineering.
+
+The project is now publicly available on GitHub and is intended to support research in navigation, sensor fusion, autonomous systems, and intelligent transportation applications.
+
+🔗 GitHub Repository:
+https://github.com/PolyU-TASLAB/TasFusion
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+> Reference Hardware Platform ([Introduction Video](https://www.bilibili.com/video/BV1fiaqzNEEm)):
+>
+> TasFusion has been validated on GNSS-IMU-4G integrated navigation module (dual-IMU + u-blox F9P-04B + 4G uplink), providing high-frequency measurements and reliable telemetry for outdoor deployments.
+>
+> For inquiries regarding this hardware platform, please contact **hbwu@hkpolyu-wxresearch.cn**.
+
+
+
+
+
diff --git a/_events/2026-01-20-simpleai.md b/_events/2026-01-20-simpleai.md
new file mode 100644
index 000000000..679de051c
--- /dev/null
+++ b/_events/2026-01-20-simpleai.md
@@ -0,0 +1,36 @@
+---
+title: PolyU and Simple AI Launch Strategic Collaboration
+subtitle:
+# author: xxx
+image: images/news/0119_simpleai/1.png
+tags: news
+order:
+---
+
+**HONG KONG, China** – January 19, 2026 – The Hong Kong Polytechnic University and Beijing Simple AI Technology Co., Ltd. (Simple AI) officially launched their strategic partnership through a Memorandum of Understanding (MOU) signing ceremony. Held at PolyU's Chiang Chen Studio Theatre (AG204), the event brought together key representatives from both institutions to exchange the agreement and discuss future collaborations in embodied intelligent robotics. This partnership underscores PolyU's commitment to advancing industry-academia synergies and driving innovation in AI-driven technologies for real-world applications.
+
+
+
+
+
+The ceremony was hosted by Prof. Weisong WEN from TAS Lab. Attendees from PolyU included Ir Prof. H.C. Man, Dean of the Faculty of Engineering, Prof. Crystal Shi from the School of Hotel and Tourism Management, and Dr. Runqiu Yang from TAS Lab. Representing Simple AI were Founder and CEO Dr. Xiaofei Li, Vice President Yutang Tang, and Marketing Director Hui Wang.
+
+The MOU outlines a framework for joint efforts in several key areas of embodied intelligent robotics:
+
+1. **Joint Research and Development**: Focusing on the design and optimization of robot "brains" using AI-driven control systems, including End-to-End Learning, Vision-Language-Navigation (VLN), and Vision-Language-Action (VLA) models for robust perception, real-time reasoning, and precise execution in dynamic environments.
+2. **Closed-Loop Systems Development**: Building systems that integrate behavioral AI models with real-world data from simulated and actual scenarios, addressing challenges like data scarcity in unstructured settings such as hotels, nursing homes, and homes.
+3. **Integration of TAS Lab Expertise**： Leveraging PolyU's Trustworthy AI and Autonomous Systems Laboratory (TAS Lab) for high-precision positioning algorithms and multi-sensor fusion to ensure safety in autonomous operations, providing fail-safe checks against AI-driven perception in complex indoor environments.
+4. **Phased Proof-of-Concept Pilots and Industrialization**: Executing pilots in sectors like hotel services (utilizing Simple AI's partnerships with major hotel groups and PolyU's leadership in Hospitality & Tourism Management), elderly care, and family environments, enhancing robots' generalization, long-horizon task planning, emotional intelligence, adaptive learning, and self-evolutionary capabilities.
+
+These initiatives aim to propel advancements in assistive robotics, fostering solutions for societal needs in hospitality, elderly care, and beyond.
+
+
+
+
+
+
+
+
diff --git a/_events/2026-01-28-Rino-AI-SFExpress-Visit.md b/_events/2026-01-28-Rino-AI-SFExpress-Visit.md
new file mode 100644
index 000000000..52fbc2d17
--- /dev/null
+++ b/_events/2026-01-28-Rino-AI-SFExpress-Visit.md
@@ -0,0 +1,31 @@
+---
+title: TAS Team Meets with SF Express(Hong Kong) and Rino AI to Discuss Smart Logistics and Autonomous Campus Delivery Collaboration
+subtitle:
+# author: xxx
+image: images/news/260128/260128.jpeg
+tags: news
+order:
+---
+
+**HONG KONG, China** – January 29, 2026 – The Hong Kong Polytechnic University's Trustworthy AI and Autonomous Systems Laboratory (TAS LAB) held a strategic cooperation meeting with SF Express Hong Kong and Rino AI to explore collaborative opportunities in smart logistics and autonomous campus delivery vehicles . This meeting underscores PolyU's commitment to advancing industry-academia partnerships and developing practical solutions for next-generation logistics systems that address real-world challenges in urban delivery and campus mobility.
+
+
+
+
+
+The meeting brought together key representatives from TAS LAB, SF Express(Hong Kong), and Rino AI to discuss innovative approaches to intelligent logistics and autonomous delivery technologies. The discussions centered on leveraging cutting-edge AI, robotics, sensor fusion, and IoT solutions to address modern logistics challenges, particularly in campus and urban environments where safety, efficiency, and sustainability are paramount concerns.
+
+Attendees from PolyU included Prof. Weisong WEN from TAS Lab and research team members. Representing SF Express Hong Kong were senior executives from the logistics operations and technology innovation divisions, while Rino AI was represented by their leadership team specializing in artificial intelligence solutions and autonomous systems development.
+
+The three-party collaboration will focus on several key technological domains and application scenarios:
+
+1. **Smart Logistics Systems**: Developing comprehensive AI-powered solutions for intelligent logistics management, including dynamic route optimization algorithms, real-time package tracking systems, predictive demand forecasting, and intelligent warehouse management. The collaboration aims to integrate machine learning models with SF Express(Hong Kong)'s extensive operational data to create adaptive logistics systems that can respond to changing conditions in real-time. This includes developing advanced algorithms for fleet management, delivery scheduling optimization, and resource allocation that can significantly enhance operational efficiency while reducing energy consumption and environmental impact. The system will leverage big data analytics and cloud computing infrastructure to process vast amounts of logistics data, enabling predictive maintenance, demand forecasting, and intelligent decision-making across the entire supply chain.
+
+2. **Autonomous Campus Delivery Vehicles**: Designing and implementing intelligent unmanned delivery vehicles specifically tailored for university campus environments. The project will address unique challenges associated with campus delivery, including pedestrian detection and avoidance, navigation in mixed-use environments with students and faculty, compliance with campus safety regulations, and integration with existing campus infrastructure. The autonomous vehicles will leverage advanced perception systems, including LiDAR, cameras, and radar sensors, combined with sophisticated path planning algorithms to ensure safe and efficient delivery operations. Special attention will be given to human-robot interaction design to ensure the vehicles can operate seamlessly in crowded campus settings, with features such as audio-visual alerts, intuitive gesture recognition, and emergency stop mechanisms. The vehicles will be designed to handle various weather conditions, navigate complex terrain including stairs and ramps, and operate efficiently during peak hours when campus foot traffic is highest.
+
+3. **Technology Integration and System Architecture**: Combining PolyU TAS LAB's cutting-edge research expertise in autonomous systems, localization, and navigation with SF Express(Hong Kong)'s extensive logistics experience and operational insights, alongside Rino AI's artificial intelligence capabilities and machine learning infrastructure. The collaboration will focus on developing a comprehensive technology stack that integrates perception, planning, and control systems with logistics management platforms. This includes creating robust communication protocols between autonomous vehicles and central dispatch systems, implementing edge computing solutions for real-time decision-making, and developing fail-safe mechanisms to ensure system reliability. The system architecture will incorporate multi-layer redundancy, cybersecurity measures to protect against potential threats, and scalable cloud infrastructure to support future expansion. Advanced sensor fusion techniques will combine data from multiple sources to create accurate environmental models, while deep learning algorithms will enable the vehicles to learn from experience and continuously improve their performance.
+
+4. **Pilot Programs and Field Testing**: Exploring opportunities to establish comprehensive testbed environments at PolyU campus for real-world validation and demonstration of autonomous delivery technologies. The pilot programs will serve as living laboratories where researchers can collect operational data, test new algorithms, and refine system performance under actual operating conditions. The testbed will enable iterative development and validation of technologies before broader deployment, allowing the team to address challenges related to weather conditions, varying terrain, obstacle avoidance, and user acceptance. Data collected from these pilot programs will inform future system improvements and provide valuable insights for scaling the technology to other campuses and urban environments. The pilot phase will include controlled experiments to test specific capabilities, followed by gradual expansion to full operational deployment. User feedback mechanisms will be integrated to gather insights from students, faculty, and staff about their experiences with the autonomous delivery system, helping to refine user interfaces and improve overall service quality.
+
+5. **Safety and Regulatory Compliance**: Developing comprehensive safety protocols and working toward compliance with local regulations governing autonomous vehicle operations in Hong Kong. This includes establishing safety standards for autonomous campus delivery, conducting thorough risk assessments, implementing redundant safety systems with multiple fail-safe mechanisms, and collaborating with regulatory bodies to ensure that autonomous delivery vehicles meet all necessary requirements for operation in public spaces. The collaboration will work closely with university safety departments, local transportation authorities, and industry standards organizations to develop best practices for autonomous delivery operations. Safety features will include emergency braking systems, collision avoidance algorithms, remote monitoring and intervention capabilities, and comprehensive logging of all operational data for incident investigation and continuous improvement.
diff --git a/_events/2026-01-30-Sandbox_Demonstration_at_Pak_Shak_Kok.md b/_events/2026-01-30-Sandbox_Demonstration_at_Pak_Shak_Kok.md
new file mode 100644
index 000000000..20c0912c0
--- /dev/null
+++ b/_events/2026-01-30-Sandbox_Demonstration_at_Pak_Shak_Kok.md
@@ -0,0 +1,52 @@
+---
+title: Team Successfully Conducts Our First Cross-Sea Logistics Flight for Hong Kong Low-altitude Economy Regulatory Sandbox
+subtitle: news
+image: images/news/0130Sandbox/pic2.jpg
+tags:
+ - news
+ - low-altitude economy
+ - logistics
+---
+
+
+
+
+
+## Team Successfully Conducts Our First Cross-Sea Logistics Flight for Hong Kong Low-altitude Economy Regulatory Sandbox
+
+On January 30, 2026, our team marked a significant milestone by successfully completing our first cross-sea logistics test flight for Phase 1 of the **Hong Kong Low-altitude Economy Regulatory Sandbox**.
+
+
+
+
+
+
+
+
+
+
+
+This critical test flight was executed with the strong support and on-site witnessing of the Civil Aviation Department (CAD) of Hong Kong and our collaborative partners. The operation successfully validated the stability and reliability of our logistics solution within the sandbox's framework.
+
+
+
+
+
+### Valuable Experience and Future Outlook
+
+We would like to extend our sincere gratitude to the Hong Kong CAD and our partners for their unwavering support of our research and operational efforts.
+
+This successful flight has allowed us to accumulate valuable flight data and operational experience specific to cross-sea logistics. We look forward to continuing our work and contributing further to the robust development of Hong Kong's low-altitude economy.
+
+### Acknowledgements
+
+We extend our sincere appreciation to our partners for their support of our research (listed in no particular order):
+
+* [Hong Kong Applied Science and Technology Research Institute Company Limited](https://www.astri.org/)
+* [SUPTC Digital Technology (Hong Kong) Limited](http://www.sutpc.com/)
+* [Leisure and Cultural Services Department](https://www.lcsd.gov.hk/)
+* [Hong Kong Broadband Network Enterprise Solutions](https://www.hkbn.net/enterprise/)
diff --git a/_events/2026-02-02-ICRA2026_Acceptance.md b/_events/2026-02-02-ICRA2026_Acceptance.md
new file mode 100644
index 000000000..bee86e9be
--- /dev/null
+++ b/_events/2026-02-02-ICRA2026_Acceptance.md
@@ -0,0 +1,22 @@
+---
+title: Our paper is accepted by IEEE ICRA 2026
+subtitle: Example news
+# author: xxx
+image: images/news/2026ICRA/system_framework.png
+tags: news
+order:
+---
+
+It is great to share that our paper (“Integrated Planning and Control on Manifolds: Factor Graph Representation and Toolkit” by Peiwen Yang, Weisong Wen, Runqiu Yang, Yuanyuan Zhang, Jiahao Hu, Yingming Chen, Naigui Xiao and Jiaqi Zhao) is accepted by the 2026 IEEE International Conference on Robotics & Automation. Congratulations to Peiwen and etc.!
+
+## Abstract
+
+Model predictive control (MPC) faces significant limitations when applied to systems evolving on nonlinear manifolds, such as robotic attitude dynamics and constrained motion planning, where traditional Euclidean formulations struggle with singularities, over-parameterization, and poor convergence. To overcome these challenges, this paper introduces FactorMPC, a factor-graph based MPC toolkit that unifies system dynamics, constraints, and objectives into a modular, user-friendly, and efficient optimization structure. Our approach natively supports manifold-valued states with Gaussian uncertainties modeled in tangent spaces. By exploiting the sparsity and probabilistic structure of factor graphs, the toolkit achieves real-time performance even for high-dimensional systems with complex constraints. The velocity-extended on-manifold control barrier function (CBF)-based obstacle avoidance factors are designed for safety-critical applications. By bridging graphical models with safety-critical MPC, our work offers a scalable and geometrically consistent framework for integrated planning and control. The simulations and experimental results on the quadrotor demonstrate superior trajectory tracking and obstacle avoidance performance compared to baseline methods. To foster research reproducibility, we have provided open-source implementation offering plug-and-play factors. Code and supplementary materials available at: https://github.com/RoboticsPolyu/FactorMPC.
+
+## System Framework
+
+
+
+
+
diff --git a/_events/2026-02-02-ICRA2026_workshop.md b/_events/2026-02-02-ICRA2026_workshop.md
new file mode 100644
index 000000000..c75bb155b
--- /dev/null
+++ b/_events/2026-02-02-ICRA2026_workshop.md
@@ -0,0 +1,25 @@
+---
+title: Our workshop is accepted by IEEE ICRA 2026
+subtitle: Example news
+# author: xxx
+image: images/news/2026ICRA/Poster_WS_RobotMeetsGNSSRanging.png
+tags: news
+order:
+---
+
+We’re organizing the 1st Workshop on Robot Meets GNSS and Ranging for Seamless Autonomy, happening on Friday, June 5, 2026 in Vienna.
+If you work on reliable autonomy in the real world—especially where GNSS/UWB/ranging gets messy—this workshop is for you. You can find more details from the [workshop page](https://robotmeetsranging.tech/)
+
+
+
+
+
+
+
+
+
+Recognizing shared challenges in sensor integration, error modeling, integrity monitoring, and certifiable optimization of ranging observations from diverse systems (e.g., GNSS, Ultra-Wideband), this event emphasizes the critical role of ranging technologies in resilient robot navigation. It aims to identify open problems and promising research directions across domains, bringing together researchers from diverse communities to exchange knowledge and foster collaboration.
+
+TAS Lab remains at the forefront of research dedicated to creating safer, more efficient, and intelligent robotics solutions for the future.
+
diff --git a/_events/2026-02-04-CFSO_WuxiRI.md b/_events/2026-02-04-CFSO_WuxiRI.md
new file mode 100644
index 000000000..5e78c6baa
--- /dev/null
+++ b/_events/2026-02-04-CFSO_WuxiRI.md
@@ -0,0 +1,50 @@
+---
+title: PolyU CFSO Delegation Visits Wuxi Research Institute and Observes Smart Drone Cleaning Demo in Shanghai
+subtitle: news
+image: images/news/20260204_CFSO_WuxiRI/1.jpg
+tags: news
+---
+
+## PolyU CFSO Delegation Visits Wuxi Research Institute and Observes Smart Drone Cleaning Demo in Shanghai
+
+Today, a delegation from the **Campus Facilities and Sustainability Office (CFSO)** of The Hong Kong Polytechnic University (PolyU), including **Mr. Wong** and **Mr. Cheung**, accompanied by **Dr. Wang ** from the PolyU Wenzhou Research Institute, visited the **PolyU Wuxi Technology and Innovation Research Institute** and the **Shanghai Sanlin Low-altitude Economy Industrial Park** for technical exchange and guidance.
+
+### Insight into Advanced Sensing and Inspection Technology
+
+At the Wuxi Technology and Innovation Research Institute, our team introduced the center's latest developments and core research areas to the delegation.
+
+The visit included a demonstration of our **handheld data collection and mapping devices, as well as indoor positioning devices**, showcasing how rapid environmental digitization supports smart facility management.
+
+
+
+
+
+Subsequently, the delegation proceeded to the **indoor flight testing field** to witness a live demonstration of our autonomous inspection drones.
+
+These drones are equipped with advanced sensors and navigation systems, allowing them to:
+* Fly autonomously in complex environments (such as tunnels or indoor structures).
+* Perceive surroundings and avoid obstacles in real-time.
+* Utilize **AI algorithms** to automatically analyze data and identify potential structural defects.
+
+
+
+
+
+
+### Witnessing the Future of Building Maintenance in Shanghai
+
+Following the visit to Wuxi, the delegation traveled to the **Shanghai Sanlin Low-altitude Economy Industrial Park**. Here, they observed a field demonstration of our **Smart Building Cleaning Drone**.
+
+The demonstration highlighted the drone's stability and efficiency in high-rise façade maintenance, presenting a safer and more automated alternative to traditional cleaning methods. The CFSO delegation expressed strong interest in how these low-altitude economy solutions could be applied to smart campus management and sustainability efforts in the future.
+
+
+
+
+
+
+Reference Press Release: [https://mp.weixin.qq.com/s/HvCxbZXmLE4ve5UVuRo08g](https://www.bilibili.com/video/BV12kcgztEgQ/?spm_id_from=333.1387.homepage.video_card.click)
+
+---
diff --git a/_events/2026-03-05-Prof_Wen_Deep_Space_Robotics_Report.md b/_events/2026-03-05-Prof_Wen_Deep_Space_Robotics_Report.md
new file mode 100644
index 000000000..96c2fdbf5
--- /dev/null
+++ b/_events/2026-03-05-Prof_Wen_Deep_Space_Robotics_Report.md
@@ -0,0 +1,49 @@
+---
+title: Prof. Wen's Team Featured in PolyU Deep-Space Robotics Report
+subtitle:
+# author: Yingming Chen
+image: images/news/20260305_deep_space_robotics/video_cover.jpg
+tags: news
+order:
+---
+
+## Prof. Wen's Team Featured in PolyU Deep-Space Robotics Report
+
+On March 5, 2026, The Hong Kong Polytechnic University published a feature story titled “两会热点！理大深空造梦者实践科学家精神”, highlighting PolyU researchers whose work supports national priorities in high-level scientific and technological self-reliance, frontier innovation, and the spirit of scientists. Among the featured researchers, Prof. Weisong WEN and his team were introduced for their vision and research direction in deep-space robotics.
+
+
+
+
Prof. Weisong WEN and his team were featured in the PolyU report on deep-space robotics.
+
+
+The report presented Prof. WEN as a forward-looking researcher in robotics, emphasizing that future deep-space robots must go beyond basic mobility. For lunar and planetary missions, robots should be able to move steadily, operate reliably over long distances, and complete complex tasks in harsh, uncertain, and remote environments. This vision closely connects with TASLAB's long-term research strengths in trustworthy autonomous systems, robotic navigation, multi-sensor fusion, SLAM, localization, and intelligent decision-making.
+
+A key achievement highlighted in the report is the team's effort to develop intelligent robotic systems for lunar exploration. In such missions, robots are expected to serve as reliable carriers and autonomous agents, capable of performing designated tasks on the lunar surface. These systems require robust perception, precise localization, safe motion planning, and dependable control, especially when operating under limited communication, difficult terrain, and extreme environmental conditions.
+
+Prof. WEN further shared a three-stage development roadmap for deep-space robotics:
+
+1. **Reliable robotic platforms**: Develop intelligent robot carriers for lunar exploration, enabling robots to perform assigned tasks on the lunar surface with stability and robustness.
+2. **Earth-Moon communication and navigation networks**: Build the infrastructure for real-time data transmission and interaction among robots, Earth, and future lunar bases. The report also highlighted Prof. WEN's insight that one day the Moon may have navigation services similar to GPS on Earth.
+3. **Intelligent robotic brains**: Equip future robots with stronger autonomy, including environmental perception, decision-making, fault diagnosis, and self-recovery capabilities. In this vision, robots will not only execute commands, but also understand situations, respond to failures, and support long-duration missions more independently.
+
+
+
+
The feature story showcased Prof. WEN's vision for the future of lunar and deep-space robots.
+
+
+The feature also reflected the broader value of interdisciplinary research at PolyU. Deep-space robotics requires the integration of aerospace engineering, artificial intelligence, robotics, communication, navigation, and advanced autonomy. By advancing trustworthy robotic systems for extreme environments, Prof. WEN and TASLAB aim to contribute not only to future lunar exploration, but also to practical autonomous technologies that can benefit transportation, inspection, low-altitude autonomy, and service robotics on Earth.
+
+Through continuous experimentation, system integration, and iterative engineering, TASLAB will keep pursuing robust and trustworthy autonomy for challenging real-world and off-world environments. The team's future work will focus on reliable robotic platforms, resilient navigation and communication, and intelligent decision-making systems, supporting the long-term vision of enabling robots to explore, work, and cooperate safely in the most demanding environments.
+
+
+
+
+
+
+Original feature by PolyU WeChat: [两会热点！理大深空造梦者实践科学家精神](https://mp.weixin.qq.com/s?__biz=MzU3MTkzMzg5MQ==&mid=2247590158&idx=1&sn=7534d662ccc782b111347f68bd793bfd&chksm=fd7e2a09065a324edb3231ea3f776c24b4f271c0369d1cf7e11f9f07b9c1cfbce971e4840810&scene=27).
diff --git a/_events/2026-03-09-Genvict_visit.md b/_events/2026-03-09-Genvict_visit.md
new file mode 100644
index 000000000..f5b2b28a5
--- /dev/null
+++ b/_events/2026-03-09-Genvict_visit.md
@@ -0,0 +1,24 @@
+---
+title: TAS Team Meets with Genvict to Discuss Smart Mobility Collaboration
+subtitle:
+# author: hf
+image: images/news/20260309_Genvict/genvict_1.jpg
+tags: news
+order:
+---
+
+## TAS Team Meets with Genvict to Discuss Smart Mobility Collaboration
+
+The Hong Kong Polytechnic University’s Trustworthy AI and Autonomous Systems Laboratory (TAS LAB) held a strategic cooperation meeting with Shenzhen Genvict Technologies Co., Ltd., a leading end-to-end provider of mobility intelligence solutions specializing in electronic toll collection (ETC), smart urban mobility, and cooperative ITS (C-ITS). The meeting explored collaborative opportunities in smart mobility and the low-altitude economy. This engagement underscores PolyU’s commitment to advancing industry–academia partnerships and developing practical solutions for next-generation transportation systems that address real-world challenges in urban and highway mobility.
+
+
+
+
+
+
+
+
+
+The meeting highlighted joint R&D directions in intelligent transportation, including AI-driven traffic management, robotics-enabled last-mile delivery, sensor-fusion-based perception for C-ITS, and IoT connectivity for real-time fleet and infrastructure optimization. Both parties emphasized deployable pilots for smart mobility, and multimodal coordination across agents, micromobility, and service vehicles.
diff --git a/_events/2026-03-12-CICV.md b/_events/2026-03-12-CICV.md
new file mode 100644
index 000000000..196f196f4
--- /dev/null
+++ b/_events/2026-03-12-CICV.md
@@ -0,0 +1,29 @@
+---
+title: China Intelligent & Connected Vehicles (Beijing) Research Institute visit PolyU
+subtitle:
+# author: hf
+image: images/news/20260312_chinaicv/discussion.jpg
+tags: news
+order:
+---
+
+## China Intelligent & Connected Vehicles (Beijing) Research Institute visit PolyU
+
+China Intelligent & Connected Vehicles (Beijing) Research Institute (CICV) visited PolyU on March 12. The meeting explored collaborative opportunities in vehicle security, wireless charging, V2X, the low‑altitude economy, and embedded AI with representatives from PolyU. This engagement underscores PolyU’s commitment to advancing industry–academia partnerships and developing practical solutions for next‑generation transportation systems that address real‑world challenges.
+
+
+
+
+
+
+
+
+
+
+## About CICV
+
+CICV was jointly initiated by China Society of Automotive Engineers (China SAE), China Association of Automobile Manufacturers (CAAM) and China Industry Innovation Alliance for the Intelligent and Connected Vehicles (CAICV). The company has 10 departments and 153 employees.
+
+
diff --git a/_events/2026-04-21-CEO_CLUB.md b/_events/2026-04-21-CEO_CLUB.md
new file mode 100644
index 000000000..8bc08f342
--- /dev/null
+++ b/_events/2026-04-21-CEO_CLUB.md
@@ -0,0 +1,25 @@
+---
+title: Quadruped Robot Showcase by TAS Members at the Inauguration of the 10th Executive Committee of the PolyU CEO Club
+subtitle:
+# author: hf
+image: images/news/20260421_ceoclub/1.jpg
+tags: news
+order:
+---
+
+## Quadruped Robot Showcase by TAS Members at the Inauguration of the 10th Executive Committee of the PolyU CEO Club
+
+TAS members Dr. Runqiu Yang and Mr. Junzhe Wang showcased a robotic dog at The Inauguration of the 10th Executive Committee of the PolyU CEO Club, where they presented PolyU’s latest advances in intelligent robotics and engaged with business leaders and distinguished guests on its potential applications in inspection, assistive operations, emergency response, and other real-world scenarios, highlighting the University’s commitment to innovation, knowledge transfer, and industry collaboration.
+
+
+
+
+
+
+
+
+
+
+
diff --git a/_events/2026-05-06-HKU_WorkShop.md b/_events/2026-05-06-HKU_WorkShop.md
new file mode 100644
index 000000000..d522b4671
--- /dev/null
+++ b/_events/2026-05-06-HKU_WorkShop.md
@@ -0,0 +1,25 @@
+---
+title: 1st Research Workshop of Safety of AI-Driven Autonomous Systems:From Intelligent Connected Vehicles to the Low-Altitude Economy
+subtitle:
+# author: hf
+image: images/news/20260506_hkuworkshop/1.jpg
+tags: news
+order:
+---
+
+## 1st Research Workshop of Safety of AI-Driven Autonomous Systems: From Intelligent Connected Vehicles to the Low-Altitude Economy
+
+Prof. WEN attended the 1st Research Workshop of Safety of AI-Driven Autonomous Systems: From Intelligent Connected Vehicles to the Low-Altitude Economy, held on May 6, 2026 at CPD-2.58, Mok Sau King Lecture Hall, HKU. During the workshop, Prof. WEN introduced our recent research progress on GNSS/SLAM localization, multi-sensor fusion, and urban autonomous navigation. The presentation highlighted our efforts in developing robust localization and perception technologies for intelligent autonomous systems operating in complex urban environments, and promoted future collaboration in safe AI-driven mobility and low-altitude autonomy.
+
+
+
+
+
+
+
+
+
+
diff --git a/_events/2026-05-07-RCUAS_WorkShop.md b/_events/2026-05-07-RCUAS_WorkShop.md
new file mode 100644
index 000000000..8c8f9ad0e
--- /dev/null
+++ b/_events/2026-05-07-RCUAS_WorkShop.md
@@ -0,0 +1,71 @@
+---
+title: The 2nd Research Workshop for RCUAS
+subtitle:
+# author: hf
+image: images/news/20260507_rcuas_workshop/2.jpg
+tags: news
+order:
+---
+
+## The 2nd Research Workshop for RCUAS
+
+The Research Centre for Unmanned Autonomous Systems (RCUAS) at The Hong Kong Polytechnic University (PolyU) successfully hosted its 2nd Research Workshop of RCUAS on May 7, 2026 at PolyU campus, bringing together leading scholars, industry experts, and students to explore the future of intelligent autonomous technologies.
+
+The event showcased PolyU's growing leadership in unmanned autonomous systems, serving as a dynamic platform for knowledge exchange and collaboration across academia and industry. Participants engaged in lively discussions on autonomous systems, embodied intelligence, trustworthy AI, robotics, and applications to the low-altitude economy.
+
+
+
+
+
+### Morning Session
+
+The workshop was opened with opening remarks by Professor Chih-Yung Wen, Director of RCUAS and Chair Professor of Aeronautical Engineering at the Department of Aeronautical and Aviation Engineering (AAE). He highlighted the critical role of interdisciplinary collaboration in advancing cutting-edge research that addresses major societal and industrial needs.
+
+The morning session featured a series of talks addressing cutting-edge research challenges in robotics and intelligent systems. Professor Boyu Zhou from the Southern University of Science and Technology shared recent progress in efficient active perception and mobile manipulation, while Prof. Chen Sun from The University of Hong Kong spoke on trustworthy driving intelligence, focusing on the challenges of generalization, safety, and deployment in autonomous driving systems.
+
+Dr Xiaofei Li, CEO of Simple AI Technology, explored the rapid rise of embodied intelligence and offered perspectives on the next stage of AI development. Mr Leo Liu, CTO of Gammon Construction Limited, examined the transformative potential of autonomous systems in the construction sector, along with the practical challenges of industry integration.
+
+A particularly engaging open discussion session before lunch brought together professors and industry leaders to reflect on how academia can build distinctive research strengths amid the rapid advancement of industrial AI and autonomous technologies.
+
+
+
+
Speakers at the 2nd Research Workshop for RCUAS.
+
+
+### Afternoon Session
+
+The afternoon session continued with talks highlighting breakthroughs in robust autonomous driving, SLAM technologies, digital twins, and drone applications. Professor Chengzhong Xu, IEEE Fellow and Dean of the Faculty of Science and Technology at the University of Macau, shared research on robust autonomous driving in mixed traffic environments.
+
+Dr Jianhao Jiao from PolyU presented his insights on lifelong spatial memory and navigation for legged robots through advanced SLAM techniques. Mr Tony Chan from Esri China (Hong Kong) Limited introduced the role of GIS and living digital twin technologies in supporting the development of the low-altitude economy. Mr Dylan Tyack, Founder and Managing Director of Drone Solutions Asia, discussed practical drone operations and the exciting opportunities they present for Hong Kong's low-altitude economy.
+
+
+
+
Speakers at the 2nd Research Workshop for RCUAS.
+
+
+### Demo Session & Poster Session
+
+Beyond the presentations, the workshop featured demonstration sessions, poster presentations of RCUAS's research outputs, and interactive exchanges, creating valuable opportunities for participants to connect, share ideas, and spark new collaborations.
+
+
+
+
Poster session at the 2nd Research Workshop for RCUAS.
+
+
+Through this successful event, RCUAS once again demonstrated its dedication to fostering world-class interdisciplinary research and strengthening ties between universities and industry. By bridging academic excellence with practical application, PolyU continues to drive innovation in intelligent autonomous technologies and support their transformative impact across transportation, robotics, urban infrastructure and aerospace engineering.
+
+More details can be found on the [PolyU RCUAS news page](https://www.polyu.edu.hk/rcuas/news-and-events/news/2026/20260507_2nd-research-workshop-for-rcuas/).
+
+
+
+
+
Group photo at the 2nd Research Workshop for RCUAS.
+
+
+
+
diff --git a/_events/2026-05-15-HKSTPSZ-Visit.md b/_events/2026-05-15-HKSTPSZ-Visit.md
new file mode 100644
index 000000000..5198ca143
--- /dev/null
+++ b/_events/2026-05-15-HKSTPSZ-Visit.md
@@ -0,0 +1,66 @@
+---
+title: TASLAB Visits HKSTPSZ and Experiences Autonomous Cross-Border Bus with ASTRI
+subtitle:
+# author: Ziqi ZHANG
+image: images/news/260515-SZHKSTP/9.jpg
+tags: news
+order:
+---
+
+## TASLAB Visits HKSTPSZ and Experiences Autonomous Cross-Border Bus with ASTRI
+
+On May 15, 2026, TASLAB member Dr. Huang Feng, Mr. Zhang Ziqi, Mr. Qin Qijun visited the Hong Kong Science Park Shenzhen Branch (HKSTPSZ) and had a meeting with ASTRI members for an on-site technology exchange. During the visit, the team toured HKSTPSZ, experienced the autonomous cross-border bus, and discussed future research collaboration with ASTRI in intelligent transportation, autonomous driving, and cross-border mobility technologies.
+
+
+
+
TASLAB members with the autonomous bus at HKSTPSZ.
+
+
+
+
+
Group photo after the autonomous bus experience.
+
+
+
+
+
Autonomous bus demonstration at HKSTPSZ.
+
+
+
+
+
Inside the autonomous bus during the on-road experience.
+
+
+
+
+
Autonomous bus ready for the demonstration ride.
+
+
+
+
+
Autonomous bus operating in the HKSTPSZ campus environment.
+
+
+
+
+
Autonomous bus displayed at HKSTPSZ.
+
+
+
+
+
Autonomous bus demonstration area at HKSTPSZ.
+
+
+
+
+
Discussion near the autonomous bus after the technology experience.
+
diff --git a/_events/2026-05-31-Congratulations_to_Dr_Yang_and_Dr_Jiao.md b/_events/2026-05-31-Congratulations_to_Dr_Yang_and_Dr_Jiao.md
new file mode 100644
index 000000000..d556379ae
--- /dev/null
+++ b/_events/2026-05-31-Congratulations_to_Dr_Yang_and_Dr_Jiao.md
@@ -0,0 +1,26 @@
+---
+title: Warm Congratulations to Dr. Yang and Dr. Jiao
+subtitle:
+# author: Yingming Chen
+image: images/news/0531_celebration/celebration_highres.jpg
+tags: news
+order:
+---
+
+## Warm Congratulations to Dr. Yang and Dr. Jiao
+
+On May 31, 2026, TASLAB members gathered together to celebrate two experienced and respected members, Dr. Runqiu Yang and Dr. Jianhao Jiao, as they prepare to begin exciting new career chapters.
+
+Dr. Runqiu Yang has accepted an offer from XSquare, a leading company in embodied intelligence. During his time with TASLAB, Dr. Yang has contributed valuable expertise in optimal control, model predictive control, reinforcement learning, aerospace engineering, and robotics. His rigorous research attitude, professional dedication, and warm support for fellow group members have been deeply appreciated by the team.
+
+Dr. Jianhao Jiao will continue his career with China Merchants Group. As an outstanding researcher in SLAM, sensor fusion, and robust robotic navigation, Dr. Jiao has made important contributions to TASLAB's research development and academic environment. His experience, insight, and collegial spirit have been highly respected by group members.
+
+These excellent offers reflect the strong research achievements, technical capabilities, and professional recognition of Dr. Yang and Dr. Jiao. The gathering was filled with sincere congratulations, appreciation, and best wishes from the TASLAB family.
+
+TASLAB warmly congratulates Dr. Yang and Dr. Jiao on their new appointments, and sincerely thanks them for their dedication and contributions to the group. We wish them every success in their future careers and look forward to seeing their continued impact in intelligent autonomous systems and related industries.
+
+
+
+
Warm congratulations to Dr. Runqiu Yang and Dr. Jianhao Jiao.
+
diff --git a/_events/2026-06-03-Zhuhai_High-tech_Zone_Delegation_Visits_TASLAB.md b/_events/2026-06-03-Zhuhai_High-tech_Zone_Delegation_Visits_TASLAB.md
new file mode 100644
index 000000000..413d03a76
--- /dev/null
+++ b/_events/2026-06-03-Zhuhai_High-tech_Zone_Delegation_Visits_TASLAB.md
@@ -0,0 +1,44 @@
+---
+title: Zhuhai High-tech Zone Delegation Visits TASLAB to Explore Technology Transfer and Project Collaboration
+subtitle:
+# author:
+image: images/news/20260603_zhuhai/1.jpg
+tags: news
+order:
+---
+
+## Zhuhai High-tech Zone Delegation Visits TASLAB to Explore Technology Transfer and Project Collaboration
+
+On June 3, 2026, a delegation from the Zhuhai High-tech Industrial Development Zone visited the Trustworthy AI and Autonomous Systems Laboratory (TASLAB) at The Hong Kong Polytechnic University for an exchange on intelligent autonomous systems, technology transfer, and potential project implementation.
+
+The delegation included Ms. Yang Xiao, Deputy Director of the Administrative Committee of Zhuhai High-tech Industrial Development Zone; Mr. Wu Weizhong, Secretary of the Party Leadership Group of the Development, Reform and Finance Bureau of Zhuhai High-tech Industrial Development Zone and Secretary of the District State-owned Enterprises Party Committee; Mr. Liao Yuxin, First-level Officer of the Development, Reform and Finance Bureau of Zhuhai High-tech Industrial Development Zone; Mr. Li Lin, General Manager of Zhuhai Gotech Financial Investment Venture Capital Management Co., Ltd.; and Mr. Yuan Shengjia, Manager of the Post-investment Management Department of Zhuhai Gotech Financial Investment Venture Capital Management Co., Ltd.
+
+During the visit, the TASLAB team introduced the laboratory's research progress in trustworthy artificial intelligence, autonomous systems, intelligent perception, navigation, and robotic technologies. The delegation toured the laboratory and learned about its unmanned aerial vehicles, quadruped robots, autonomous vehicles, and other experimental platforms, as well as their potential applications in complex-environment perception, autonomous decision-making, multi-platform collaboration, and intelligent equipment.
+
+In the subsequent discussion, both sides exchanged views on the industrial development needs of Zhuhai High-tech Zone, the commercialization of research outcomes, and possible pathways for implementing collaborative projects. The discussion highlighted opportunities to combine TASLAB's research and innovation capabilities with Zhuhai High-tech Zone's industrial foundation, policy support, and investment resources, with the aim of promoting practical applications of intelligent autonomous systems.
+
+The visit strengthened mutual understanding and laid a solid foundation for further collaboration in intelligent autonomous systems, low-altitude economy, robotics, and related fields.
+
+
+
+
The Zhuhai High-tech Zone delegation and the TASLAB team discuss technology transfer and potential project collaboration.
+
+
+
+
+
The delegation visits TASLAB and learns about its autonomous systems research and experimental platforms.
+
+
+
+
+
Group photo of the Zhuhai High-tech Zone delegation and TASLAB members.
+
+
+
+
+
The delegation and laboratory members at the Department of Aeronautical and Aviation Engineering.
+
diff --git a/_events/2026-06-05-ICRA2026_Workshop_and_Paper.md b/_events/2026-06-05-ICRA2026_Workshop_and_Paper.md
new file mode 100644
index 000000000..9d55b602c
--- /dev/null
+++ b/_events/2026-06-05-ICRA2026_Workshop_and_Paper.md
@@ -0,0 +1,44 @@
+---
+title: TASLAB Hosts ICRA 2026 Workshop and Presents Accepted Paper
+subtitle:
+# author: hf
+image: images/news/20260605_icra2026_workshop/group_photo.jpg
+tags: news
+order:
+---
+
+## TASLAB Hosts ICRA 2026 Workshop and Presents Accepted Paper
+
+TASLAB is pleased to share that our team hosted the 1st Workshop on Robot Meets GNSS and Ranging for Seamless Autonomy at the 2026 IEEE International Conference on Robotics and Automation (ICRA 2026), held in Vienna, Austria. The workshop brought together researchers from robotics, navigation, positioning, and intelligent transportation communities to discuss how GNSS, UWB, ranging, and multi-sensor fusion technologies can support reliable robot autonomy in complex real-world environments.
+
+The workshop focused on shared challenges in sensor integration, ranging error modeling, integrity monitoring, robust localization, and certifiable optimization for autonomous systems. Through invited talks, technical presentations, and discussions, participants exchanged ideas on how ranging technologies can improve the safety, continuity, and resilience of robot navigation.
+
+In addition to hosting the workshop, our paper, "Integrated Planning and Control on Manifolds: Factor Graph Representation and Toolkit", by Peiwen Yang, Weisong Wen, Runqiu Yang, Yuanyuan Zhang, Jiahao Hu, Yingming Chen, Naigui Xiao and Jiaqi Zhao, was accepted by ICRA 2026. The paper introduces FactorMPC, a factor-graph based model predictive control toolkit for systems evolving on nonlinear manifolds, supporting geometrically consistent planning and control for robotics applications.
+
+The successful workshop and paper acceptance highlight TASLAB's continued efforts in robust navigation, GNSS/ranging-aided autonomy, factor graph optimization, and safety-aware planning and control for intelligent autonomous systems.
+
+More details about the workshop can be found on the [workshop page](https://robotmeetsranging.tech/).
+
+
+
+
TASLAB members at the ICRA 2026 workshop venue in Vienna.
+
+
+
+
+
Opening remarks for the 1st Workshop on Robot Meets GNSS and Ranging for Seamless Autonomy.
+
+
+
+
+
Presentation related to factor graphs, world models, and planning-control integration at ICRA 2026.
+
+
+
+
+
Group photo from the ICRA 2026 Robot Meets GNSS and Ranging workshop.
+
diff --git a/_events/2026-06-05-TASLAB-Supports-PolyU-AI-and-Robotics-Club.md b/_events/2026-06-05-TASLAB-Supports-PolyU-AI-and-Robotics-Club.md
new file mode 100644
index 000000000..5b76fae64
--- /dev/null
+++ b/_events/2026-06-05-TASLAB-Supports-PolyU-AI-and-Robotics-Club.md
@@ -0,0 +1,20 @@
+---
+title: TASLAB to Support the Supervision of the PolyU AI and Robotics Club
+subtitle:
+# author: Ziqi ZHANG
+image: images/news/260605-club/cover.png
+tags: news
+order:
+---
+
+## TASLAB to Support the Supervision of the PolyU AI and Robotics Club
+
+On June 5, 2026, TASLAB announced that it will help with the supervision of the PolyU AI and Robotics Club as a record of its support for student-led innovation in artificial intelligence and robotics. The effort will be led by Prof. Weisong Wen, with support from the PolyU Faculty of Engineering, Ir Prof. H.C. Man, Dean of the Faculty of Engineering, and the PolyU Industrial Centre.
+
+Through this support, TASLAB will provide general academic and technical guidance for the club's future activities, helping connect student interests with research practice, engineering standards, and responsible technical development. With the broader support of the Faculty of Engineering and the Industrial Centre, the collaboration reflects TASLAB's continued commitment to supporting PolyU's robotics community and encouraging students to explore intelligent systems through project-based learning, technical exchange, and hands-on activities.
+
+
+
+
PolyU AI and Robotics Club logo.
+
diff --git a/_events/2026-06-25-Prof_Wen_ITSNT_2026.md b/_events/2026-06-25-Prof_Wen_ITSNT_2026.md
new file mode 100644
index 000000000..97ed34b32
--- /dev/null
+++ b/_events/2026-06-25-Prof_Wen_ITSNT_2026.md
@@ -0,0 +1,46 @@
+---
+title: Prof. Weisong Wen Presents at ITSNT 2026 on GNSS/LiDAR/Inertial Integrated Positioning
+subtitle:
+# author:
+image: images/news/20260625_itsnt/cover.jpg
+tags: news
+order:
+---
+
+## Prof. Weisong Wen Presents at ITSNT 2026 on GNSS/LiDAR/Inertial Integrated Positioning
+
+On June 25, 2026, Professor Weisong Wen, Director of the Trustworthy AI and Autonomous Systems Laboratory (TAS LAB) at The Hong Kong Polytechnic University (PolyU), presented at the International Technical Symposium on Navigation and Timing (ITSNT 2026), held at the École Nationale de l'Aviation Civile (ENAC) in Toulouse, France.
+
+As the opening speaker of Session 1 (chaired by Carl MILNER, ENAC), Prof. Wen presented on "Efficient and Outlier-Aware GNSS/LiDAR/inertial Integrated Positioning for Autonomous Systems in Urban Canyons" from 9:15 to 9:45 AM. His talk was featured alongside presentations from leading researchers at the European Space Agency (ESA), CNES, Stanford University, and other top institutions, highlighting TAS LAB's growing international visibility in navigation and timing research.
+
+
+
+
Prof. Weisong Wen at ITSNT 2026, ENAC, Toulouse, France.
+
+
+Prof. Wen's presentation traced a coherent research roadmap on trustworthy positioning in urban canyons, spanning from GNSS NLOS handling to tightly-coupled multi-sensor fusion. The talk covered several key research threads from TAS LAB, including:
+
+- 3D LiDAR Aided (3DLA) GNSS: A systematic progression from NLOS detection and exclusion to Doppler-aided direction-of-arrival estimation and reflection-path-based NLOS correction in dense urban environments.
+- 3DLA GNSS-RTK: An efficient factor-graph optimization framework integrating virtual satellites for geometry improvement and drift-free point-cloud-map-aided NLOS exclusion.
+- GLIO: A globally consistent, tightly-coupled GNSS/LiDAR/IMU odometry system for continuous and drift-free state estimation in urban areas ([open-source code on GitHub](https://github.com/XikunLiu-huskit/GLIO.git)).
+- GLIO2: A GPU-parallelized LiDAR–Inertial–GNSS framework designed for robust, real-time global localization on edge devices.
+- GNSS Integrity via Differentiable Protection Levels: A novel approach bridging robust robotics perception and aviation-grade integrity monitoring for safety-critical autonomous systems.
+
+
+
+
Prof. Wen presenting on factor graph optimization for GNSS/LiDAR/inertial integrated positioning at ITSNT 2026.
+
+
+The talk also showcased real-world applications of TAS LAB's positioning technologies, including autonomous facade-cleaning UAVs and guide-dog navigation systems for the visually impaired, demonstrating how robust multi-sensor fusion translates into practical solutions for safety-assured autonomous systems.
+
+Prof. Wen's participation at ITSNT 2026 reflects TAS LAB's commitment to advancing trustworthy AI and autonomous systems through cutting-edge research in urban navigation, multi-sensor fusion, and safety-assured positioning, as well as fostering international academic exchange with the global PNT community.
+
+
+
+
ENAC campus, the venue of ITSNT 2026 in Toulouse, France.
+
+
+More details about the symposium program can be found on the [ITSNT 2026 website](https://itsnt.fr/program/).
\ No newline at end of file
diff --git a/_events/2026-06-27-GNSS-Data-Collection-Volunteers.md b/_events/2026-06-27-GNSS-Data-Collection-Volunteers.md
new file mode 100644
index 000000000..4dad90e20
--- /dev/null
+++ b/_events/2026-06-27-GNSS-Data-Collection-Volunteers.md
@@ -0,0 +1,80 @@
+---
+title: High-Precision GNSS Data Collection - Volunteers Needed!
+subtitle: Join us in supporting cutting-edge GNSS positioning research
+image: images/news/gnss_volunteers/poster.png
+tags: news
+---
+
+## High-Precision GNSS Data Collection Project
+## Volunteers Needed!
+
+We are currently conducting a research project on **high-precision GNSS positioning in urban environments** and are looking for enthusiastic volunteers to assist with outdoor GNSS data collection and equipment cross-validation.
+
+---
+
+
+
+
+
+---
+
+### What You Will Do
+
+- **Conduct outdoor data collection** for 2–3 hours per session (flexible timing; good weather and low traffic preferred)
+- **Perform repeat collections** at the same location/trajectory for cross-validation
+- **Work with advanced equipment**: u-blox F9P receivers, NovAtel SPAN systems, U-center, and Google Earth
+
+---
+
+### Selected Scenarios in Hong Kong
+
+Data collection will be conducted at **carefully selected urban scenarios throughout Hong Kong**, where high-precision positioning is particularly challenging yet critical for autonomous systems research.
+
+---
+
+### Requirements & Preferences
+
+**Must have:**
+- A Windows laptop (to run logging software)
+- Basic knowledge of GNSS/navigation principles
+
+**Highly preferred:**
+- Prior experience with GNSS/GPS data collection
+- Familiarity with U-center (receiver configuration, data monitoring/logging)
+- Familiarity with NovAtel SPAN-CPT integrated navigation systems
+- Strict adherence to experimental protocols
+
+---
+
+### Rewards
+
+You will receive a **HK$400 supermarket voucher** for each successfully completed and valid task.
+
+✨ **You can participate multiple times, earning up to a maximum of HK$2,000!**
+
+---
+
+### How to Apply
+
+If you are interested in this opportunity, please **send your CV or a brief summary of your relevant experience** to the project coordinator. In your email, please also indicate:
+- The number of data collection sessions you would like to participate in
+- Your availability and preferred time slots
+- Any relevant experience you have with GNSS/GPS systems
+
+**Contact:** yixin.gao@connect.polyu.hk
+
+**Deadline:** June 27, 2026 (UTC+8:00)
+
+---
+
+### Why Join Us?
+
+This is an excellent opportunity to:
+- Contribute to cutting-edge autonomous systems research
+- Gain hands-on experience with professional GNSS equipment
+- Work with the **Trustworthy AI and Autonomous Systems Laboratory (TAS LAB)** at PolyU
+- Earn competitive compensation for your contribution
+
+The TAS LAB is actively advancing research in trustworthy AI and autonomous systems. Your participation will directly support our mission to develop reliable positioning solutions for urban environments.
diff --git a/_events/2026-06-29-Fuyao_Award_at_PolyU_Tsinghua_Alumni_Jiangsu_Visit.md b/_events/2026-06-29-Fuyao_Award_at_PolyU_Tsinghua_Alumni_Jiangsu_Visit.md
new file mode 100644
index 000000000..fbb4da6b4
--- /dev/null
+++ b/_events/2026-06-29-Fuyao_Award_at_PolyU_Tsinghua_Alumni_Jiangsu_Visit.md
@@ -0,0 +1,44 @@
+---
+title: TASLAB Project Receives Fuyao Award at PolyU-Tsinghua Alumni Association Jiangsu Visit
+subtitle:
+# author:
+image: images/news/20260629_jiangsu_alumni/fuyao_award.jpg
+tags: news
+order:
+---
+
+## TASLAB Project Receives Fuyao Award at PolyU-Tsinghua Alumni Association Jiangsu Visit
+
+On June 29, 2026, TASLAB participated in the PolyU-Tsinghua Alumni Association Jiangsu Visit and the PolyU industry-university-research achievements exhibition held in Wuxi. The event brought together university leaders, alumni representatives, government officials, research institutes, and industry partners to promote technology exchange, innovation collaboration, and the translation of research outcomes into real-world applications.
+
+During the event, TASLAB's project, "Safe, Trustworthy and AI-driven Intelligent UAV System for Building Facade Cleaning", received the Fuyao Award. The award recognizes the project's innovation in autonomous aerial operations, trustworthy AI, environmental perception, and intelligent robotic systems for high-rise facade cleaning. The project aims to improve the safety, efficiency, and intelligence of building exterior maintenance by integrating UAV autonomy, sensing, planning, and reliable control technologies.
+
+TASLAB also presented several research and technology products to attending guests, including GNSS/IMU positioning boards, the DroneExplorer ultra-visual exploration UAV, and self-developed UWB devices. Through on-site demonstrations and technical exchanges, the team introduced the laboratory's recent progress in high-precision navigation, autonomous exploration, multi-sensor fusion, and intelligent unmanned systems.
+
+Distinguished participants included Dr. Lam Tai-fai, Permanent Honorary President of the PolyU-Tsinghua Alumni Association and Chairman of the Council of The Hong Kong Polytechnic University; Professor Christopher Chao, Senior Vice President of PolyU; Professor Zijian Zheng, Vice President of PolyU; Professor Qiping Shen, Associate Vice President of PolyU; Professor Guoquan Huang, Director of the PolyU Wuxi Technology and Innovation Research Institute; and Professor Mingyuan Li, Deputy Director of the Institute. Ms. Zhu Xiaohong, Vice Chairperson of the CPPCC Xinwu District Committee, and Mr. Chen Weiliang, Secretary of the Party Working Committee and Director of the Administrative Committee of the Airport Economic Development Zone, as well as Secretary of the Shuofang Subdistrict Party Working Committee, also attended the event.
+
+The participation further strengthened TASLAB's engagement with the Yangtze River Delta innovation ecosystem and created valuable opportunities for collaboration in low-altitude economy, intelligent robotics, autonomous systems, and trusted AI applications.
+
+
+
+
TASLAB's intelligent UAV facade cleaning project receives the Fuyao Award.
+
+
+
+
+
TASLAB introduces UAV, navigation, and intelligent system technologies to guests during the exhibition.
+
+
+
+
+
TASLAB showcases its intelligent UAV facade cleaning system, GNSS/IMU boards, DroneExplorer UAV, and UWB devices.
+
+
+
+
+
Award recipients at the PolyU industry-university-research achievements exhibition.
+
diff --git a/_events/2026-06-30-Housing_Department_and_China_Resources_Visit_TASLAB.md b/_events/2026-06-30-Housing_Department_and_China_Resources_Visit_TASLAB.md
new file mode 100644
index 000000000..38fd4c6d3
--- /dev/null
+++ b/_events/2026-06-30-Housing_Department_and_China_Resources_Visit_TASLAB.md
@@ -0,0 +1,71 @@
+---
+title: Housing Department and China Resources Longdation Visit TASLAB for Drone Demonstration and Research Exchange
+subtitle:
+# author:
+image: images/news/20260630_housing_cr/1.jpg
+tags: news
+order:
+---
+
+## Housing Department and China Resources Longdation Visit TASLAB for Drone Demonstration and Research Exchange
+
+On June 30, 2026, representatives from the Housing Department and China Resources visited the Trustworthy AI and Autonomous Systems Laboratory (TASLAB) at The Hong Kong Polytechnic University for an exchange on autonomous systems, robotic technologies, and potential smart facility applications.
+
+The visiting representatives included PC Wang from the Housing Department and William Wong from China Resources. During the visit, the TASLAB team presented an indoor unmanned aerial vehicle demonstration in which a drone autonomously approached, picked up, transported, and released garments within a protected flight-testing environment.
+
+The demonstration showcased TASLAB's research progress in aerial autonomy, precision control, perception, and lightweight manipulation. It also provided a practical reference for discussing how autonomous systems may support future facility management scenarios, including object retrieval, inspection assistance, and operations in areas where manual handling may be inefficient or difficult.
+
+
+
+
TASLAB demonstrates an indoor drone garment pickup and transport task.
+
+
+
+
+
A second demonstration run shows the drone approaching the garment, lifting it, and returning toward the target area.
+
+
+After the demonstration, the visitors toured the laboratory and learned about TASLAB's experimental platforms, including unmanned aerial vehicles, robotic systems, sensing equipment, and other autonomous system research facilities. The tour provided an opportunity for further technical exchange on system reliability, deployment constraints, and the adaptation of laboratory research to real-world operating environments.
+
+
+
+
+
Representatives from the Housing Department and China Resources discuss TASLAB's autonomous systems research with laboratory members.
+
+
+
+
+
The visitors tour TASLAB and learn about its research platforms and experimental facilities.
+
+
+
+
+
The TASLAB team introduces autonomous robotic platforms and related research facilities during the laboratory tour.
+
+
+
+In the subsequent meeting, both sides discussed potential application needs, operational requirements, safety considerations, and possible pathways for future collaboration. The exchange highlighted shared interest in translating autonomous systems research into practical tools for smart building, property, and infrastructure-related scenarios.
+
+
+
+
The TASLAB team introduces related research during the meeting.
+
+
+The visit strengthened mutual understanding between the Housing Department, China Resources, and TASLAB, and laid a foundation for further dialogue on trustworthy autonomous systems and their practical deployment.
+
+
+
+
+
Group photo of representatives from the Housing Department and China Resources with TASLAB members at the Department of Aeronautical and Aviation Engineering.
diff --git a/_members/Ai_Kedai.md b/_members/Ai_Kedai.md
new file mode 100644
index 000000000..1e404d9a2
--- /dev/null
+++ b/_members/Ai_Kedai.md
@@ -0,0 +1,24 @@
+---
+name: Akida Tursun
+image: images/team/Akida.jpg
+role: ra # pi / postdoc / phd / ms / under / ra / visiting
+affiliation: PolyU-Wuxi Technology and innovation Research Institute
+order: 11
+
+links:
+ orcid:
+ email: Akida@hkpolyu-wxresearch.cn
+ profile:
+
+display_1:
+ - B.Eng.(Jiangnan University)
+display_2:
+ - June 2024 - Present
+---
+
+
+
+
+Akida received a Bachelor's degree in Management from Jiangnan University, with major courses including Principles of Management, Marketing, Consumer Behavior, Human Resource Management, etc. Currently, she works in the the Hong Kong Polytechnic University-Wuxi Research Institute, handling administrative and sales-related responsibilities.
+
+
diff --git a/_members/Bai_Lu.md b/_members/Bai_Lu.md
index b5a0e6024..116c3287d 100644
--- a/_members/Bai_Lu.md
+++ b/_members/Bai_Lu.md
@@ -1,7 +1,7 @@
---
name: Bai Lu
image: images/team/bai_lu.jpg
-role: postdoc # pi / postdoc / phd / ms / under / ra / visiting
+role: alumni # pi / postdoc / phd / ms / under / ra / visiting / alumni
affiliation: Hong Kong Polytechnic University
order: 5
@@ -10,16 +10,14 @@ links:
email: lubai@buaa.edu.cn
profile:
-display_1:
- - postdoc, Ph.D.(BUAA), M.Eng.(BUAA), B.Eng.(BUAA)
-display_2:
- - Feb 2025 - Present
+display_1: Ph.D.(BUAA), M.Eng.(BUAA), B.Eng.(BUAA)
+display_2: Postdoc (Feb 2025)
---
-Lu Bai (Member, IEEE) received the BEng degree and MEng in Electronic and Information Engineering from Beihang University, Beijing, China in 2014 and 2017, respectively. After that, she received the Ph.D. degree in communication and information systems from Beihang University, Beijing, China, in 2024.
+Lu Bai (Member, IEEE) received the BEng degree and MEng in Electronic and Information Engineering from Beihang University, Beijing, China in 2014 and 2017, respectively. After that, she received the Ph.D. degree in communication and information systems from Beihang University, Beijing, China, in 2024. She was a postdoctoral fellow at the Hong Kong Polytechnic University.
Her research focuses on GNSS-5G hybrid positioning methods, GNSS spoofing detection and interference mitigation techniques.
**Research Areas**
diff --git a/_members/Chen_Hongchang.md b/_members/Chen_Hongchang.md
new file mode 100644
index 000000000..c0dd6130f
--- /dev/null
+++ b/_members/Chen_Hongchang.md
@@ -0,0 +1,28 @@
+---
+name: Chen Hongchang
+image: images/team/hongchang.jpg
+role: phd
+affiliation: Hong Kong Polytechnic University
+order: 1
+
+links:
+ home-page:
+ orcid: 0009-0007-8094-5926
+ google-scholar:
+ github:
+ email: hongchang.chen@connect.polyu.hk
+ profile:
+
+display_1: Ph.D.(PolyU), M.Eng.(BIT), B.Eng. (HNU)
+display_2:
+---
+
+
+
+
+Hongchang Chen received his M.S. degree from school of Mechanical Engineering at Beijing Institute of Technology, Beijing, China, in 2025. He is currently pursuing his Ph.D. degree at The Hong Kong Polytechnic University (PolyU). His current research interests include Robotics and Computer Vision.
+
+
+
+**Research Areas**
+Autonomous Driving; Robotics; Computer Vision
diff --git a/_members/FenchiZHU_HEU_visiting.md b/_members/FenchiZHU_HEU_visiting.md
new file mode 100644
index 000000000..f6158eaff
--- /dev/null
+++ b/_members/FenchiZHU_HEU_visiting.md
@@ -0,0 +1,27 @@
+---
+name: Fengchi ZHU
+image: images/team/fengchiZHU.jpg
+role: visiting # pi / postdoc / phd / ms / under / ra / visiting
+affiliation: Harbin Engineering University
+order: 1
+
+links:
+ home-page: N/A
+ orcid: 0000-0002-1572-7769
+ google-scholar: BWgKaxcAAAAJ&hl=zh-CN
+ github: N/A
+ email: zfchiggins@163.com
+ profile:
+
+display_1: M.S and B.Eng. (HEU)
+display_2: Oct 2025
+
+---
+
+
+
+
+Fengchi Zhu received the B.S. degree in Automation from the College of Intelligent Systems Science and Engineering, Harbin Engineering University, in 2021, where he is currently working toward the Ph.D degree in control science and engineering. From Oct. 2025 to Mar. 2026, he is a visiting graduate researcher at the Department of Aeronautical and Aviation Engineering, Faculty of Engineering, The Hong Kong Polytechnic University. He won the Best Student Paper Award in 2023 IEEE International Conference on Mechatronics and Automation. His current research interests include state estimation, integrated navigation and cooperative navigation.
+
+**Research Areas**
+State estimation, Multi-agent Systems, Adaptive Kalman Filter
\ No newline at end of file
diff --git a/_members/GuangyanGuo_HEU_visiting.md b/_members/GuangyanGuo_HEU_visiting.md
new file mode 100644
index 000000000..da555152e
--- /dev/null
+++ b/_members/GuangyanGuo_HEU_visiting.md
@@ -0,0 +1,27 @@
+---
+name: Guangyan Guo
+image: images/team/guangyanGuo.jpg
+role: visiting # pi / postdoc / phd / ms / under / ra / visiting
+affiliation: Harbin Engineering University
+order: 2
+
+links:
+ home-page: N/A
+ orcid: N/A
+ google-scholar: N/A
+ github: N/A
+ email: guoguangyan@hrbeu.edu.cn
+ profile:
+
+display_1: B.Eng. (HEU)
+display_2: Dec 2025
+
+---
+
+
+
+
+Guangyan Guo received the B.S. degree in Automation from the College of Intelligent Systems Science and Engineering, Harbin Engineering University, in 2021. He is currently pursuing the Ph.D. degree in control science and engineering at the same university. From December 2025 to May 2026, he is a visiting graduate researcher at the Department of Aeronautical and Aviation Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong. He won the Best Student Paper Award at the 2025 Chinese Automation Congress. His current research interests include visual SLAM, visual scene reconstruction, and the computer simulation of physical fields.
+
+**Research Areas**
+visual SLAM，Visual scene reconstruction, Computer simulation
\ No newline at end of file
diff --git a/_members/LixiangShi_Tongji_visiting.md b/_members/LixiangShi_Tongji_visiting.md
index 491b88ace..e84c491a1 100644
--- a/_members/LixiangShi_Tongji_visiting.md
+++ b/_members/LixiangShi_Tongji_visiting.md
@@ -1,20 +1,20 @@
---
name: Yuxiang Shi
image: images/team/Yuxiang_SHI_tongji.jpg
-role: visiting # pi / postdoc / phd / ms / under / ra / visiting
+role: alumni # pi / postdoc / phd / ms / under / ra / visiting / alumni
affiliation: Tongji University
-order: 2
+order: 9
links:
- home-page: N/A
- orcid: N/A
- google-scholar: N/A
- github: N/A
+ home-page:
+ orcid:
+ google-scholar:
+ github:
email: 2011200@tongji.edu.cn
profile:
-display_1: Phd student (Tongji) and B.Eng. (Southwest Jiaotong University)
-display_2: To be join in fall 2025
+display_1: Ph.D. Student (Tongji), B.Eng. (SWJTU)
+display_2: Visiting (2025)
---
diff --git a/_members/Qijun.md b/_members/Qijun.md
index a2dc61acf..a6510158c 100644
--- a/_members/Qijun.md
+++ b/_members/Qijun.md
@@ -1,20 +1,16 @@
---
-name: QIN Qijun
+name: Qin Qijun
image: images/team/qijun.jpg
-role: ms # pi / postdoc / phd / ms / under / ra / visiting
+role: ms # pi / postdoc / phd / ms / under / ra / visiting
affiliation: Hong Kong Polytechnic University
order: 2
links:
github: https://github.com/QuintinUmi
email: qijun.qin@connect.polyu.hk
-
-display_1: BEng (HONS) Aviation Engineering (2021-2025)
-display_2:
- - Merit Award, Best URIS Research Project 2024
- - Attended PRSC 2024
- - Dean's Honours List, PolyU (2022-2023)
- - To join Mphil in fall 2025
+
+display_1: MPhil Student (PolyU), B.Eng. (PolyU)
+display_2: Fall 2025
---
diff --git a/_members/WANG_Zhongqi.md b/_members/WANG_Zhongqi.md
new file mode 100644
index 000000000..b469adc03
--- /dev/null
+++ b/_members/WANG_Zhongqi.md
@@ -0,0 +1,24 @@
+---
+name: WANG Zhongqi
+image: images/team/zhongqi_wang.jpg
+role: under
+affiliation: Hong Kong Polytechnic University
+order: 2
+
+links:
+ home-page:
+ github: https://github.com/zqwang1105
+ email: 20099224d@connect.polyu.hk
+ profile:
+
+display_1: B.Eng.(PolyU)
+display_2: July 2025 - Present
+---
+
+
+
+
+Mr. WANG Zhongqi is currently a final-year Undergraduate Student Assistant at Department of Mechanical Engineering, The Hong Kong Polytechnic University (PolyU).
+
+**Research Areas**
+Robotics, Reinforcement learning
diff --git a/_members/XiangruWang.md b/_members/XiangruWang.md
index 0d283eeb3..1280c4730 100644
--- a/_members/XiangruWang.md
+++ b/_members/XiangruWang.md
@@ -1,7 +1,7 @@
---
name: Wang Xiangru
image: images/team/wang_xiangru.jpg
-role: ra # pi / postdoc / phd / ms / under / ra / visiting
+role: phd # pi / postdoc / phd / ms / under / ra / visiting
affiliation: Hong Kong Polytechnic University
order: 8
@@ -11,7 +11,7 @@ links:
profile:
display_1:
- - RA, M.Sc. (TUM), B.Eng. (WHU)
+ - PhD student, M.Sc. (TUM), B.Eng. (WHU)
display_2:
- From Feb. 2025
---
diff --git a/_members/Xu_Ruijie.md b/_members/Xu_Ruijie.md
index 7d073e798..251588f31 100644
--- a/_members/Xu_Ruijie.md
+++ b/_members/Xu_Ruijie.md
@@ -13,7 +13,7 @@ links:
email: ruijie.xu@connect.polyu.hk
profile:
-display_1: B.Eng. (BUCT)
+display_1: Ph.D. Student(PolyU), B.Eng. (BUCT)
display_2: fall 2023 -- Present
---
diff --git a/_members/Yang_Mokui.md b/_members/Yang_Mokui.md
new file mode 100644
index 000000000..717b04500
--- /dev/null
+++ b/_members/Yang_Mokui.md
@@ -0,0 +1,24 @@
+---
+name: Yang Mokui
+image: images/team/yang_mokui.jpg
+role: ms
+affiliation: Hong Kong Polytechnic University
+order: 1
+
+links:
+ home-page: /
+ github: https://github.com/Guohao-Fu
+ email: mokui.yang@connect.polyu.hk
+ profile:
+
+display_1: M.Phil. Student, B.Eng.(HDU)
+display_2: May 2025 - Present
+---
+
+
+
+
+Mr. Yang Mokui is currently a MPhil Student at Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University(PolyU), supervised by Dr. Wen Weisong.
+
+**Research Areas**
+FPGA Hardware Acceleration
diff --git a/_members/ZHAO_Jiaqi.md b/_members/ZHAO_Jiaqi.md
index 2bc582e37..5de186f93 100644
--- a/_members/ZHAO_Jiaqi.md
+++ b/_members/ZHAO_Jiaqi.md
@@ -1,24 +1,24 @@
---
name: ZHAO Jiaqi
image: images/team/zhao_jiaqi.jpg
-role: under
+role: ms
affiliation: Hong Kong Polytechnic University
order: 1
links:
- home-page: www.linkedin.com/in/jiaqi-zhao-7ab009228
+ home-page: https://www.linkedin.com/in/jiaqi-zhao-7ab009228
github: https://github.com/Qiamp
email: jiaqi.zhao@connect.polyu.hk
profile:
-display_1: B.Eng.(PolyU)
+display_1: M.Phil. Student, B.Eng.(PolyU), Drone Captain with HKCAD & CAAC License
display_2: March 2024 - Present
---
-Mr. Zhao Jiaqi is currently a Year-4 Undergraduate Student Assistant at Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University(PolyU), supervised by Dr. Wen Weisong.
+Mr. Zhao Jiaqi is currently a MPhil Student at Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University(PolyU), supervised by Dr. Wen Weisong.
**Research Areas**
-UAV Vision-Based Positioning and Navigation
+UAV end2end Positioning and Navigation
diff --git a/_members/Zhang_Ziqi.md b/_members/Zhang_Ziqi.md
index ec012c84f..8c48d6761 100644
--- a/_members/Zhang_Ziqi.md
+++ b/_members/Zhang_Ziqi.md
@@ -3,7 +3,7 @@ name: Zhang Ziqi
image: images/team/Zhang_Ziqi.JPG
role: phd # pi / postdoc / phd / ms / under / ra / visiting
affiliation: Hong Kong Polytechnic University
-order: 1
+order: 3
links:
orcid: 0009-0001-1289-4932
diff --git a/_members/ZihaoWang_WHU_visiting.md b/_members/ZihaoWang_WHU_visiting.md
index c374514f9..9b741fb09 100644
--- a/_members/ZihaoWang_WHU_visiting.md
+++ b/_members/ZihaoWang_WHU_visiting.md
@@ -1,20 +1,20 @@
---
name: Zihao Wang
image: images/team/Zihao-Wang.png
-role: visiting # pi / postdoc / phd / ms / under / ra / visiting
+role: alumni # pi / postdoc / phd / ms / under / ra / visiting / alumni
affiliation: Wuhan University
-order: 1
+order: 8
links:
- home-page: N/A
+ home-page:
orcid: 0009-0000-0221-9768
- google-scholar: N/A
- github: N/A
+ google-scholar:
+ github:
email: wzihao@whu.edu.cn
profile:
display_1: M.S and B.Eng. (WHU)
-display_2: To be join in fall 2025
+display_2: Visiting (Sept - Dec 2025)
---
diff --git a/_members/gao_yixin.md b/_members/gao_yixin.md
index c982bcc77..4130fd5b5 100644
--- a/_members/gao_yixin.md
+++ b/_members/gao_yixin.md
@@ -13,7 +13,7 @@ links:
email: yixin.gao@connect.polyu.hk
display_1: PhD Student(PolyU), M.Eng.(ZJU), B.Eng. (UPC)
-display_2: Spring 2024 -- Present
+display_2: Fall 2024 -- Present
---
diff --git a/_members/hujiahao.md b/_members/hujiahao.md
index 108c3bd6b..6f8114069 100644
--- a/_members/hujiahao.md
+++ b/_members/hujiahao.md
@@ -1,7 +1,7 @@
---
name: Hu Jiahao
image: images/team/hu_jiahao.jpg
-role: ra # pi / postdoc / phd / ms / under / visiting
+role: phd # pi / postdoc / phd / ms / under / visiting
affiliation: Hong Kong Polytechnic University
order: 1
@@ -12,14 +12,14 @@ links:
email: jiahu@polyu.edu.hk
profile:
-display_1: Project Technical Assistant, M.Eng.(WHUT), B.Eng. (WHUT)
+display_1: PhD Student, M.Eng.(WHUT), B.Eng. (WHUT)
display_2:
---
-Jiahao Hu received his M.S. degree from the School of Mechanical and Electrical Engineering at Wuhan University of Technology, Wuhan, China, in 2023. He is currently a Project Technical Assistant in the Department of Aeronautical and Aviation Engineering at The Hong Kong Polytechnic University, Hong Kong. His current research interests include UAV positioning and navigation, Sensor Fusion.
+Jiahao Hu received his M.S. degree from the School of Mechanical and Electrical Engineering at Wuhan University of Technology, Wuhan, China, in 2023. He is currently a PhD student in the Department of Aeronautical and Aviation Engineering at The Hong Kong Polytechnic University, Hong Kong. His current research interests include UAV positioning and navigation, Sensor Fusion.
**Research Areas**
UAV positioning and navigation, Sensor Fusion
diff --git a/_members/jiao_jianhao.md b/_members/jiao_jianhao.md
new file mode 100644
index 000000000..3d4a303da
--- /dev/null
+++ b/_members/jiao_jianhao.md
@@ -0,0 +1,25 @@
+---
+name: Jianho Jiao
+image: images/team/jianhaojiao_pict_2023.jpg
+role: postdoc # pi / postdoc / phd / ms / under / ra / visiting
+affiliation: Hong Kong Polytechnic University
+order: 1
+
+links:
+ home-page: https://gogojjh.github.io/
+ orcid:
+ google-scholar: https://scholar.google.com/citations?user=psqleSQAAAAJ&hl=zh-TW
+ github: https://github.com/gogojjh
+ email: jiaojh1994@gmail.com
+ profile:
+
+display_1: Ph.D.(HKUST), B.Eng. (ZJU)
+---
+
+
+
+
+Jianhao Jiao (Member, IEEE) received a Ph.D. in Electronic and Computer Engineering from the Hong Kong University of Science and Technology, in 2021. His research specializes in SLAM, sensor fusion, and robust robotic navigation, exemplified by pioneering works such as M-LOAM, FusionPortable dataset, and the scalable, structure-free visual navigation system, OpenNavMap. He has authored over ten papers in premier robotics venues (e.g., IROS, ICRA, NeurIPS, IJRR, IEEE TRO) and serves as an Associate Editor for RAL, IROS 2024-2025, ICRA 2025. Dr. Jiao’s ultimate research objective is to endow autonomous systems with lifelong, cognitive spatial memory mechanisms capable of dynamic updating, directed towards applications in challenging, unstructured environments such as subterranean mines and forests.
+
+**Research Areas**
+Mobile Robot, Navigation, Embodied Intelligence
\ No newline at end of file
diff --git a/_members/liheng.md b/_members/liheng.md
new file mode 100644
index 000000000..231735da3
--- /dev/null
+++ b/_members/liheng.md
@@ -0,0 +1,30 @@
+---
+name: Li Heng
+image: images/team/LiHeng.jpg
+role: ra
+affiliation: Hong Kong Polytechnic University
+order: 9
+
+links:
+ home-page:
+ orcid:
+ google-scholar:
+ github: https://github.com/shannonlee2024
+ email: shannon-h.li@polyu.edu.hk
+ profile:
+
+display_1: Research Assistant,B.Eng. (DLPU), R&D Engineer(Unmanned Systems Field, Shenzhen ,China)
+display_2: Spring 2025 -- Present
+
+---
+
+
+
+
+Heng Li received a BEng degree in Automation(Innovation Experimental Class) from Dalian Polytechnic University(DLPU) DaLian, China, in 2017. And he was a research assistant to the Director of R&D Institute of Integrated Measurement&Control,DLPU.
+
+From 2017 to 2024, he worked as a R&D engineer at a company in the unmanned systems field for seven years. His main research areas are perception and security of unmanned systems.
+
+
+**Research Areas**
+Unmanned Systems Perception;Unmanned Systems Security
diff --git a/_members/liu_xikun.md b/_members/liu_xikun.md
index a178bd75b..8063e8c54 100644
--- a/_members/liu_xikun.md
+++ b/_members/liu_xikun.md
@@ -1,7 +1,7 @@
---
name: Liu Xikun
image: images/team/liu_xikun.png
-role: phd # pi / postdoc / phd / ms / under / ra / visiting
+role: alumni # pi / postdoc / phd / ms / under / ra / visiting / alumni
affiliation: Hong Kong Polytechnic University
order: 3
@@ -13,14 +13,14 @@ links:
email: xi-kun.liu@connect.polyu.hk
profile:
-display_1: Ph.D.candidate (PolyU), M.Sc.(KIT), B.Eng. (HUST)
+display_1: Ph.D.(PolyU), M.Sc.(KIT), B.Eng. (HUST)
display_2: MION
---
-Xikun Liu received his bachelor's degree in Mechanical Design, Manufacturing, and Automation from Huazhong University of Science and Technology, China in 2017, and master’s degree in Mechatronics and Information Technology from Karlsruhe Institute of Technology, Germany in 2021. He is currently a Ph.D. candidate in the Department of Aeronautical and Aviation Engineering, the Hong Kong Polytechnic University. His research interests include GNSS and sensor-aided GNSS positioning, SLAM, and multiple sensor fusion in autonomous driving.
+Xikun Liu received his Ph.D. degree from the Department of Aeronautical and Aviation Engineering, the Hong Kong Polytechnic University. He received his bachelor's degree in Mechanical Design, Manufacturing, and Automation from Huazhong University of Science and Technology, China in 2017, and master's degree in Mechatronics and Information Technology from Karlsruhe Institute of Technology, Germany in 2021. His research interests include GNSS and sensor-aided GNSS positioning, SLAM, and multiple sensor fusion in autonomous driving.
**Research Areas**
3D LiDAR aided GNSS Positioning; Sensor Fusion; Wireless Positioning; GNSS;
diff --git a/_members/runqiuyang.md b/_members/runqiuyang.md
index 86faa5798..ebb22138c 100644
--- a/_members/runqiuyang.md
+++ b/_members/runqiuyang.md
@@ -8,7 +8,7 @@ order: 3
links:
home-page: n/a
orcid: 0000-0001-6286-8217
- google-scholar: https://scholar.google.com/citations?user=cDycNtAAAAAJ&hl=en
+ google-scholar: cDycNtAAAAAJ&hl=en
github: n/a
email: runqiu.yang@polyu.edu.hk
profile:
diff --git a/_members/runzhi_hu.md b/_members/runzhi_hu.md
index 9a3795297..9c1d2f97b 100644
--- a/_members/runzhi_hu.md
+++ b/_members/runzhi_hu.md
@@ -1,9 +1,9 @@
---
name: Runzhi Hu
image: images/team/runzhi_hu.jpg
-role: phd # pi / postdoc / phd / ms / under / ra / visiting
+role: alumni # pi / postdoc / phd / ms / under / ra / visiting / alumni
affiliation: Hong Kong Polytechnic University
-order: 3
+order: 5
links:
home-page: https://rztest.cn/
@@ -13,14 +13,14 @@ links:
email: run-zhi.hu@connect.polyu.hk
profile:
-display_1: Ph.D. Candidate(PolyU), M.Eng.(CAU), B.Eng. (CAU)
-display_2: 2022 fall - Present
+display_1: Ph.D.(PolyU), M.Eng.(CAU), B.Eng. (CAU)
+display_2: 2022 - 2025
---
-Runzhi Hu was born in Leshan, Sichuan, China. He received his B.S and master degrees in mechanical engineering and computer science, respectively, from China Agricultural University. He now is a Ph.D candidate at the Hong Kong Polytechnic University. His research interests include HD map, multi-sensor fusion, SLAM, and GNSS positioning in urban canyons. He loves popping and locking dancing so much.
+Runzhi Hu was born in Leshan, Sichuan, China. He received his B.S and master degrees in mechanical engineering and computer science, respectively, from China Agricultural University. He received his Ph.D. degree from the Hong Kong Polytechnic University. His research interests include HD map, multi-sensor fusion, SLAM, and GNSS positioning in urban canyons.
**Research Areas**
Deep Learning, Sensor Fusion; GNSS; SLAM; HD Map
diff --git a/_members/wang_junzhe.md b/_members/wang_junzhe.md
new file mode 100644
index 000000000..4cde88c08
--- /dev/null
+++ b/_members/wang_junzhe.md
@@ -0,0 +1,17 @@
+---
+name: WANG Junzhe
+image: images/team/wang_junzhe.png
+role: ms
+affiliation: Hong Kong Polytechnic University
+order: 114
+links:
+ email: cooper.wang@connect.polyu.hk
+ profile:
+display_1: M.Phil. Student, B.Eng.(HKUST)
+display_2: Fall 2025
+---
+
+
+WANG Junzhe received a BEng degree from the Hong Kong University of Science and Technology (HKUST). He is currently pursuing his M.Phil. degree at The Hong Kong Polytechnic University (PolyU).
+**Research Areas**
+UAV, Mapping, and Localization; Sensor Fusion; GNSS
diff --git a/_members/wangyun.md b/_members/wangyun.md
index d9d4cdfc5..dc7c873d9 100644
--- a/_members/wangyun.md
+++ b/_members/wangyun.md
@@ -1,7 +1,7 @@
---
name: Wang Yun
image: images/team/wang_yun.jpg
-role: ra
+role: alumni # pi / postdoc / phd / ms / under / ra / visiting / alumni
affiliation: PolyU-Wuxi Technology and innovation Research Institute
order: 7
@@ -13,16 +13,16 @@ links:
email: yun.wang@hkpolyu-wxresearch.cn
profile:
-display_1: B.Eng.(SEUCX)
-display_2:
+display_1: B.Eng.(SEUCX)
+display_2: RA
---
-WangYun received a B.Eng degree in Automation from Southeast University Cheng Xian College(SEUCX),Nanjing,China,in,2022.After that, he worked as a electrical engineer at the Makita before joining PolyU-Wuxi Technology and innovation Research Institute.
+Wang Yun received a B.Eng degree in Automation from Southeast University Cheng Xian College (SEUCX), Nanjing, China, in 2022. After that, he worked as an electrical engineer at the Makita before joining PolyU-Wuxi Technology and innovation Research Institute.
**Research Areas**
-Autonomous Driving; UAV;GNSS
+Autonomous Driving; UAV; GNSS
diff --git a/_members/xpzhai.md b/_members/xpzhai.md
index 87a66ce18..fc0fa4127 100644
--- a/_members/xpzhai.md
+++ b/_members/xpzhai.md
@@ -13,7 +13,7 @@ links:
profile:
display_1: Ph.D.(PolyU, NPU), B.Eng.(NPU)
-display_2: To join in fall 2025
+display_2: Jan 2026
---
diff --git a/_members/yfeng.md b/_members/yfeng.md
index dd5bf8813..5b76d0239 100644
--- a/_members/yfeng.md
+++ b/_members/yfeng.md
@@ -13,7 +13,7 @@ links:
profile:
display_1: Ph.D. Student (PolyU-NKU), B.Eng. (NKU)
-display_2: To join in fall 2025
+display_2: Sept 2025
---
diff --git a/_members/yihan_zhong.md b/_members/yihan_zhong.md
index 2a9051086..aa420592f 100644
--- a/_members/yihan_zhong.md
+++ b/_members/yihan_zhong.md
@@ -1,26 +1,26 @@
---
name: Zhong Yihan
image: images/team/yihan_zhong.jpg
-role: phd # pi / postdoc / phd / ms / under / ra / visiting
+role: alumni # pi / postdoc / phd / ms / under / ra / visiting / alumni
affiliation: Hong Kong Polytechnic University
-order: 2
+order: 4
links:
home-page:
orcid: 0000-0002-1462-3642
- google-scholar: https://scholar.google.com/citations?user=c1xJ5pIAAAAJ&hl=en&oi=ao
+ google-scholar: c1xJ5pIAAAAJ&hl=en&oi=ao
github: https://github.com/Pirkaklo
email: yi-han.zhong@connect.polyu.hk
profile:
-display_1: Ph.D. Candidate(PolyU), M.Sc.(PolyU), B.Eng. (GXU), MION
-display_2: Fall 2022 -- Present
+display_1: Ph.D.(PolyU), M.Sc.(PolyU), B.Eng. (GXU), MION
+display_2: 2022 - 2025
---
-Yihan Zhong Yihan Zhong obtained his bachelor's degree in process equipment and control engineering from Guangxi University in 2020 and a Master's degree with the Department of Mechanical Engineering from The Hong Kong Polytechnic University (PolyU) in 2022. He is currently a Ph.D. student at the Department of Aeronautical and Aviation Engineering (AAE) of PolyU.
+Yihan Zhong obtained his bachelor's degree in process equipment and control engineering from Guangxi University in 2020 and a Master's degree with the Department of Mechanical Engineering from The Hong Kong Polytechnic University (PolyU) in 2022. He received his Ph.D. degree from the Department of Aeronautical and Aviation Engineering (AAE) of PolyU.
His research interests include factor graph optimization-based collaborative positioning and low-cost localization.
diff --git a/_members/yingmign_chen.md b/_members/yingmign_chen.md
index 1378099a0..3f47d56d0 100644
--- a/_members/yingmign_chen.md
+++ b/_members/yingmign_chen.md
@@ -10,11 +10,11 @@ links:
orcid:
google-scholar:
github: https://github.com/AndyPawn
- email: yingming.chen@polyu.edu.hk
+ email: yingming.chen60@connect.polyu.hk
profile:
display_1: M.Phil. Student, B.Eng. (Western University of Ontario)
-display_2: Spring 2024
+display_2: Spring 2024 -- Present
---
diff --git a/_members/yywang.md b/_members/yywang.md
index b80ca5042..1489db7a4 100644
--- a/_members/yywang.md
+++ b/_members/yywang.md
@@ -6,9 +6,9 @@ affiliation: Hong Kong Polytechnic University
order: 2
links:
- home-page: http://www.ee.cuhk.edu.hk/~yywang/
+ home-page: https://yywang.pages.dev/
orcid: 0000-0003-3293-0790
- google-scholar: https://scholar.google.com/citations?user=bRwHOgwAAAAJ&hl=zh-CN
+ google-scholar: bRwHOgwAAAAJ&hl=zh-CN
email: ying5wang@polyu.edu.hk
profile:
@@ -22,3 +22,4 @@ Yingying Wang received the B.E. degree in Electronic Engineering from Northeaste
**Research Areas**
Smart sensing; Robotics; Sensor Fusion; Inertial Measurement Unit; Wireless Sensing
+
diff --git a/_members/zhengxi.md b/_members/zhengxi.md
index af732b409..9d634c2f0 100644
--- a/_members/zhengxi.md
+++ b/_members/zhengxi.md
@@ -1,14 +1,14 @@
---
name: Zheng Xi
image: images/team/zheng_xi.png
-role: phd # pi / postdoc / phd / ms / under / ra / visiting
+role: alumni # pi / postdoc / phd / ms / under / ra / visiting / alumni
affiliation: Hong Kong Polytechnic University
order: 2
links:
home-page:
orcid: 0000-0001-8399-5127
- google-scholar: https://scholar.google.com/citations?user=cfhVuzMAAAAJ&hl=zh-CN
+ google-scholar: cfhVuzMAAAAJ&hl=zh-CN
github: https://github.com/ZHENGXi-git
email: zheng-xi.zheng@connect.polyu.hk
profile:
diff --git a/_members/zxr.md b/_members/zxr.md
index de2515a43..0081ea0a6 100644
--- a/_members/zxr.md
+++ b/_members/zxr.md
@@ -14,7 +14,7 @@ links:
profile:
display_1: Master of Philosophy, B.Eng. (BUAA)
-display_2: To join in fall 2025
+display_2: Sept 2025
---
diff --git a/_opensource/2025-11-11-HDMap.md b/_opensource/2025-11-11-HDMap.md
new file mode 100644
index 000000000..b9880bc4c
--- /dev/null
+++ b/_opensource/2025-11-11-HDMap.md
@@ -0,0 +1,37 @@
+---
+title: Semantic-Vector HD Map
+subtitle: Multi-Sensor HD Map Construction Pipeline for Autonomous Vehicles
+author: Runzhi Hu
+image: images/opensource/HDMap/garage_half.gif
+tags:
+order:
+---
+
+An open-source HD vector map (HDVM) generation pipeline for autonomous vehicles, integrating GNSS, INS, LiDAR, and camera data.
+
+**[HDMap](https://github.com/ebhrz/HDMap)** provides a complete pipeline for constructing high-definition semantic and vector maps, designed for autonomous driving in complex urban environments. Unlike traditional methods that rely on planar assumptions, our approach fuses multi-sensor data to produce accurate 3D HD maps.
+
+**Pipeline Overview:**
+1. **Semantic extraction** — Extracts semantic information from raw images using Vision Transformer (ViT) and Swin Transformer architectures
+2. **3D reconstruction** — Obtains absolute 3D coordinates of semantic objects from LiDAR depth data
+3. **Precise localization** — Uses GNSS-RTK and INS for high-precision pose estimation
+4. **Vector map generation** — Extracts vector features (e.g., lane markings) to form the HD vector map
+5. **Error analysis** — Provides an error propagation scheme analyzing segmentation and LiDAR-camera extrinsic calibration errors
+
+A **Docker version** of the pipeline is available for easy deployment.
+
+
+
+
+
+**Citation:**
+```bibtex
+@article{hu2024hdmap,
+ author={Hu, Runzhi and Bai, Shiyu and Wen, Weisong and Xia, Xin and Hsu, Li-Ta},
+ title={Towards high-definition vector map construction based on multi-sensor integration for intelligent vehicles: Systems and error quantification},
+ journal={IET Intelligent Transport Systems},
+ doi={https://doi.org/10.1049/itr2.12524}
+}
+```
+
+**GitHub:** [https://github.com/ebhrz/HDMap](https://github.com/ebhrz/HDMap)
diff --git a/_opensource/2025-11-11-kltdataset.md b/_opensource/2025-11-11-kltdataset.md
new file mode 100644
index 000000000..f1fa37031
--- /dev/null
+++ b/_opensource/2025-11-11-kltdataset.md
@@ -0,0 +1,25 @@
+---
+title: KLT Dataset
+subtitle: Urban GNSS Dataset with LOS/NLOS Labels
+author: Runzhi Hu
+image: images/opensource/kltdataset/NLOS_crop.gif
+tags:
+order:
+---
+
+An open urban GNSS dataset with LOS/NLOS satellite labels for benchmarking GNSS positioning in challenging environments.
+
+**[KLT Dataset](https://github.com/ebhrz/KLTDataset)** is a light urban scenario dataset collected for GNSS research, providing labeled satellite signal conditions to support studies in multipath mitigation, NLOS detection, and robust positioning.
+
+**Dataset Contents:**
+- **GNSS raw measurements** — Collected using a u-blox F9P receiver with pseudorange and carrier phase observations
+- **Ground truth** — High-precision reference trajectories from a SPAN-CPT system
+- **LOS/NLOS labels** — Per-satellite labels for GPS and BeiDou constellations
+- **Additional sensors** — IMU, LiDAR, and camera recordings included in the ROS bag file
+- **Quick-start scripts** — Configuration files and start scripts provided for immediate use
+
+
+
+
+
+**GitHub:** [https://github.com/ebhrz/KLTDataset](https://github.com/ebhrz/KLTDataset)
diff --git a/_opensource/2025-11-11-plvins.md b/_opensource/2025-11-11-plvins.md
new file mode 100644
index 000000000..b63f88ccd
--- /dev/null
+++ b/_opensource/2025-11-11-plvins.md
@@ -0,0 +1,35 @@
+---
+title: SafetyQuantifiable-PLVINS
+subtitle: Safety-Quantifiable Visual Localization with 3D Prior Map
+author: Xi Zheng
+image: images/opensource/zhengxi/framework2.png
+tags:
+order:
+---
+
+Safety-quantifiable line feature-based monocular visual localization with 3D prior map and integrity monitoring.
+
+**[SafetyQuantifiable-PLVINS](https://github.com/ZHENGXi-git/SafetyQuantifiable-PLVINS)** addresses drift and safety quantification challenges in visual localization by proposing a novel map-aided method that delivers both accurate pose estimates and a measurable error bound.
+
+**Key Contributions:**
+- Tightly integrates visual-inertial odometry with a prior 3D line map via geometric constraints between 2D image features and 3D map lines
+- Introduces a **GNSS-inspired integrity monitoring framework** to compute a Protection Level (PL)
+- Quantifies potential error in both position and orientation, certifying the solution's safety
+- First application of integrity monitoring to visual localization systems
+
+
+
+
+
+**Citation:**
+```bibtex
+@article{zheng2025safety,
+ title={Safety-quantifiable line feature-based monocular visual localization with 3D prior map},
+ author={Zheng, Xi and Wen, Weisong and Hsu, Li-Ta},
+ journal={IEEE Transactions on Intelligent Transportation Systems},
+ year={2025},
+ publisher={IEEE}
+}
+```
+
+**GitHub:** [https://github.com/ZHENGXi-git/SafetyQuantifiable-PLVINS](https://github.com/ZHENGXi-git/SafetyQuantifiable-PLVINS)
diff --git a/_opensource/2025-11-11-pyrtklib.md b/_opensource/2025-11-11-pyrtklib.md
new file mode 100644
index 000000000..74a9bf29f
--- /dev/null
+++ b/_opensource/2025-11-11-pyrtklib.md
@@ -0,0 +1,42 @@
+---
+title: pyrtklib
+subtitle: Python Binding for RTKLIB — The Most Popular GNSS Positioning Library
+author: Runzhi Hu
+tags:
+order:
+---
+
+A complete Python binding for RTKLIB, bringing the full power of the most widely-used GNSS positioning library to the Python ecosystem.
+
+**[pyrtklib](https://github.com/IPNL-POLYU/pyrtklib)** bridges the gap between RTKLIB's high-performance C implementation and the Python-based research workflows widely used in deep learning and data science. With pyrtklib, you can read RINEX files, process GNSS observations, and perform SPP, RTK, and PPP positioning — all from Python.
+
+**Key Features:**
+- Full Python interface to RTKLIB's core functions
+- Supports SPP, DGNSS, RTK, and PPP positioning modes
+- Seamless RINEX file reading and GNSS observation processing
+- Enables tight integration of deep learning with GNSS positioning
+- Available via PyPI for easy installation
+
+**Quick Install:**
+```bash
+pip install pyrtklib # Standard RTKLIB version
+pip install pyrtklib5 # Based on rtklibexplorer/rtklib_demo5
+```
+
+[](https://pepy.tech/projects/pyrtklib)
+
+**Citation:**
+```bibtex
+@ARTICLE{10965937,
+ author={Hu, Runzhi and Xu, Penghui and Zhong, Yihan and Wen, Weisong},
+ journal={IEEE Transactions on Intelligent Transportation Systems},
+ title={pyrtklib: An Open-Source Package for Tightly Coupled Deep Learning and GNSS Integration for Positioning in Urban Canyons},
+ year={2025},
+ volume={26},
+ number={7},
+ pages={10652-10662},
+ doi={10.1109/TITS.2025.3552691}
+}
+```
+
+**GitHub:** [https://github.com/IPNL-POLYU/pyrtklib](https://github.com/IPNL-POLYU/pyrtklib) | **Demo5 version:** [https://github.com/IPNL-POLYU/pyrtklib_demo5](https://github.com/IPNL-POLYU/pyrtklib_demo5)
diff --git a/_opensource/2025-11-11-tasgnss.md b/_opensource/2025-11-11-tasgnss.md
new file mode 100644
index 000000000..8c890e3ce
--- /dev/null
+++ b/_opensource/2025-11-11-tasgnss.md
@@ -0,0 +1,24 @@
+---
+title: TASGNSS
+subtitle: Simple and Modern Python GNSS Interface
+author: Runzhi Hu
+tags:
+order:
+---
+
+A simple and modern Python interface for GNSS positioning, built on top of pyrtklib.
+
+**[TASGNSS](https://github.com/PolyU-TASLAB/TASGNSS)** provides a clean, high-level Python API for GNSS data processing and positioning. Built on [pyrtklib](https://github.com/IPNL-POLYU/pyrtklib), it abstracts away low-level complexity and offers an intuitive interface for researchers and developers working with GNSS data.
+
+**Key Features:**
+- High-level Pythonic API for GNSS positioning (SPP, RTK, PPP)
+- Built on the well-established pyrtklib/RTKLIB engine
+- Easy-to-use data reading from RINEX and other standard formats
+- Comprehensive [documentation](https://polyu-taslab.github.io/TASGNSS/) with tutorials and examples
+
+**Quick Install:**
+```bash
+pip install tasgnss
+```
+
+**GitHub:** [https://github.com/PolyU-TASLAB/TASGNSS](https://github.com/PolyU-TASLAB/TASGNSS) | **Docs:** [https://polyu-taslab.github.io/TASGNSS/](https://polyu-taslab.github.io/TASGNSS/)
diff --git a/_opensource/2025-11-11-tc-viml.md b/_opensource/2025-11-11-tc-viml.md
new file mode 100644
index 000000000..8a1b50595
--- /dev/null
+++ b/_opensource/2025-11-11-tc-viml.md
@@ -0,0 +1,43 @@
+---
+title: TC-VIML
+subtitle: Tightly-Coupled Visual-Inertial-Map Localization for Intelligent Vehicles
+author: Xi Zheng
+image: images/opensource/zhengxi/framework.png
+tags:
+order:
+---
+
+Tightly-coupled Visual/Inertial/Map integration with observability analysis for reliable localization of intelligent vehicles.
+
+**[TC-VIML](https://github.com/ZHENGXi-git/TC-VIML)** proposes a tightly-coupled visual-inertial odometry (VIO) system that leverages a 3D prior line map for drift-free localization. Unlike loosely-coupled methods, our approach deeply integrates line features into a factor graph optimization framework, supported by a robust cross-modality matching and outlier rejection strategy.
+
+**Key Contributions:**
+- Tight integration of 2D image line features with a 3D prior line map via factor graph optimization
+- Robust cross-modality matching and outlier rejection for line feature association
+- First rigorous proof that the system achieves **full observability in global translation** (only yaw unobservable)
+- Validated in both simulated and real-world urban driving environments
+
+
+
+
+
+**Citation:**
+```bibtex
+@article{zheng2024tightly,
+ title={Tightly-coupled visual/inertial/map integration with observability analysis for reliable localization of intelligent vehicles},
+ author={Zheng, Xi and Wen, Weisong and Hsu, Li-Ta},
+ journal={IEEE Transactions on Intelligent Vehicles},
+ year={2024},
+ publisher={IEEE}
+}
+
+@inproceedings{zheng2023tightly,
+ title={Tightly-coupled line feature-aided visual inertial localization within lightweight 3D prior map for intelligent vehicles},
+ author={Zheng, Xi and Wen, Weisong and Hsu, Li-Ta},
+ booktitle={IEEE ITSC},
+ pages={6019--6026},
+ year={2023}
+}
+```
+
+**GitHub:** [https://github.com/ZHENGXi-git/TC-VIML](https://github.com/ZHENGXi-git/TC-VIML)
diff --git a/_opensource/2025-11-11-tdl-gnss.md b/_opensource/2025-11-11-tdl-gnss.md
new file mode 100644
index 000000000..2814a59ea
--- /dev/null
+++ b/_opensource/2025-11-11-tdl-gnss.md
@@ -0,0 +1,38 @@
+---
+title: TDL-GNSS
+subtitle: Tightly Coupled Deep Learning Framework for GNSS Positioning
+author: Runzhi Hu
+image: images/papers/2024/runzhi2024pyrtklib.png
+tags:
+order:
+---
+
+A tightly coupled deep learning framework for GNSS positioning in challenging urban environments.
+
+**[TDL-GNSS](https://github.com/ebhrz/TDL-GNSS)** is built on top of [pyrtklib](https://github.com/IPNL-POLYU/pyrtklib) and [TASGNSS](https://github.com/PolyU-TASLAB/TASGNSS), designed to seamlessly integrate deep learning models into the GNSS processing workflow. The framework enables researchers to leverage neural networks for tasks such as satellite signal quality assessment, weight optimization, and positioning error mitigation — all within a unified Python pipeline.
+
+**Key Features:**
+- Tightly integrates deep learning with conventional GNSS processing (SPP, RTK, PPP)
+- Built on the established pyrtklib and TASGNSS ecosystem
+- End-to-end trainable pipeline for GNSS positioning
+- Designed for urban canyon scenarios with severe multipath and NLOS effects
+
+
+
+
+
+**Citation:**
+```bibtex
+@ARTICLE{10965937,
+ author={Hu, Runzhi and Xu, Penghui and Zhong, Yihan and Wen, Weisong},
+ journal={IEEE Transactions on Intelligent Transportation Systems},
+ title={pyrtklib: An Open-Source Package for Tightly Coupled Deep Learning and GNSS Integration for Positioning in Urban Canyons},
+ year={2025},
+ volume={26},
+ number={7},
+ pages={10652-10662},
+ doi={10.1109/TITS.2025.3552691}
+}
+```
+
+**GitHub:** [https://github.com/ebhrz/TDL-GNSS](https://github.com/ebhrz/TDL-GNSS)
diff --git a/_opensource/2026-01-17-TasFusion.md b/_opensource/2026-01-17-TasFusion.md
new file mode 100644
index 000000000..6e0b78b22
--- /dev/null
+++ b/_opensource/2026-01-17-TasFusion.md
@@ -0,0 +1,39 @@
+---
+title: TasFusion
+subtitle: ROS1 Package for Multi-Sensor GNSS/IMU Fusion Navigation
+author: ZHAO Jiaqi
+image: images/opensource/TasFusion/demo.gif
+tags:
+order:
+---
+
+A ROS1 package for Ceres-based GNSS/IMU loosely coupled sliding-window optimization, designed for robust multi-sensor navigation.
+
+**[TasFusion](https://github.com/PolyU-TASLAB/TasFusion)** provides a complete multi-sensor navigation framework with the following features:
+
+- **Ceres-based optimization** — Sliding-window GNSS/IMU loosely coupled fusion with IMU pre-integration and online bias estimation
+- **Marginalization** — Preserves historical information for consistent state estimation
+- **GPS constraints** — Supports both position and velocity constraints from GNSS
+- **NLOS exclusion** — Built-in utilities to reject non-line-of-sight satellite signals
+- **Flexible configuration** — All major functions can be enabled/disabled via launch file parameters
+- **Supporting tools** — Includes GNSS message definitions, a NovAtel driver, and NMEA ROS parsing scripts
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+> **Reference Hardware Platform** ([Introduction Video](https://www.bilibili.com/video/BV1fiaqzNEEm)):
+> TasFusion has been validated on a GNSS-IMU-4G integrated navigation module (dual-IMU + u-blox F9P-04B + 4G uplink), providing high-frequency measurements and reliable telemetry for outdoor deployments.
+> For hardware inquiries, please contact **hbwu@hkpolyu-wxresearch.cn**.
+
+**GitHub:** [https://github.com/PolyU-TASLAB/TasFusion](https://github.com/PolyU-TASLAB/TasFusion)
diff --git a/_posts/2021-09-07-Huawei_PolyU_High-accuracy_Localization_Project.md b/_posts/2021-09-07-Huawei_PolyU_High-accuracy_Localization_Project.md
index 89d1202e7..605e9176f 100644
--- a/_posts/2021-09-07-Huawei_PolyU_High-accuracy_Localization_Project.md
+++ b/_posts/2021-09-07-Huawei_PolyU_High-accuracy_Localization_Project.md
@@ -4,6 +4,7 @@ subtitle: Knowledge Transfer to Unmanned Autonomous Systems
# author: XNG
image: images/project/huawei_mapping.gif
tags: Localization, mapping, sensor-fusion, RTK, GNSS, LiDAR, IMU, Virtual-satellites, Cycle-slip-detection
+research_direction: gnss
order:
---
diff --git a/_posts/2022-02-14-Research_on_GNSS_Urban_Positioning_Algorithm_Based_on_3D_LiDAR.md b/_posts/2022-02-14-Research_on_GNSS_Urban_Positioning_Algorithm_Based_on_3D_LiDAR.md
index 9504d66a8..9cfd34c50 100644
--- a/_posts/2022-02-14-Research_on_GNSS_Urban_Positioning_Algorithm_Based_on_3D_LiDAR.md
+++ b/_posts/2022-02-14-Research_on_GNSS_Urban_Positioning_Algorithm_Based_on_3D_LiDAR.md
@@ -4,6 +4,7 @@ subtitle: Knowledge Transfer to Unmanned Autonomous Systems
# author: XNG
image: images/project/GDSTC/fgo.png
tags: Localization, mapping, sensor-fusion, RTK, GNSS, LiDAR, IMU
+research_direction: gnss
order:
---
## Abstract
diff --git a/_posts/2023-01-01-Safety-certifiable_UAV_System_for_Terrian_and_Civil_Infrastructure_Inspection.md b/_posts/2023-01-01-Safety-certifiable_UAV_System_for_Terrian_and_Civil_Infrastructure_Inspection.md
index 4b13c0beb..a82571c0b 100644
--- a/_posts/2023-01-01-Safety-certifiable_UAV_System_for_Terrian_and_Civil_Infrastructure_Inspection.md
+++ b/_posts/2023-01-01-Safety-certifiable_UAV_System_for_Terrian_and_Civil_Infrastructure_Inspection.md
@@ -4,6 +4,7 @@ subtitle: Knowledge Transfer to Unmanned Autonomous Systems
# author: XNG
image:
tags: Localization, UAV
+research_direction: drones
order:
---
diff --git a/_posts/2023-04-01-Vision_Aided_GNSS-RTK_Positioning_for_UAV_System_in_Urban_Canyons.md b/_posts/2023-04-01-Vision_Aided_GNSS-RTK_Positioning_for_UAV_System_in_Urban_Canyons.md
index fd3b1e36b..6eb6d7f36 100644
--- a/_posts/2023-04-01-Vision_Aided_GNSS-RTK_Positioning_for_UAV_System_in_Urban_Canyons.md
+++ b/_posts/2023-04-01-Vision_Aided_GNSS-RTK_Positioning_for_UAV_System_in_Urban_Canyons.md
@@ -4,6 +4,7 @@ subtitle: Fisheye Camera Aided GNSS NLOS Detection and Learning-based Pseudorang
# author: XNG
image: images/project/Vision_aided_GNSS_RTK/framework.png
tags: Artificial intelligence, Deep learning, GNSS
+research_direction: gnss
order:
---
## Abstract
diff --git a/_posts/2023-05-08-Unmanned_Aerial_Vehicle_Aided_High_Accuracy_Addictive_Manufacturing_for_Carbon_Fiber_Reinforced_Thermoplastic_Composites_Material.md b/_posts/2023-05-08-Unmanned_Aerial_Vehicle_Aided_High_Accuracy_Addictive_Manufacturing_for_Carbon_Fiber_Reinforced_Thermoplastic_Composites_Material.md
index 9e854ff30..19ff47f3b 100644
--- a/_posts/2023-05-08-Unmanned_Aerial_Vehicle_Aided_High_Accuracy_Addictive_Manufacturing_for_Carbon_Fiber_Reinforced_Thermoplastic_Composites_Material.md
+++ b/_posts/2023-05-08-Unmanned_Aerial_Vehicle_Aided_High_Accuracy_Addictive_Manufacturing_for_Carbon_Fiber_Reinforced_Thermoplastic_Composites_Material.md
@@ -4,6 +4,7 @@ subtitle: Knowledge Transfer to Unmanned Autonomous Systems
# author: XNG
image:
tags: UAV, Manufacturing
+research_direction: drones
order:
---
diff --git a/_posts/2023-09-30-Research_on_high-precision_vehicle-mounted_GNSS-IMU-Camera_fusion_positioning_technology_in_complex_urban_environments_based_on_factor_graph.md b/_posts/2023-09-30-Research_on_high-precision_vehicle-mounted_GNSS-IMU-Camera_fusion_positioning_technology_in_complex_urban_environments_based_on_factor_graph.md
index b89fec63b..064037caf 100644
--- a/_posts/2023-09-30-Research_on_high-precision_vehicle-mounted_GNSS-IMU-Camera_fusion_positioning_technology_in_complex_urban_environments_based_on_factor_graph.md
+++ b/_posts/2023-09-30-Research_on_high-precision_vehicle-mounted_GNSS-IMU-Camera_fusion_positioning_technology_in_complex_urban_environments_based_on_factor_graph.md
@@ -5,6 +5,7 @@ subtitle: A Factor Graph Optimization-Based Multiple‑epoch Ambiguity Resolutio
# author: XNG
image: images/project/Vision_aided_GNSS_RTK/framework.png
tags: Global navigation satellite system, Real-time kinematic positioning, Factor graph optimization, Multi‑epoch ambiguity resolution, Urban canyons
+research_direction: gnss
order:
---
## Abstract
diff --git a/_posts/2023-10-15-Vehicle-infrastructure_Collaboration_for_Connected_Unmanned_Ground_and_Aerial_Vehicles_in_Complex_Urban_Canyons.md b/_posts/2023-10-15-Vehicle-infrastructure_Collaboration_for_Connected_Unmanned_Ground_and_Aerial_Vehicles_in_Complex_Urban_Canyons.md
index 9d27d2879..a8b23d6ee 100644
--- a/_posts/2023-10-15-Vehicle-infrastructure_Collaboration_for_Connected_Unmanned_Ground_and_Aerial_Vehicles_in_Complex_Urban_Canyons.md
+++ b/_posts/2023-10-15-Vehicle-infrastructure_Collaboration_for_Connected_Unmanned_Ground_and_Aerial_Vehicles_in_Complex_Urban_Canyons.md
@@ -4,6 +4,7 @@ subtitle: Knowledge Transfer to Unmanned Autonomous Systems
# author: XNG
image:
tags: Unmanned Ground Vehicle, Unmanned Aerial Vehicle, Cooperation, urban canyons
+research_direction: vehicles
order:
---
diff --git a/_posts/2023-12-03-Multi_robot_Collaborative_Operations_in_Lunar_Areas_for_Regolith_Processing_Project.md b/_posts/2023-12-03-Multi_robot_Collaborative_Operations_in_Lunar_Areas_for_Regolith_Processing_Project.md
index 7cd45ffc0..4624568cf 100644
--- a/_posts/2023-12-03-Multi_robot_Collaborative_Operations_in_Lunar_Areas_for_Regolith_Processing_Project.md
+++ b/_posts/2023-12-03-Multi_robot_Collaborative_Operations_in_Lunar_Areas_for_Regolith_Processing_Project.md
@@ -3,7 +3,8 @@ title: Multi-robot Collaborative Operations in Lunar Areas for Regolith Processi
subtitle: High Accuracy Positioning with Multi-sensory Integration for Robotics in Complex Scenarios
# author: CYM
image: images/project/prototype.png
-tags: Multi-robot-collaboration, MPC, mapping, Leader-Follower-Formation-Algorithm, sensor-fusion, LiDAR, IMU
+tags: Multi-robot-collaboration, MPC, mapping, Leader-Follower-Formation-Algorithm, sensor-fusion, LiDAR, IMU
+research_direction: humanoid
order:
---
## Abstract
diff --git a/_posts/2024-01-01-Data-driven-assisted_GNSS_RTK-INS_Navigation_for_Autonomous_Systems_in_Urban_Canyons.md b/_posts/2024-01-01-Data-driven-assisted_GNSS_RTK-INS_Navigation_for_Autonomous_Systems_in_Urban_Canyons.md
index e9c10698e..b94486d29 100644
--- a/_posts/2024-01-01-Data-driven-assisted_GNSS_RTK-INS_Navigation_for_Autonomous_Systems_in_Urban_Canyons.md
+++ b/_posts/2024-01-01-Data-driven-assisted_GNSS_RTK-INS_Navigation_for_Autonomous_Systems_in_Urban_Canyons.md
@@ -4,6 +4,7 @@ subtitle: AI-aided Navigation
# author: XNG
image: images/project/Data_driven_structure.png
tags: GNSS Positioning, NLOS/Multipath Correction, Autonomous Driving, Positional Encoding, Multimodal Network, Vision Feature
+research_direction: gnss
order:
---
## Abstract
diff --git a/_posts/2024-01-01-Maximum_Consensus_Integration_of_GNSS_and_LiDAR_for_Urban_Navigation.md b/_posts/2024-01-01-Maximum_Consensus_Integration_of_GNSS_and_LiDAR_for_Urban_Navigation.md
index 565be9381..6d43fbd1c 100644
--- a/_posts/2024-01-01-Maximum_Consensus_Integration_of_GNSS_and_LiDAR_for_Urban_Navigation.md
+++ b/_posts/2024-01-01-Maximum_Consensus_Integration_of_GNSS_and_LiDAR_for_Urban_Navigation.md
@@ -3,7 +3,8 @@ title: Maximum Consensus Integration of GNSS and LiDAR for Urban Navigation
subtitle: Knowledge Transfer to Unmanned Autonomous Systems
# author: XNG
image:
-tags: GNSS, LIDAR, Sensor fusion
+tags: GNSS, LIDAR, Sensor fusion
+research_direction: gnss
order:
---
diff --git a/_posts/2024-04-01-Sustainable_Window_Cleaning_for_PolyU_Jockey_Club_Innovation_Tower_with_Unmanned_Aerial_Vehicles (UAV)_An_Application_of_Autonomous_Systems_Enabled_Carbon_Reduction.md b/_posts/2024-04-01-Sustainable_Window_Cleaning_for_PolyU_Jockey_Club_Innovation_Tower_with_Unmanned_Aerial_Vehicles (UAV)_An_Application_of_Autonomous_Systems_Enabled_Carbon_Reduction.md
index 27a70cafd..172407eff 100644
--- a/_posts/2024-04-01-Sustainable_Window_Cleaning_for_PolyU_Jockey_Club_Innovation_Tower_with_Unmanned_Aerial_Vehicles (UAV)_An_Application_of_Autonomous_Systems_Enabled_Carbon_Reduction.md
+++ b/_posts/2024-04-01-Sustainable_Window_Cleaning_for_PolyU_Jockey_Club_Innovation_Tower_with_Unmanned_Aerial_Vehicles (UAV)_An_Application_of_Autonomous_Systems_Enabled_Carbon_Reduction.md
@@ -3,7 +3,8 @@ title: Sustainable Window Cleaning for PolyU Jockey Club Innovation Tower with U
subtitle: Knowledge Transfer to Unmanned Autonomous Systems
# author: XNG
image: images/project/uav_clean.png
-tags: Unmanned Aerial Vehicle
+tags: Unmanned Aerial Vehicle
+research_direction: drones
order:
---
diff --git a/_posts/2024-04-08-Development_of_an_Assisted_Navigation_and_Collision_Avoidance_System_using_AI_and_Location-based_Service.md b/_posts/2024-04-08-Development_of_an_Assisted_Navigation_and_Collision_Avoidance_System_using_AI_and_Location-based_Service.md
index b9e13b19c..ed5bd9820 100644
--- a/_posts/2024-04-08-Development_of_an_Assisted_Navigation_and_Collision_Avoidance_System_using_AI_and_Location-based_Service.md
+++ b/_posts/2024-04-08-Development_of_an_Assisted_Navigation_and_Collision_Avoidance_System_using_AI_and_Location-based_Service.md
@@ -4,6 +4,7 @@ subtitle: Knowledge Transfer to Unmanned Autonomous Systems
# author: XNG
image: images/project/stf/demo_gif.gif
tags: Positioning Services, Multi-Vehicle Collaborative Sensing, AI aided GNSS, GNSS Signal Tracing, Sensor Integration
+research_direction: fusion
order:
---
## Abstract
diff --git a/_posts/2024-04-08-Safe-assured_Learning-based_Deep_SE(3)_Motion_Joint_Planning_and_Control_for_Unmanned_Aerial_Vehicles.md b/_posts/2024-04-08-Safe-assured_Learning-based_Deep_SE(3)_Motion_Joint_Planning_and_Control_for_Unmanned_Aerial_Vehicles.md
index 17a861579..997a9a10c 100644
--- a/_posts/2024-04-08-Safe-assured_Learning-based_Deep_SE(3)_Motion_Joint_Planning_and_Control_for_Unmanned_Aerial_Vehicles.md
+++ b/_posts/2024-04-08-Safe-assured_Learning-based_Deep_SE(3)_Motion_Joint_Planning_and_Control_for_Unmanned_Aerial_Vehicles.md
@@ -3,7 +3,8 @@ title: Safe-assured Learning-based Deep SE(3) Motion Joint Planning and Control
subtitle: Knowledge Transfer to Unmanned Autonomous Systems
# author: XNG
image:
-tags: Advanced Vehicle Safety Systems, Automated Vehicle Operation, Motion Planning, Navigation, Aerial, Marine and Surface Intelligent Vehicles
+tags: Advanced Vehicle Safety Systems, Automated Vehicle Operation, Motion Planning, Navigation, Aerial, Marine and Surface Intelligent Vehicles
+research_direction: drones
order:
---
diff --git a/_posts/2024-10-14-AI_assisted_inertial_navigation_system.md b/_posts/2024-10-14-AI_assisted_inertial_navigation_system.md
index 7505c715d..fcdeaba56 100644
--- a/_posts/2024-10-14-AI_assisted_inertial_navigation_system.md
+++ b/_posts/2024-10-14-AI_assisted_inertial_navigation_system.md
@@ -3,7 +3,8 @@ title: AI assisted inertial navigation system
subtitle: Knowledge Transfer to Unmanned Autonomous Systems
# author: XNG
image: images/project/Honor.png
-tags: Inertial Navigation System, AI
+tags: Inertial Navigation System, AI
+research_direction: fusion
order:
---
diff --git a/_posts/2024-12-09-Reliable_UAV_Perception_and_Perching_Solutions_in_Urban_Streets.md b/_posts/2024-12-09-Reliable_UAV_Perception_and_Perching_Solutions_in_Urban_Streets.md
index 81d42a320..50d819a14 100644
--- a/_posts/2024-12-09-Reliable_UAV_Perception_and_Perching_Solutions_in_Urban_Streets.md
+++ b/_posts/2024-12-09-Reliable_UAV_Perception_and_Perching_Solutions_in_Urban_Streets.md
@@ -4,6 +4,7 @@ subtitle: Smart Street light Poles with UAV Airports
# author: ZHAO Jiaqi
image: images/project/UAV_Perching/Smart_Street_light_Poles_with_UAV_Airports.png
tags: Landing, UAV Perching, UAV Airport
+research_direction: drones
order:
---
Develop a comprehensive UAV perception and Perching solution, focusing on the integration of smart streetlight poles with a UAV takeoff, landing, and battery exchange platform
diff --git a/_posts/2025-01-01-Our_Autonomous_Platforms.md b/_posts/2025-01-01-Our_Autonomous_Platforms.md
index 9a893b8b3..d8ad4b631 100644
--- a/_posts/2025-01-01-Our_Autonomous_Platforms.md
+++ b/_posts/2025-01-01-Our_Autonomous_Platforms.md
@@ -1,63 +1,146 @@
---
title: Our Autonomous Platforms
-# subtitle: Knowledge Transfer to Unmanned Autonomous Systems
+# subtitle: End-to-End AI-Powered Self-Driving Systems
# author: Zhang Ziqi
image: images/project/Vehicle/ADV.png
tags: Autonomous-Driving
+research_direction: vehicles
order:
---
-Demonstration of our Autonomous Driving Vehicles and their onboard sensor platforms.
+
+Our cutting-edge research platforms for end-to-end AI self-driving, where neural networks learn to drive directly from sensor data to control outputs.
+
+## What is End-to-End AI Self-Driving?
+
+End-to-end AI self-driving represents a paradigm shift in autonomous vehicle technology. Unlike traditional modular pipelines that break down driving into separate perception, prediction, planning, and control modules, end-to-end approaches use deep neural networks to learn the entire driving task holistically—directly mapping raw sensor inputs to vehicle control commands.
+
+This revolutionary approach offers several key advantages:
+
+**Direct Sensor-to-Control Learning**: Neural networks process multi-modal sensor data (cameras, LiDAR, GNSS) and output steering angles, throttle, and brake commands in a single forward pass, eliminating the error propagation inherent in modular systems.
+
+**Learned Representations**: Rather than hand-crafting features and rules, the network automatically discovers optimal internal representations of the driving environment, capturing subtle patterns that human engineers might miss.
+
+**Data-Driven Adaptation**: End-to-end models continuously improve through exposure to diverse driving scenarios, learning complex behaviors like defensive driving, traffic flow prediction, and context-aware decision-making from demonstration data.
+
+**Unified Optimization**: The entire driving pipeline is optimized jointly using gradient-based learning, ensuring that perception and control work synergistically rather than as isolated components.
+
+Our research explores multiple end-to-end architectures—from imitation learning systems that mimic expert drivers to reinforcement learning agents that discover optimal policies through trial and error in simulation, then transfer to real-world deployment.
## Introduction
-An autonomous car, also known as a self-driving vehicle, is a sophisticated mode of transportation that can perceive its environment and navigate without human intervention. These vehicles employ a variety of advanced technologies to achieve safe and efficient driving, making them a significant innovation in modern transportation.
+Autonomous vehicles represent the future of intelligent transportation, leveraging end-to-end AI architectures to transform raw sensor data into safe, human-like driving decisions. Our laboratory develops and deploys advanced self-driving systems that embody the latest breakthroughs in deep learning, computer vision, and robotics.
+
+At the core of our autonomous platforms is an integrated AI pipeline that processes multi-modal sensor streams—LiDAR point clouds, camera images, and GNSS/INS data—through sophisticated neural network architectures. These systems learn to simultaneously perceive the environment, predict future trajectories, and execute driving maneuvers in real-time, handling complex urban scenarios with human-level performance.
+
+The autonomous driving vehicle operates under comprehensive CANBUS control integrated with ROS2 middleware. Our AI control stack communicates seamlessly with the vehicle's MCU, translating high-level neural network outputs into low-level CAN signals for precise actuation. This architecture enables full drive-by-wire control including:
+
+- **Longitudinal control**: Acceleration and braking commands derived from learned policies
+- **Lateral control**: Steering angles predicted by end-to-end neural networks
+- **Mode management**: Automated gear shifting (D/P/R/N) based on mission planning
+- **Safety systems**: AI-monitored lighting, indicators, and fail-safe mechanisms
+
+This platform serves as our testbed for advancing AI-powered autonomous driving, from imitation learning and reinforcement learning to vision-language models for natural language navigation.
+
+## End-to-End AI Architecture Components
+
+Our autonomous driving system implements a comprehensive end-to-end AI architecture comprising the following key components:
+
+### 1. Multi-Modal Perception Network
+**Function**: Fuses data from cameras, LiDAR, and GNSS/INS into unified spatial-temporal representations
+
+**Architecture**: Vision backbone (ResNet, EfficientNet, or Vision Transformers) for image feature extraction; PointNet++/VoxelNet for 3D point cloud processing; Multi-scale feature pyramid networks for detecting objects at various distances; Temporal fusion modules (ConvLSTM, 3D CNNs) for motion prediction
+
+**Outputs**: Bird's-eye-view (BEV) semantic maps, 3D object detections, drivable area segmentation, lane boundary predictions
+
+### 2. World Model & Prediction
+**Function**: Learns predictive models of how the environment evolves over time
+
+**Architecture**: Recurrent neural networks (GRU/LSTM) or Transformers for sequential prediction; Probabilistic trajectory forecasting for surrounding vehicles and pedestrians; Occupancy grid prediction for future scene states; Attention mechanisms for modeling agent-agent interactions
+
+**Outputs**: Multi-modal future trajectory distributions, predicted collision risks, uncertainty estimates
-A critical aspect of autonomous vehicles is their ability to sense and localize themselves within their surroundings. This capability is essential for navigating complex environments, avoiding obstacles, and making real-time driving decisions. Accurate sensing and localization allow autonomous cars to interpret data from their surroundings and respond appropriately to dynamic conditions.
+### 3. Planning & Decision-Making Network
+**Function**: Generates safe, comfortable, and efficient driving trajectories
-The autonomous driving vehicle operates under the comprehensive control of a CANBUS system. The host computer establishes a connection with the MCU, which is equipped with integrated ROS messaging capabilities. This integration allows the system to convert ROS messages into CAN signals, which are then transmitted to the MCU.
+**Architecture**: Hierarchical planning with high-level route planning and low-level trajectory optimization; Imitation learning from expert demonstrations (Behavioral Cloning, GAIL, DAgger); Reinforcement learning for reward-driven policy optimization (PPO, SAC, TD3); Cost volume networks for evaluating trajectory candidates; Attention-based reasoning for traffic rule compliance
+
+**Outputs**: Reference trajectories (waypoints with velocity profiles), discrete actions (lane changes, stops)
+
+### 4. Control Network
+**Function**: Executes planned trajectories through precise vehicle control
+
+**Architecture**: PID controllers enhanced with learned gain scheduling; Model Predictive Control (MPC) with learned dynamics models; Direct end-to-end control networks (steering/throttle/brake prediction); Residual learning to compensate for model uncertainties
+
+**Outputs**: Low-level commands (steering angle, throttle percentage, brake pressure)
+
+### 5. Safety & Verification Layer
+**Function**: Ensures AI decisions meet safety constraints and override when necessary
+
+**Components**: Learned safety filters using reachability analysis; Rule-based fallback systems for edge cases; Uncertainty-aware decision-making (epistemic and aleatoric uncertainty); Real-time monitoring and anomaly detection; Redundant sensor validation and fault diagnosis
+
+**Outputs**: Safety scores, intervention flags, fail-safe commands
+
+### 6. Continuous Learning Pipeline
+**Function**: Enables the system to improve from real-world deployment data
+
+**Components**: On-vehicle data logging (sensor streams, AI decisions, interventions); Offline reinforcement learning from logged experience; Active learning for identifying informative scenarios; Sim-to-real transfer learning using domain adaptation; Federated learning across vehicle fleet
+
+**Outputs**: Updated model weights, identified edge cases, performance metrics
-This architecture provides us with extensive access to the vehicle's functionalities. We can not only relay vital velocity information but also manage gear settings, including Drive (D), Park (P), Reverse (R), and Neutral (N). Additionally, the system enables control of various lighting functions, enhancing both safety and operational efficiency. Overall, this setup ensures seamless communication between components, facilitating precise control and monitoring of the vehicle’s performance.
## Sensor Platform
-Currently, our lab has two autonomous vehicles deployed on the PolyU Main Campus and the PolyU-Wuxi Research Institute. Both vehicles are equipped with unique sensors, including LiDAR, cameras, and integrated GNSS/INS, for localization and navigation.
+Our laboratory operates two autonomous vehicle testbeds—one at PolyU Main Campus and another at PolyU-Wuxi Research Institute—both equipped with production-grade sensor suites for multi-modal AI training and validation.
+
+The sensor configuration enables comprehensive environmental perception:
-Here is the sensor suite:
+| Sensor Type | Brand/Model | Specifications | AI Application |
+|-------------|-------------|----------------|----------------|
+| **LiDAR** | Robosense RS-LiDAR-32 | 32 channels, 200m range, 360° FOV, 30° vertical FOV, 10-20Hz | 3D point cloud processing for obstacle detection, semantic segmentation, and occupancy prediction |
+| **Cameras** | HikRobot Event Camera | 1280×720 resolution, 120dB HDR, 60fps, global shutter | Vision-based perception, lane detection, traffic sign recognition, end-to-end driving policy learning |
+| **GNSS/INS**| CHCNav GNSS/INS | Dual-frequency RTK, integrated IMU, cm-level accuracy | Ground-truth localization for supervised learning, map-based planning, sensor fusion validation |
-| Sensor Type | Brand/Model | Parameters |
-|-------------|-------------|------------|
-| **LiDAR** | Robosense RS-LiDAR-32 | 32 laser channels, 200m range, 360° horizontal FOV, 30° vertical FOV, 10Hz-20Hz scanning frequency |
-| **Cameras** | HikRobot Event camera | 1280x720 resolution, 120dB dynamic range, 60fps frame rate, global shutter |
-| **GNSS/INS**| CHCNav GNSS/INS | Dual-frequency GNSS receiver, integrated IMU, centimeter-level accuracy, real-time kinematic (RTK) support |
+This sensor fusion architecture provides redundant, complementary data streams that feed our end-to-end AI models, enabling robust perception under diverse weather and lighting conditions.
+## AI-Driven Autonomous Driving Demonstrations
-## ADV Demo Video
+### Real-World Testing: Campus Deployment
-### Testing
-
ADV in PolyU Campus
+
End-to-End AI Navigation — PolyU Campus
-
-
ADV in PolyU-Wuxi Research Institute
+
+
Autonomous Operation — PolyU-Wuxi Research Institute
+### AI Training Pipeline: CARLA Simulation
-
-### Carla Simulation Video
+Our AI models are pre-trained and validated in high-fidelity simulation environments before real-world deployment. Using CARLA simulator, we generate diverse driving scenarios for imitation learning, reinforcement learning, and domain adaptation research.
-
-
Carla Simulation
+
CARLA Simulation Environment — End-to-End AI Policy Learning
+
+
+
+## Research Team
+
+**Principal Investigator:**
+[Dr. Wen Weisong](https://polyu-taslab.github.io/members/Wen_Weisong.html) — Assistant Professor, Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University
-### Researcher
+**Core Researchers:**
+[Mr. Zhang Ziqi](https://polyu-taslab.github.io/members/Zhang_Ziqi.html) — PhD Student, End-to-End Learning & Sensor Fusion
+[Dr. Huang Feng](https://polyu-taslab.github.io/members/Huang_Feng.html) — Postdoctoral Researcher, Navigation & Localization
+
+---
-[Dr. Weisong Wen](https://polyu-taslab.github.io/members/Wen_Weisong.html), [Mr. Zhang Ziqi](https://polyu-taslab.github.io/members/Zhang_Ziqi.html), [Mr. Huang Feng](https://polyu-taslab.github.io/members/Huang_Feng.html)
+**Research Focus:** End-to-End Deep Learning, Vision-Language Navigation, Multi-Modal Sensor Fusion, Sim-to-Real Transfer, Safe Reinforcement Learning, Imitation Learning, World Models for Autonomous Driving
\ No newline at end of file
diff --git a/_posts/2025-02-16-Safety-certified_Multi-source_Fusion_Positioning_for_Autonomous_Vehicles_in_Complex_Scenarios.md b/_posts/2025-02-16-Safety-certified_Multi-source_Fusion_Positioning_for_Autonomous_Vehicles_in_Complex_Scenarios.md
index 4ff1b8a92..0c21e1710 100644
--- a/_posts/2025-02-16-Safety-certified_Multi-source_Fusion_Positioning_for_Autonomous_Vehicles_in_Complex_Scenarios.md
+++ b/_posts/2025-02-16-Safety-certified_Multi-source_Fusion_Positioning_for_Autonomous_Vehicles_in_Complex_Scenarios.md
@@ -3,7 +3,8 @@ title: Safety-certified Multi-source Fusion Positioning for Autonomous Vehicles
subtitle: Knowledge Transfer to Unmanned Autonomous Systems
# author: XNG
image:
-tags: Localization, Sensor fusion, Safety, Autonomous Vehicle
+tags: Localization, Sensor fusion, Safety, Autonomous Vehicle
+research_direction: fusion
order:
---
diff --git a/_sass/custom.scss b/_sass/custom.scss
new file mode 100644
index 000000000..c8f75f412
--- /dev/null
+++ b/_sass/custom.scss
@@ -0,0 +1,179 @@
+---
+title: Projects
+nav:
+ order: 3
+ tooltip:
+---
+
+# {% include icon.html icon="fa-solid fa-wrench" %}Projects
+
+
+
Our Projects
+
Explore our latest projects and initiatives.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+{% include section.html %}
+
+{% include search-box.html %}
+
+{% include tags.html tags=site.tags %}
+
+{% include search-info.html %}
+
+{% include list.html data="posts" component="post-excerpt" %}
+
+
+
+
\ No newline at end of file
diff --git a/_styles/-theme.scss b/_styles/-theme.scss
index 0caecc619..f83d93a6b 100644
--- a/_styles/-theme.scss
+++ b/_styles/-theme.scss
@@ -27,25 +27,25 @@
:root {
// font families
- --title: "Barlow", sans-serif;
- --heading: "Barlow", sans-serif;
- --body: "Barlow", sans-serif;
+ --title: "Barlow", Arial, sans-serif;
+ --heading: "Barlow", Arial, sans-serif;
+ --body: "Barlow", Arial, sans-serif;
--code: "Roboto Mono", monospace;
// font sizes
- --large: 1.2rem;
- --xl: 1.4rem;
- --xxl: 1.6rem;
+ --large: 1.15rem;
+ --xl: 1.3rem;
+ --xxl: 1.5rem;
// font weights
--thin: 200;
--regular: 400;
- --semi-bold: 500;
- --bold: 600;
+ --semi-bold: 600;
+ --bold: 700;
// text line spacing
- --spacing: 2;
- --compact: 1.5;
+ --spacing: 1.55;
+ --compact: 1.4;
// effects
--rounded: 3px;
diff --git a/_styles/body.scss b/_styles/body.scss
index 91ecffcfb..d34ef67ff 100644
--- a/_styles/body.scss
+++ b/_styles/body.scss
@@ -10,6 +10,7 @@ body {
background: var(--background);
color: var(--text);
font-family: var(--body);
+ font-size: 15px;
text-align: center;
line-height: var(--compact);
}
diff --git a/_styles/bold.scss b/_styles/bold.scss
index 01c72f687..01efe1e85 100644
--- a/_styles/bold.scss
+++ b/_styles/bold.scss
@@ -5,3 +5,9 @@ b,
strong {
font-weight: var(--bold);
}
+
+// Blue bold emphasis for key terms
+.blue {
+ color: var(--primary);
+ font-weight: var(--bold);
+}
\ No newline at end of file
diff --git a/_styles/citation.scss b/_styles/citation.scss
index dc6c95e2a..11fad92b1 100644
--- a/_styles/citation.scss
+++ b/_styles/citation.scss
@@ -10,40 +10,41 @@ $wrap: 800px;
.citation {
display: flex;
- margin: 20px 0;
- border-radius: var(--rounded);
+ flex-direction: row;
+ margin: 10px 0;
+ padding: 14px 18px;
+ border-radius: 6px;
background: var(--background);
- overflow: hidden;
- box-shadow: var(--shadow);
+ overflow: visible;
+ border-left: 3px solid var(--primary);
+ box-shadow: 0 1px 4px rgba(0, 0, 0, 0.06);
+ transition: box-shadow 0.2s, transform 0.15s;
+ align-items: flex-start;
}
-.citation-image {
- position: relative;
- width: $thumb-size;
- flex-shrink: 0;
- // box-shadow: var(--shadow);
+.citation:hover {
+ box-shadow: 0 3px 12px rgba(0, 0, 0, 0.10);
+ transform: translateY(-1px);
}
-.citation-image img {
- position: absolute;
- inset: 0;
- width: 100%;
- height: 100%;
- object-fit: contain;
+/* Hide thumbnail images for cleaner academic look */
+.citation-image {
+ display: none;
}
.citation-text {
position: relative;
display: inline-flex;
flex-wrap: wrap;
- gap: 10px;
+ gap: 4px;
max-width: 100%;
height: min-content;
- padding: 20px;
- padding-left: 30px;
+ padding: 0;
+ padding-left: 0;
text-align: left;
overflow-wrap: break-word;
z-index: 0;
+ font-size: 0.93em;
}
.citation-title,
@@ -54,50 +55,73 @@ $wrap: 800px;
}
.citation-title {
- font-weight: var(--semi-bold);
+ font-size: 1em;
+ font-weight: 600;
+ line-height: 1.4;
+ color: var(--primary);
+}
+
+.citation-title:hover {
+ text-decoration: underline;
}
.citation-text > .icon {
- position: absolute;
- top: 20px;
- right: 20px;
- color: var(--light-gray);
- opacity: 0.5;
- font-size: 30px;
- z-index: -1;
+ display: none;
+}
+
+.citation-authors {
+ font-size: 0.88em;
+ color: #444;
+ line-height: 1.4;
}
.citation-publisher {
text-transform: capitalize;
+ font-style: italic;
+}
+
+.citation-details {
+ font-size: 0.84em;
+ color: #777;
+ line-height: 1.4;
}
.citation-description {
- color: var(--gray);
+ font-size: 0.85em;
+ color: #666;
+ line-height: 1.45;
+ margin-top: 2px;
}
.citation-buttons {
display: flex;
flex-wrap: wrap;
- gap: 10px;
+ gap: 6px;
+ margin-top: 2px;
}
.citation-buttons .button {
margin: 0;
+ font-size: 0.82em;
+ padding: 2px 8px;
+ border-radius: 4px;
+ background: #f0f7ff;
+ color: var(--primary);
+ border: 1px solid #d6e8f7;
+}
+
+.citation-buttons .button:hover {
+ background: var(--primary);
+ color: #fff;
}
.citation-text > .tags {
display: inline-flex;
justify-content: flex-start;
- margin: 0;
+ margin: 2px 0 0 0;
}
-@container (max-width: #{$wrap}) {
- .citation {
- flex-direction: column;
- }
-
- .citation-image {
- width: unset;
- height: $thumb-size;
- }
+.citation-text > .tags .tag {
+ font-size: 0.78em;
+ padding: 1px 8px;
}
diff --git a/_styles/code.scss b/_styles/code.scss
index 4a50657eb..6ea031895 100644
--- a/_styles/code.scss
+++ b/_styles/code.scss
@@ -5,7 +5,7 @@ pre,
code,
pre *,
code * {
- font-family: var(--code);
+ font-family: var(--code), 'Fira Mono', 'Menlo', 'Monaco', 'Consolas', 'Liberation Mono', 'Courier New', monospace;
}
// inline code
diff --git a/_styles/feature.scss b/_styles/feature.scss
index 3d2a53f94..8e8f40ff0 100644
--- a/_styles/feature.scss
+++ b/_styles/feature.scss
@@ -7,8 +7,8 @@ $wrap: 800px;
display: flex;
justify-content: center;
align-items: center;
- gap: 40px;
- margin: 40px 0;
+ gap: 24px;
+ margin: 20px 0;
}
.feature-image {
diff --git a/_styles/footer.scss b/_styles/footer.scss
index d0d527741..b7d890b63 100644
--- a/_styles/footer.scss
+++ b/_styles/footer.scss
@@ -6,10 +6,11 @@ footer {
justify-content: center;
align-items: center;
flex-direction: column;
- gap: 20px;
- padding: 40px;
+ gap: 14px;
+ padding: 24px 30px;
line-height: var(--spacing);
box-shadow: var(--shadow);
+ font-size: 0.88rem;
}
footer a {
diff --git a/_styles/header.scss b/_styles/header.scss
index d6b435b12..4a318bb1e 100644
--- a/_styles/header.scss
+++ b/_styles/header.scss
@@ -99,13 +99,16 @@ nav {
justify-content: center;
align-items: center;
flex-wrap: wrap;
- gap: 10px;
+ gap: 8px;
font-family: var(--heading);
+ font-size: 0.88rem;
+ font-weight: var(--semi-bold);
text-transform: uppercase;
+ letter-spacing: 0.5px;
}
nav > a {
- padding: 5px;
+ padding: 4px 6px;
}
nav > a:hover {
diff --git a/_styles/heading.scss b/_styles/heading.scss
index f739e58a8..281127e71 100644
--- a/_styles/heading.scss
+++ b/_styles/heading.scss
@@ -7,45 +7,47 @@ h3,
h4,
h5,
h6 {
- margin: 40px 0 20px 0;
+ margin: 20px 0 8px 0;
font-family: var(--heading);
- font-weight: var(--semi-bold);
+ font-weight: var(--bold);
text-align: left;
- letter-spacing: 1px;
+ letter-spacing: 0.3px;
}
h1 {
- margin: 40px 0;
- font-size: 1.6rem;
- font-weight: var(--regular);
+ margin: 20px 0;
+ font-size: 1.5rem;
+ font-weight: var(--semi-bold);
text-transform: uppercase;
text-align: center;
+ letter-spacing: 1px;
}
h2 {
- font-size: 1.6rem;
- padding-bottom: 5px;
+ font-size: 1.35rem;
+ padding-bottom: 4px;
border-bottom: solid 1px var(--light-gray);
- font-weight: var(--regular);
+ font-weight: var(--semi-bold);
}
h3 {
- font-size: 1.5rem;
+ font-size: 1.15rem;
+ font-weight: var(--semi-bold);
}
h4 {
- font-size: 1.3rem;
+ font-size: 1.05rem;
}
h5 {
- font-size: 1.15rem;
+ font-size: 0.95rem;
}
h6 {
- font-size: 1rem;
+ font-size: 0.9rem;
}
:where(h1, h2, h3, h4, h5, h6) > .icon {
- margin-right: 1em;
+ margin-right: 0.6em;
color: var(--light-gray);
}
diff --git a/_styles/list.scss b/_styles/list.scss
index d769a6a38..f28cd718c 100644
--- a/_styles/list.scss
+++ b/_styles/list.scss
@@ -3,8 +3,8 @@
ul,
ol {
- margin: 20px 0;
- padding-left: 40px;
+ margin: 6px 0;
+ padding-left: 24px;
}
ul {
@@ -12,10 +12,11 @@ ul {
}
li {
- margin: 5px 0;
- padding-left: 10px;
+ margin: 2px 0;
+ padding-left: 4px;
text-align: justify;
line-height: var(--spacing);
+ font-size: 0.95rem;
ul,
ol {
diff --git a/_styles/paragraph.scss b/_styles/paragraph.scss
index 08b05a331..f9b612eac 100644
--- a/_styles/paragraph.scss
+++ b/_styles/paragraph.scss
@@ -2,7 +2,8 @@
---
p {
- margin: 20px 0;
+ margin: 8px 0;
text-align: justify;
line-height: var(--spacing);
+ font-size: 0.95rem;
}
diff --git a/_styles/post-excerpt.scss b/_styles/post-excerpt.scss
index 27c7a1dc1..d5cfec42b 100644
--- a/_styles/post-excerpt.scss
+++ b/_styles/post-excerpt.scss
@@ -1,7 +1,7 @@
---
---
-$thumb-size: 200px;
+$thumb-size: 160px;
$wrap: 800px;
.post-excerpt-container {
@@ -10,18 +10,24 @@ $wrap: 800px;
.post-excerpt {
display: flex;
- margin: 20px 0;
- border-radius: var(--rounded);
+ margin: 12px 0;
+ border-radius: 6px;
background: var(--background);
overflow: hidden;
- box-shadow: var(--shadow);
+ border-left: 3px solid var(--primary);
+ box-shadow: 0 1px 4px rgba(0, 0, 0, 0.06);
+ transition: box-shadow 0.2s, transform 0.15s;
+}
+
+.post-excerpt:hover {
+ box-shadow: 0 3px 12px rgba(0, 0, 0, 0.10);
+ transform: translateY(-1px);
}
.post-excerpt-image {
position: relative;
width: $thumb-size;
flex-shrink: 0;
- // box-shadow: var(--shadow);
}
.post-excerpt-image img {
@@ -35,8 +41,8 @@ $wrap: 800px;
.post-excerpt-text {
display: flex;
flex-wrap: wrap;
- gap: 20px;
- padding: 20px 30px;
+ gap: 6px;
+ padding: 14px 20px;
text-align: left;
}
@@ -46,15 +52,27 @@ $wrap: 800px;
.post-excerpt-text > a:first-child {
width: 100%;
- font-weight: var(--semi-bold);
+ font-weight: 600;
+ font-size: 1.05em;
+ color: var(--primary);
+ line-height: 1.4;
+}
+
+.post-excerpt-text > a:first-child:hover {
+ text-decoration: underline;
}
.post-excerpt-text > div {
justify-content: flex-start;
+ font-size: 0.85em;
+ color: #777;
}
.post-excerpt-text > p {
width: 100%;
+ font-size: 0.9em;
+ line-height: 1.5;
+ color: #444;
}
@container (max-width: #{$wrap}) {
diff --git a/_styles/rule.scss b/_styles/rule.scss
index abf797b82..ec4eca012 100644
--- a/_styles/rule.scss
+++ b/_styles/rule.scss
@@ -2,7 +2,7 @@
---
hr {
- margin: 40px 0;
+ margin: 20px 0;
background: var(--light-gray);
border: none;
height: 1px;
diff --git a/_styles/search-box.scss b/_styles/search-box.scss
index 5f20a783c..091d0dc26 100644
--- a/_styles/search-box.scss
+++ b/_styles/search-box.scss
@@ -24,3 +24,88 @@
color: var(--black);
border: none;
}
+
+/* Smart search suggestion styles */
+.search-suggestions {
+ position: absolute;
+ top: 100%;
+ left: 0;
+ width: 100%;
+ background: #fff;
+ border: 1px solid #ccc;
+ border-radius: 0 0 8px 8px;
+ box-shadow: 0 2px 8px rgba(0,0,0,0.08);
+ z-index: 10;
+ max-height: 220px;
+ overflow-y: auto;
+ display: none;
+ font-size: 1rem;
+}
+
+.suggestion-item {
+ display: flex;
+ flex-direction: column;
+ gap: 2px;
+ padding: 12px 18px;
+ cursor: pointer;
+ color: var(--black);
+ transition: background 0.2s;
+ border-bottom: 1px solid #f0f0f0;
+}
+.suggestion-item:last-child {
+ border-bottom: none;
+}
+.suggestion-item:hover {
+ background: var(--light-gray, #f5f5f5);
+}
+.suggestion-title {
+ font-weight: 600;
+ color: var(--primary, #1a73e8);
+ font-size: 1.05em;
+}
+.suggestion-tags {
+ font-size: 0.92em;
+ color: var(--secondary, #666);
+ margin-top: 2px;
+ display: flex;
+ flex-wrap: wrap;
+ gap: 6px;
+}
+.suggestion-tag {
+ background: var(--light-gray, #f5f5f5);
+ color: var(--primary, #1a73e8);
+ border-radius: 999px;
+ padding: 2px 10px;
+ font-size: 0.9em;
+}
+
+.search-box .search-input {
+ border-radius: 8px;
+ border: 1.5px solid #bdbdbd;
+ padding: 10px 14px;
+ font-size: 1.08rem;
+ box-sizing: border-box;
+ outline: none;
+ transition: border-color 0.2s, box-shadow 0.2s;
+}
+.search-box .search-input:focus {
+ border-color: var(--primary, #1a73e8);
+ box-shadow: 0 0 0 2px rgba(26,115,232,0.08);
+}
+
+.search-box button {
+ border-radius: 8px;
+ border: 1.5px solid #bdbdbd;
+ background: #f5f5f5;
+ color: var(--black);
+ font-size: 1.08rem;
+ cursor: pointer;
+ padding: 0 16px;
+ height: 38px;
+ margin-left: 8px;
+ transition: background 0.2s, border-color 0.2s;
+}
+.search-box button:hover {
+ background: var(--light-gray, #eaeaea);
+ border-color: var(--primary, #1a73e8);
+}
diff --git a/_styles/section.scss b/_styles/section.scss
index 332deb65d..a332681ef 100644
--- a/_styles/section.scss
+++ b/_styles/section.scss
@@ -2,7 +2,7 @@
---
$page: 1000px;
-$padding: 40px;
+$padding: 30px;
section {
padding: $padding max($padding, calc((100% - $page) / 2));
diff --git a/blog/index.md b/blog/index.md
index 1f1ce0d96..67ed80176 100644
--- a/blog/index.md
+++ b/blog/index.md
@@ -1,8 +1,8 @@
---
title: Blog
-nav:
- order: 5
- tooltip: Knowledge sharing
+# nav:
+# order: 5
+# tooltip: Knowledge sharing
---
# {% include icon.html icon="fa-solid fa-feather-pointed" %}Blog
diff --git a/contact/index.md b/contact/index.md
deleted file mode 100644
index 458494076..000000000
--- a/contact/index.md
+++ /dev/null
@@ -1,81 +0,0 @@
----
-title: Join Us!
-nav:
- order: 6
- tooltip: Email, address, and location
----
-
-# {% include icon.html icon="fa-regular fa-envelope" %}Join Us
-
-
-### Openings
-
-We regularly have multiple openings for Postdoc/PhD/MPhil/RA/Internships (All year round) to work on research related to trustworthy autonomous systems in general, including UAV and self-driving cars. If you are a PolyU student (Undergraduate and MSc students seeking URIS or dissertation supervision) interested in working with me, feel free to drop me an email (together with your transcript and brief introduction) or walk into my office at room R820!
-
-**Postdoc/RA positions** (Regular quotas): High precise perception positioning control with multi-sensory integration, autonomous systems, unmanned aerial vehicles (UAV), semantic aided positioning, map update and qualification, hardware-software co-design for next-generation navigation chips, urban GNSS positioning, GNSS RTK, PPP, PPP-RTK, multi-agent collaborative positioning. For those interested, please send us your CV, representative publications list, and research statement/proposal. (We will reply to you within one week if you are shortlisted for an interview). For any candidate, you MUST have at least one of the following properties: (1) a strong publication record! Or (2) strong capabilities in coding (at least C++ or Python) or hardware. Or (3) strong capabilities in preparing research proposals.
-
-**PhD/MPhil topics** (Regular quotas): Safety-certifiable positioning, control, and perception for autonomous systems. For more topics we are working on, please refer to our project page. For those interested, please send us your CV, representative publications list, and research proposal. (We will reply to you within one week if you are shortlisted for an interview).
-
-
-{%
- include button.html
- type="email"
- text="welson.wen@polyu.edu.hk"
- link="welson.wen@polyu.edu.hk"
-%}
-{%
- include button.html
- type="phone"
- text="(852) 3400 8234"
- link="+852 3400 8234"
-%}
-{%
- include button.html
- type="address"
- tooltip="Our location on Google Maps for easy navigation"
- link="https://maps.app.goo.gl/Aj8Zj2xQ8KzHSRtr9"
-%}
-
-{% include section.html %}
-
-{% capture col1 %}
-
-{%
- include figure.html
- image="images/AboutPolyU_Campus3.png"
- caption=" "
-%}
-
-{% endcapture %}
-
-{% capture col2 %}
-
-{%
- include figure.html
- image="images/AboutPolyU_Campus5.jpg"
- caption=" "
-%}
-
-{% endcapture %}
-
-{% include cols.html col1=col1 col2=col2 %}
-
-{% include section.html %}
-
-
-
-{% capture col1 %}
-
-{% endcapture %}
-
-{% capture col2 %}
-
-{% endcapture %}
-
-{% capture col3 %}
-
-{% endcapture %}
-
-{% include cols.html col1=col1 col2=col2 col3=col3 %}
-
-
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new file mode 100644
index 000000000..8b1378917
--- /dev/null
+++ b/images/news/0116_linxai/readme.md
@@ -0,0 +1 @@
+
diff --git a/images/news/0119_simpleai/1.png b/images/news/0119_simpleai/1.png
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new file mode 100644
index 000000000..8b1378917
--- /dev/null
+++ b/images/news/0119_simpleai/readme.md
@@ -0,0 +1 @@
+
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diff --git a/index.md b/index.md
index fe5bff192..4f91793f6 100644
--- a/index.md
+++ b/index.md
@@ -3,84 +3,136 @@
# PolyU TAS LAB's Website
-
-The Trustworthy AI and Autonomous Systems (TAS) Laboratory is at the forefront of pioneering advancements in autonomous systems (such as UAV and self-driving cars) technology, emphasizing the importance of safety, reliability, and ethical standards. Our laboratory is home to a diverse group of researchers and engineers who specialize in artificial intelligence, robotics, cybersecurity, and human-system interaction. Together, we are committed to developing autonomous systems that inspire confidence and trust among users and stakeholders. Through collaborative efforts with industry partners, academic institutions, and policymakers, our team addresses the complex challenges of integrating autonomous systems into society, ensuring they operate transparently and responsibly.
+
+The Trustworthy AI and Autonomous Systems (TAS) Laboratory is at the forefront of pioneering advancements in autonomous systems (such as UAV and self-driving cars) technology, emphasizing the importance of safety, reliability, and ethical standards. Our laboratory is home to a diverse group of researchers and engineers who specialize in artificial intelligence, robotics, cybersecurity, and human-system interaction. Together, we are committed to developing autonomous systems that inspire confidence and trust among users and stakeholders. Through collaborative efforts with industry partners, academic institutions, and policymakers, our team addresses the complex challenges of integrating autonomous systems into society, ensuring they operate transparently and responsibly.
+Our research aims to build algorithm foundations for embodied AI that enable trustworthy perception, navigation, and control of autonomous systems. We develop practical embodied AI-driven autonomous systems — including drones, intelligent vehicles, and legged/humanoid robots — with end-to-end learning and safety certification capabilities, enabling them to perceive, reason, and interact with the physical world safely and reliably for the future society. Our work spans large AI models for autonomous systems, foundation models and vision-language-action models for robotic perception and control, AI-enabled multi-sensor fusion, and software-hardware co-design for efficient embodied AI systems.
+
-{% endcapture %}
+{% include section.html %}
-{%
- include feature.html
- image="images/team/team.png"
- link="team"
- title="Our Team"
- text=text
-%}
+## Visitor Map
-
\ No newline at end of file
+
+
+
+
+
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index a0e2d9df5..32cf2c38a 100644
--- a/news/index.md
+++ b/news/index.md
@@ -1,11 +1,11 @@
---
-title: Events & News
+title: News
nav:
order: 1
- tooltip: Recent News
+ tooltip: Events and news
---
-# {% include icon.html icon="fa-light fa-bullhorn" %}Events & News
+# {% include icon.html icon="fa-solid fa-newspaper" %}News
diff --git a/openings/index.md b/openings/index.md
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index 000000000..867f176f9
--- /dev/null
+++ b/openings/index.md
@@ -0,0 +1,99 @@
+---
+title: Openings
+nav:
+ order: 7
+ tooltip: Openings and contact
+---
+
+# {% include icon.html icon="fa-regular fa-envelope" %}Openings
+
+We regularly have multiple openings for Postdoc/PhD/MPhil/RA/Internships (all year round) to work on research related to AI-driven trustworthy autonomous systems, with a focus on end-to-end autonomous UAVs and end-to-end self-driving cars. If you are a PolyU student (Undergraduate and MSc students seeking URIS or dissertation supervision) interested in working with me, feel free to drop me an email at welson.wen@polyu.edu.hk (together with your transcript and brief introduction) or walk into my office at room R820!
+
+---
+
+#### Postdoc/PhD/MPhil/RA Research Directions
+
+- Embodied AI and foundation models for robotics (drones, autonomous vehicles, ground robots)
+- High-precision positioning with multi-sensor fusion (LiDAR/Camera/IMU/GNSS) and integrity monitoring
+- End-to-end learning for self-driving cars and autonomous UAVs
+- Trustworthy and safety-certifiable AI for navigation and control
+- Software-hardware co-design for efficient embodied AI systems
+- Vision-language-action models and multimodal learning for autonomous systems
+
+For more specific topics, please refer to our [TAS Lab website](https://polyu-taslab.github.io/) and [research page](https://polyu-taslab.github.io/research/).
+
+---
+
+#### Application Requirements
+
+For those interested, please send the following materials to welson.wen@polyu.edu.hk:
+
+1. CV (with education background, publications, awards, and coding experience)
+2. Representative publications list (if any)
+3. A detailed research proposal (~6 pages) including abstract, background and literature review, research objectives, proposed methodology, expected outcomes, timeline, and references.
+
+We will reply to you within one week if you are shortlisted for an interview.
+
+For any candidate, you MUST have at least two of the following:
+
+1. A strong publication record in top-tier AI/robotics venues (e.g., NeurIPS, ICML, ICRA, IROS, CoRL, CVPR, ICCV);
+2. Strong capabilities in coding (proficient in C++ and/or Python, experience with PyTorch/TensorFlow/ROS);
+3. Awards or demonstrated excellence in robotics competitions (e.g., RoboMaster, ICRA competitions) are strongly preferred for PhD/MPhil applicants.
+
+---
+
+#### What We Offer
+
+- Access to cutting-edge UAV platforms, self-driving car testbeds, and GPU computing clusters
+- Collaboration with leading industry partners (Huawei, Tencent, Meituan, HONOR)
+- Opportunities to publish in top AI/robotics conferences and journals
+- A vibrant, diverse, and inclusive research environment with 30+ lab members
+- Funding support for conference travel and research equipment
+
+**Application materials:** CV + Publications/Coding portfolio + Research statement → welson.wen@polyu.edu.hk
+
+{%
+ include button.html
+ type="email"
+ text="welson.wen@polyu.edu.hk"
+ link="welson.wen@polyu.edu.hk"
+%}
+{%
+ include button.html
+ type="phone"
+ text="(852) 3400 8234"
+ link="+852 3400 8234"
+%}
+{%
+ include button.html
+ type="address"
+ tooltip="Our location on Google Maps for easy navigation"
+ link="https://maps.app.goo.gl/Aj8Zj2xQ8KzHSRtr9"
+%}
+
+{% include section.html %}
+
+{% capture col1 %}
+
+{%
+ include figure.html
+ image="images/AboutPolyU_Campus3.png"
+ width="66%"
+ caption=" "
+%}
+
+{% endcapture %}
+
+{% capture col2 %}
+
+{%
+ include figure.html
+ image="images/AboutPolyU_Campus5.jpg"
+ width="66%"
+ caption=" "
+%}
+
+{% endcapture %}
+
+{% include cols.html col1=col1 col2=col2 %}
+
diff --git a/opensource/index.md b/opensource/index.md
new file mode 100644
index 000000000..113ab1da0
--- /dev/null
+++ b/opensource/index.md
@@ -0,0 +1,20 @@
+---
+title: Dataset & Code
+nav:
+ order: 6
+ tooltip: Open-source datasets and code
+---
+
+# {% include icon.html icon="fa-solid fa-code" %}Dataset & Code
+
+
+We are committed to open science and reproducible research by sharing our datasets, software packages, and code with the broader research community. Below are the open-source tools and resources developed by TAS Lab, spanning GNSS positioning, multi-sensor fusion, visual localization, and HD mapping. All repositories are publicly available on the TAS Lab GitHub.
+
+
+{% include section.html %}
+
+{% include search-box.html %}
+
+{% include search-info.html %}
+
+{% include list.html data="opensource" component="post-excerpt" %}
diff --git a/projects/index.md b/projects/index.md
deleted file mode 100644
index 9084d4686..000000000
--- a/projects/index.md
+++ /dev/null
@@ -1,22 +0,0 @@
----
-title: Projects
-nav:
- order: 3
- tooltip:
----
-
-# {% include icon.html icon="fa-solid fa-wrench" %}Projects
-
-
-
-
-
-{% include section.html %}
-
-{% include search-box.html %}
-
-{% include tags.html tags=site.tags %}
-
-{% include search-info.html %}
-
-{% include list.html data="posts" component="post-excerpt" %}
\ No newline at end of file
diff --git a/publications/index.md b/publications/index.md
new file mode 100644
index 000000000..66ab9c4e7
--- /dev/null
+++ b/publications/index.md
@@ -0,0 +1,21 @@
+---
+title: Publications
+nav:
+ order: 2
+ tooltip: Journal and conference papers
+---
+
+# {% include icon.html icon="fa-solid fa-book" %}Publications
+
+More on [Google Scholar](https://scholar.google.com/citations?user=N-AFqt8AAAAJ&hl=en){:target="_blank"} \| *: Corresponding author
+{:.center}
+
+{% include section.html %}
+
+## All
+
+{% include search-box.html %}
+
+{% include search-info.html %}
+
+{% include list.html data="citations" component="citation" style="rich" %}
diff --git a/research/papers/2004.10572v2.pdf b/publications/papers/2004.10572v2.pdf
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+---
+title: Embodied Drones for City Maintenance
+---
+
+# 🚁 Embodied Drones for City Maintenance and Manipulation
+
+
+Maintaining urban infrastructure in dense city environments — particularly external wall cleaning of high-rise buildings and structural inspection in urban canyons — presents significant challenges that demand intelligent, physically interactive drone systems. This research develops embodied drone platforms that combine autonomous navigation in GPS-degraded urban canyons with contact-based manipulation capabilities for real-world city maintenance tasks.
+
+
+
+Our approach addresses three fundamental challenges:
+
+
Autonomous Inspection in Urban Canyons — Dense urban environments with tall buildings, narrow streets, and GPS-degraded conditions pose severe challenges for drone navigation. We develop AI-driven multi-sensor fusion algorithms (LiDAR/Camera/IMU/GNSS) and robust localization methods that enable drones to navigate safely and precisely in complex urban canyon environments. Our systems provide centimeter-level positioning for close-proximity inspection of building facades, bridges, and other urban structures.
+
External Wall Cleaning with Drones — High-rise external wall cleaning is one of the most hazardous tasks in urban maintenance. We develop drone-based cleaning systems that integrate aerial manipulation with contact-aware flight control, enabling drones to approach building surfaces, maintain stable contact, and perform cleaning operations autonomously. Our force-controlled manipulation strategies ensure safe and effective cleaning while accommodating varying surface geometries, wind disturbances, and dynamic environmental conditions.
+
Software-Hardware Co-Design for Maintenance Drones — We pursue an integrated approach to drone system design, jointly optimizing the AI software stack (perception, planning, contact control) with the hardware platform (airframe, cleaning/manipulation end-effectors, onboard compute) to achieve reliable embodied AI performance under the strict size, weight, and power (SWaP) constraints of aerial platforms.
+
+
+
+
+
+
+
Embodied Drones for City Maintenance and Manipulation
Integrated Planning and Control on Manifolds: Factor Graph Representation and Toolkit. Yang, P., Wen, W., Yang, R., Zhang, Y., Hu, J., Chen, Y., Xiao, N., Zhao, J. IEEE International Conference on Robotics & Automation (ICRA), 2026.
+
+
Learning Safe, Optimal, Real-Time Flight Interaction with Deep Confidence-enhanced Reachability Guarantee. Zhang, Y., Wang, Y., Yan, P., Wen, W. IEEE Transactions on Intelligent Transportation Systems, 2025.(IF: 8.4, JCR Q1, Citations: 2)
+
+
Tightly Joined Positioning and Control Model for Unmanned Aerial Vehicles Based on Factor Graph Optimization. Yang, P., Wen, W.*, Bai, S., Hsu, L.T. IEEE Transactions on Vehicular Technology, 2025.(IF: 7.1, JCR Q1, Citations: 4)
+
+
Online Dynamic Model Calibration for Reliable Control of Quadrotor Based on Factor Graph Optimization. Yang, P., Wen, W.*, Bai, S., Hu, J. IEEE Transactions on Aerospace and Electronic Systems, 2025.(IF: 5.7, JCR Q1, Citations: 2)
+
+
RTT-LIO: A Wi-Fi RTT-aided LiDAR-Inertial Odometry via Tightly-Coupled Factor Graph Optimization in Complex Scenes. Xu, R., Liu, X., Wang, X., Wen, W., Huang, Y. IEEE Internet of Things Journal, 2025.(IF: 8.9, JCR Q1)
+
+
Safe-Assured Learning-Based Deep SE(3) Motion Joint Planning and Control for UAV Interactions with Dynamic Environments. Zhang, Y., Wen, W., Yan, P. IEEE ITSC 2024.(Citations: 4)
+
+
SUG-UAV Multirotor Dataset with Multi-sensor Integration in Indoor and Urban Areas. Xiao, N., Wen, W.*, Hu, J., Yang, P., Zhao, J., Wu, C., Bai, S. IPIN 2024.(Citations: 3)
+
+
Tightly Joining Positioning and Control for Trustworthy Unmanned Aerial Vehicles Based on Factor Graph Optimization in Urban Transportation. Yang, P., Wen, W. IEEE ITSC 2023.(Citations: 7)
+
+
Tightly-Coupled Wi-Fi/LiDAR/Inertial Integration via Factor Graph Optimization for UAS. Xu, R., Liu, X., Wen, W. 2025 IEEE/ION PLANS, 648-653.(Citations: 1)
+
+{% include section.html %}
+
+## Acknowledgement and Collaborators
+
+
+This research is supported by The Hong Kong Polytechnic University, the Department of Science and Technology of Guangdong Province (Drone System and Offshore Wind Turbines Inspection), Esri China (HK) Limited (Vision-Language-Action Models for Intelligent UAV Systems), and Meituan (Vision Aided GNSS-RTK Positioning for UAV System in Urban Canyons). We collaborate with leading research groups and industry partners in intelligent drone systems and urban maintenance solutions.
+
+
+{% include section.html %}
+
+{% assign posts = site.posts | where: "research_direction", "drones" | sort: "date" | reverse %}
+
+## Projects ({{ posts.size }})
+
+{% for post in posts %}
+ {% include post-excerpt.html title=post.title url=post.url image=post.image content=post.content excerpt=post.excerpt date=post.date author=post.author tags=post.tags last_modified_at=post.last_modified_at %}
+{% endfor %}
diff --git a/research/education.md b/research/education.md
new file mode 100644
index 000000000..3971cbd82
--- /dev/null
+++ b/research/education.md
@@ -0,0 +1,122 @@
+---
+title: Embodied AI for Robotics Education
+---
+
+# Embodied AI for Robotics Education
+
+← Back to all Research Directions
+
+
+
+---
+
+## Abstract
+
+
+
+
+
+
+At the TAS Lab, we believe that cutting-edge research should go hand-in-hand with innovative education. Our research in Embodied AI for Robotics Education focuses on developing AI-powered educational platforms and hands-on learning experiences that bridge the gap between academic research and industry-ready skills. We leverage our expertise in autonomous systems — including drones, ground robots, and intelligent vehicles — to create immersive, project-based curricula that empower the next generation of roboticists and AI engineers.
+
+
+
+Our educational research integrates embodied AI concepts into university courses and outreach programs, enabling students to interact with real robotic hardware and state-of-the-art AI algorithms. From GNSS-based navigation labs to end-to-end autonomous driving projects, we design curricula that combine theoretical foundations with practical implementations, fostering both deep understanding and engineering competency.
+
+
+---
+
+## Key Research Directions
+
+
+
AI-Powered Robotics Education Platforms — Developing integrated hardware-software platforms for teaching AI, perception, navigation, and control using real drones, ground robots, and autonomous vehicles.
+
GitHub-Based Collaborative Learning — Pioneering open-source, GitHub-based pedagogical approaches with 50+ code examples that have been adopted by universities worldwide, including Wuhan University, Beihang University, and UC Berkeley.
+
Hands-on Project-Based Learning (PBL) — Designing curricula around ROS-based robotic car projects, drone programming workshops (PX4/ArduPilot), MATLAB/Python demonstrations, and deep learning framework integration.
+
Bridging Research and Industry Skills — Training students with industry-relevant tools and platforms, preparing them for careers in autonomous systems, AI engineering, and robotics R&D.
+
Embodied AI Curriculum Development — As Associate Programme Leader, Dr. Wen drafted the MSc in Low-altitude Economy proposal to meet emerging industry needs in drone technology and urban air mobility.
+
+
+---
+
+## Courses and Teaching Platforms
+
+
+Our education research is tightly integrated with the following courses at The Hong Kong Polytechnic University:
+
+
+
+
AAE4011 — Artificial Intelligence in Unmanned Autonomous Systems: Covers AI fundamentals for autonomous drones and ground robots, including perception, planning, and decision-making using deep learning and reinforcement learning.
+
AAE4203 — Guidance and Navigation: GNSS positioning (SPP, DGNSS, RTK), visual navigation, state estimation using Kalman filtering and factor graph optimization. Features video lectures and hands-on tutorials.
+
AAE3004 — Dynamical Systems and Control: Fundamentals of dynamical systems modeling, stability analysis, and feedback control design for aerospace and robotics applications.
+
AAE6102 — Satellite Communication and Navigation (Invited Lecture): Advanced GNSS positioning techniques, multi-sensor integration, and AI-aided navigation in urban environments.
+
+
+---
+
+## Video Lectures
+
+
+
+
AAE4203 Guidance and Navigation — Lecture Series on YouTube
+
+
+---
+
+## Robotics Competitions
+
+
+TAS Lab actively supports and supervises students in robotics competitions, providing mentorship, technical resources, and hands-on training. Competitions are a vital platform for students to apply their theoretical knowledge, develop teamwork skills, and push the boundaries of autonomous systems engineering.
+
+
+
+
PolyU Robotics Club (Supervisor) — Dr. Wen serves as the faculty supervisor of the PolyU Robotics Club, guiding students in designing, building, and programming robots for national and international competitions. The club brings together students from diverse engineering disciplines to collaborate on cutting-edge robotics projects.
+
RoboMaster University Championship — TAS Lab mentors student teams competing in the DJI RoboMaster competition, one of the world's most prestigious university robotics contests, involving autonomous robot combat, AI-based perception, and real-time strategy.
+
ICRA Robot Challenges — Supporting student participation in IEEE ICRA robot challenges, including autonomous navigation, manipulation, and multi-robot coordination tasks.
+
UAV / Drone Competitions — Supervising teams in autonomous UAV challenges, including indoor navigation, aerial manipulation, and drone swarm coordination, leveraging TAS Lab's expertise in embodied AI for drones.
+
Interdisciplinary Training — Competition preparation involves cross-training in mechanical design, embedded systems, computer vision, SLAM, and reinforcement learning, providing students with a comprehensive skill set for careers in robotics and AI.
+
+
+---
+
+## Student Supervision Highlights
+
+
+
Reliable UAV Perception and Perching Solutions in Urban Areas — ZHAO Jiaqi, LI Mingjue To, FU Chenlei (AAE10, 2024/25)
+
Handheld Multi-sensor Fusion Mapping System — QIN Qijun, WANG Yuteng (AAE11, 2024/25)
+
High-Definition Map with Traffic Signs Based on LiDAR-Visual-IMU Fusion SLAM — QIN Qijun (Merit Award, Best URIS Research Project 2024)
+
An Adaptive Drilling Process for the Aircraft Skin — LAU Chun Ho, LEUNG Cheuk To, CHAN Hei Lam Joshua (DD01, 2022/23)
+
UAS for Situation Awareness and Risk Assessment — LAM Yat Long, CHEN Yat Nam (AAE39, 2022/23)
+
Person-following Mobile Robotics — MOHAMMAD Tamz (AAE33, 2021/22)
+
+
+---
+
+## Acknowledgement and Collaborators
+
+
+Our robotics education initiatives are supported by The Hong Kong Polytechnic University, the Department of Aeronautical and Aviation Engineering, and the Faculty of Engineering. We are grateful to our collaborators at Wuhan University, Beihang University, UC Berkeley, and industry partners for adopting and contributing to our open-source educational resources.
+
+
+
+
+
diff --git a/research/fusion.md b/research/fusion.md
new file mode 100644
index 000000000..ed7bbe112
--- /dev/null
+++ b/research/fusion.md
@@ -0,0 +1,160 @@
+---
+title: Safety-certifiable Multi-Sensor Fusion
+---
+
+# 🔒 Safety-certifiable Multi-Sensor Fusion for Robotic Navigation in Urban Scenes
+
+
+The visual/LiDAR SLAM methods are challenged in complex urban scenarios, especially when safety certification is required for autonomous systems. In this project, we aim to study the mechanism of the impacts caused by dynamic scenarios on the visual/LiDAR SLAM methods, and develop safety-certifiable navigation algorithms that can quantify and guarantee the reliability of localization results. We try to answer the questions of how dynamic objects affect the state estimation of visual/LiDAR SLAM methods, how to improve robustness, and how to provide safety-quantifiable localization for robotics in complex urban environments.
+
+
+
+
+
+
GNSS/LiDAR/Visual/INS Integration for Robotics Navigation
+
+
+
+
+
Safety-certifiable Visual Localization with 3D Prior Map
September 2022, 1 paper accepted in IET Intelligent Transport Systems.
+
+
Zhong, Y., Huang, F., Zhang, J., Wen, W., Hsu, L.-T.: Low-cost solid-state LiDAR/inertial-based localization with prior map for autonomous systems in urban scenarios. IET Intell. Transp. Syst., 2022.
+
+
+
Aug 2022, 1 paper on LiDAR SLAM accepted in NAVIGATION: Journal of the Institute of Navigation.
+
+
Wen, W., & Hsu, L.T. (2022). AGPC-SLAM: Absolute Ground Plane Constrained 3D Lidar SLAM. NAVIGATION, 69(3).
+
+
+
+
+{% include section.html %}
+
+## Video Demonstration
+
+
+
+
+
Safety-quantifiable Line Feature-based Monocular Visual Localization with 3D Prior Map
+
+
+
+
+
Multi-sensor Integration Navigation System for Autonomous Driving
+
+
+
+
+
Demonstration: Low-cost Solid-state LiDAR/Inertial Based Localization with Prior Map
+
+
+
+
+
Presentation in ION GNSS+ 2021: A Coarse-to-Fine LiDAR-Based SLAM with Dynamic Object Removal
+
+
+
+
+
Presentation in ION GNSS+ 2021: Continuous GNSS-RTK Aided by LiDAR/Inertial Odometry
+
+{% include section.html %}
+
+## Related Papers (*: Corresponding author)
+
+
+
+
2025
+
+
+
POPL-SLAM: A Pose-Only Representation-Based Visual-Inertial SLAM With Point and Structural Line Features. Li, T., Han, B., Yan, D., Wen, W., Wang, Z., Shi, C. IEEE Transactions on Aerospace and Electronic Systems, 62, 1509-1525, 2025.(IF: 5.7, JCR Q1)
+
+
Safety-quantifiable Line Feature-based Monocular Visual Localization with 3D Prior Map. Zheng, X., Wen, W.*, Hsu, L.T. IEEE Transactions on Intelligent Transportation Systems, 2025.(IF: 8.4, JCR Q1, Citations: 3)
+
+
Fault Detection Algorithm for Gaussian Mixture Noises: An Application in Lidar/IMU Integrated Localization Systems. Yan, P., Li, Z., Huang, F., Wen, W., Hsu, L.T. NAVIGATION: Journal of the Institute of Navigation, 72(1), 2025.(IF: 3.1, JCR Q1, Citations: 6)
+
+
Multi-Sensor Plug-and-Play Navigation Based on Resilient Information Filter. Meng, Q., Su, C., Jiang, Y., Wen, W., Meng, X. IEEE Sensors Journal, 2025.(IF: 4.5, JCR Q1)
+
+
A Novel Lie Group-based Reliable IMM Estimation Method for SINS/GNSS/OD/NHC Integrated Navigation in Complex Environments. Du, S., Huang, Y., Wen, W., Zhang, Y. IEEE Internet of Things Journal, 2025.(IF: 8.9, JCR Q1, Citations: 5)
+
+
Graph-Based Indoor 3D Pedestrian Location Tracking With Inertial-Only Perception. Bai, S., Wen, W.*, Su, D., Hsu, L.T. IEEE Transactions on Mobile Computing, 2025.(IF: 9.2, JCR Q1, Citations: 5)
+
+
+
2024
+
+
+
Safety-Quantifiable Planar-Feature-based LiDAR Localization with a Prior Map for Intelligent Vehicles in Urban Scenarios. Zhang, J., Liu, X., Wen, W.*, Hsu, L.T. IEEE Transactions on Intelligent Vehicles, 2024.(IF: 14.3, JCR Q1, Citations: 2)
+
+
Factor Graph Optimization-Based Smartphone IMU-Only Indoor SLAM With Multi-Hypothesis Turning Behavior Loop Closures. Bai, S., Wen, W.*, Hsu, L.T., Yang, P. IEEE Transactions on Aerospace and Electronic Systems, 2024.(IF: 5.7, JCR Q1, Citations: 9)
+
+
Tightly-coupled Visual/Inertial/Map Integration with Observability Analysis for Reliable Localization of Intelligent Vehicles. Zheng, X., Wen, W.*, Hsu, L.T. IEEE Transactions on Intelligent Vehicles, 2024.(IF: 14.3, JCR Q1, Citations: 3)
+
+
Integrity-Constrained Factor Graph Optimization for GNSS Positioning in Urban Canyons. Xia, X., Wen, W., Hsu, L.T.* NAVIGATION: Journal of the Institute of Navigation, 2024.(IF: 3.1, JCR Q1, Citations: 5)
+
+
FGO-MFI: Factor Graph Optimization-based Multi-sensor Fusion and Integration for Reliable Localization. Zhu, J., Zhuo, G., Xia, X.*, Wen, W., Xiong, L., Leng, B., Liu, W. Measurement Science and Technology, 35(8), 086303, 2024.(IF: 3.4, JCR Q1, Citations: 7)
+
+
+
2023
+
+
+
GLIO: Tightly-coupled GNSS/LiDAR/IMU Integration for Continuous and Drift-free State Estimation of Intelligent Vehicles in Urban Areas. Liu, X., Wen, W.*, Hsu, L.T. IEEE Transactions on Intelligent Vehicles, 2023.(IF: 14.3, JCR Q1, Citations: 52)
+
+
Low-cost Solid-state LiDAR/Inertial Based Localization with Prior Map for Autonomous Systems in Urban Scenarios. Zhong, Y., Huang, F., Zhang, J., Wen, W.*, Hsu, L.T. IET Intelligent Transport Systems, 17(3), 474-486, 2023.(IF: 2.3, JCR Q2, Citations: 9)
+
+
+
2018–2022
+
+
+
AGPC-SLAM: Absolute Ground Plane Constrained 3D Lidar SLAM. Wen, W., & Hsu, L.T. NAVIGATION: Journal of the Institute of Navigation, 69(3), 2022.
Point Wise or Feature Wise? A Benchmark Comparison of Publicly Available Lidar Odometry Algorithms in Urban Canyons. Huang, F., Wen, W., Zhang, J., Hsu, L.T.* IEEE Intelligent Transportation Systems Magazine, 2021.
+
+
Robust Visual-Inertial Integrated Navigation System Aided by Online Sensor Model Adaption for Autonomous Ground Vehicles in Urban Areas. Bai, X., Wen, W., Hsu, L.T. Remote Sensing, 12(10), 1686, 2020.
+
+
Performance Analysis of NDT-based Graph SLAM for Autonomous Vehicle in Diverse Typical Driving Scenarios of Hong Kong. Wen, W., Hsu, L.T., Zhang, G. Sensors, 18, 3928, 2018.
+
+{% include section.html %}
+
+## Acknowledgement and Collaborators
+
+
+This research is supported by government and industry partners, including Hong Kong Polytechnic University, Guangdong Basic and Applied Basic Research Foundation, and Huawei Technologies. We collaborate with leading research groups in multi-sensor fusion and safety-certifiable navigation.
+
+
+
+
+
+
+{% include section.html %}
+
+{% assign posts = site.posts | where: "research_direction", "fusion" | sort: "date" | reverse %}
+
+## Projects ({{ posts.size }})
+
+{% for post in posts %}
+ {% include post-excerpt.html title=post.title url=post.url image=post.image content=post.content excerpt=post.excerpt date=post.date author=post.author tags=post.tags last_modified_at=post.last_modified_at %}
+{% endfor %}
diff --git a/research/gnss.md b/research/gnss.md
new file mode 100644
index 000000000..0663d5f9c
--- /dev/null
+++ b/research/gnss.md
@@ -0,0 +1,183 @@
+---
+title: 3D LiDAR Aided GNSS Positioning
+---
+
+# 🛰️ 3D LiDAR Aided GNSS Positioning for Robotics Navigation
+
+
+Positioning in urban environments is becoming essential due to the increasing demand for autonomous driving vehicles (ADV). The global navigation satellite system (GNSS) is currently one of the principal means of providing globally-referenced positioning for ADV localization. With the increased availability of multiple satellite constellations, GNSS can provide satisfactory performance in open-sky areas. However, the positioning accuracy is significantly degraded in highly-urbanized cities such as Hong Kong, due to signal reflection caused by static buildings and dynamic objects such as double-decker buses. If the direct line-of-sight (LOS) is blocked, and reflected signals from the same satellite are received, the notorious non-line-of-sight (NLOS) receptions occur. According to a recent review paper, NLOS is currently the major difficulty in the use of GNSS in intelligent transportation systems.
+
+
+
+Inspired by the strong perception capability of ADV using onboard sensors (such as 3D LiDAR), we continuously developed the perception-aided NLOS mitigation methods where the 3D LiDAR is employed to timely reconstruct the surrounding environments to identify the NLOS receptions. The idea was also reported in the industrial magazine in 2018. The work was further improved in 2020, where several drawbacks are relaxed and was awarded the Best Presentation Award in the session of Navigation in Urban Environments. Interestingly, this award is selected by the session chairs from Waymo and Swift Navigation. Meanwhile, the idea is transferred into industrial applications for high-accuracy offline mapping applications. Recently, we extended the LiDAR aided GNSS NLOS mitigation to the GNSS Real-time Kinematic (RTK), leading to sub-meter level accuracy. Unfortunately, the fixed rate of the RTK is still not guaranteed as:
+
+
+
+
+
The existing method does not fully mitigate the NLOS with multiple reflections and multipath. It is still an unknown question to model the multiple reflection and multipath.
+
Poor satellite geometry due to the signal blockage and potential NLOS exclusion. It is still an unknown question to effectively improve the geometry of the satellite constraints in dense urban canyons.
+
+
+
+
+
+
+
3D LiDAR Aided GNSS Positioning for Robotics Urban Navigation
May 2022, 1 paper accepted in IEEE Transactions on Intelligent Transportation Systems.
+
+
Wen, W., and Hsu, L.T., 2022. 3D LiDAR Aided GNSS NLOS Mitigation in Urban Canyons. IEEE Transactions on Intelligent Transportation Systems.
+
+
+
23rd April 2022, our conference paper was accepted in ION GNSS+ 2022.
+
+
Liu, X., Wen, W*., and Hsu, L.T. 2022, September. 3D LiDAR Aided GNSS Real-time Kinematic Positioning via Coarse-to-fine Batch Optimization for High Accuracy Mapping in Dense Urban Canyons. In Proceedings of ION GNSS+ 2022.
+
+
+
+
+{% include section.html %}
+
+## Video Demonstration
+
+
+
+
+
Demonstration: 3D LiDAR Aided NLOS Exclusion for GNSS Real-time Kinematic (RTK) Positioning in Urban Canyons
+
+
+
+
+
Presentation in ION GNSS+ 2021: 3D LiDAR Aided NLOS Exclusion for GNSS RTK Positioning
+
+
+
+
+
Demonstration: 3D LiDAR Aided NLOS Exclusion for GNSS Single Point Positioning
+
+
+
+
+
Presentation in ION GNSS+ 2020: 3D LiDAR Aided GNSS and Its Tightly Coupled Integration with INS
+
+
+
+
+
Presentation in ION GNSS+ 2021: Continuous GNSS-RTK Aided by LiDAR/Inertial Odometry
+
+{% include section.html %}
+
+## Related Papers (*: Corresponding author)
+
+
+
+
2025
+
+
+
3-D LiDAR-Aided GNSS NLOS Mitigation for Reliable GNSS-RTK Positioning in Urban Canyons. Liu, X., Wen, W.*, Huang, F., Gao, H., Wang, Y., Hsu, L.T. IEEE Transactions on Instrumentation and Measurement, 74, 1-15, 2025.(IF: 5.9, JCR Q1, Citations: 9)
+
+
3D LiDAR Aided GNSS NLOS Correction by Direction-of-Arrival Estimation Using Doppler Measurements in Urban Canyons. Liu, X., Wen, W.*, Zhang, L., Hsu, L.T. IEEE Transactions on Intelligent Transportation Systems, 2025.(IF: 8.4, JCR Q1)
+
+
Fisheye Image/GNSS Based Multimodal Learning for GNSS NLOS/Multipath Correction: Enhancing Vehicle Positioning in Urban Canyons for Autonomous Driving. Hu, R., Liu, J., Zhong, Y., Wen, W., Xia, M., Huang, Y. IEEE Transactions on Vehicular Technology, 2025.(IF: 7.1, JCR Q1)
+
+
pyrtklib: An Open-source Package for Tightly Coupled Deep Learning and GNSS Integration for Positioning in Urban Canyons. Hu, R., Xu, P., Zhong, Y., Wen, W. IEEE Transactions on Intelligent Transportation Systems, 2025.(IF: 8.4, JCR Q1, Citations: 7)
+
+
Urban GNSS Positioning for Consumer Electronics: 3D Mapping and Advanced Signal Processing. Wang, J., Xia, M., Zhang, D., Wen, W., Chen, W., Shi, C. IEEE Transactions on Consumer Electronics, 2025.(IF: 10.9, JCR Q1, Citations: 7)
+
+
+
2024
+
+
+
Integrity-Constrained Factor Graph Optimization for GNSS Positioning in Urban Canyons. Xia, X., Wen, W., Hsu, L.T.* NAVIGATION: Journal of the Institute of Navigation, 2024.(IF: 3.1, JCR Q1, Citations: 5)
+
+
Subspace-based Adaptive GMM Error Modeling for Fault-Aware Pseudorange-based Positioning in Urban Canyons. Yan, P., Xia, X., Brizzi, M., Wen, W., Hsu, L.T.* IEEE Transactions on Intelligent Vehicles, 2024.(IF: 14.3, JCR Q1, Citations: 4)
+
+
Trajectory Smoothing Using GNSS/PDR Integration Via Factor Graph Optimization in Urban Canyons. Zhong, Y., Wen, W.*, Hsu, L.T. IEEE Internet of Things Journal, 2024.(IF: 8.9, JCR Q1, Citations: 16)
+
+
Enhancing GNSS Positioning Accuracy for Road Monitoring Systems: A Factor Graph Optimization Approach Aided by Geospatial Information. Zhong, Y., Hu, R., Bai, X., Li, X., Hsu, L.T., Wen, W. IEEE Transactions on Instrumentation and Measurement, 73, 1-12, 2024.(IF: 5.9, JCR Q1, Citations: 12)
+
+
+
2023
+
+
+
3D Vision Aided GNSS Real-time Kinematic Positioning for Autonomous Systems in Urban Canyons. Wen, W.*, Bai, X., Hsu, L.T. NAVIGATION: Journal of the Institute of Navigation, 2023.(IF: 3.1, JCR Q1, Citations: 22)
+
+
Hong Kong UrbanNav: An Open-Source Multisensory Dataset for Benchmarking Urban Navigation Algorithms. Hsu, L.T., Huang, F., Ng, H.F., Zhang, G., Zhong, Y., Bai, X., Wen, W. NAVIGATION: Journal of the Institute of Navigation, 70(4), 2023.(IF: 3.1, JCR Q1, Citations: 80)
+
+
GLIO: Tightly-coupled GNSS/LiDAR/IMU Integration for Continuous and Drift-free State Estimation of Intelligent Vehicles in Urban Areas. Liu, X., Wen, W.*, Hsu, L.T. IEEE Transactions on Intelligent Vehicles, 2023.(IF: 14.3, JCR Q1, Citations: 52)
+
+
+
2021–2022
+
+
+
3D LiDAR Aided GNSS NLOS Mitigation in Urban Canyons. Wen, W., and Hsu, L.T. IEEE Transactions on Intelligent Transportation Systems, 2021.
+
+
Time-correlated Window Carrier-phase Aided GNSS Positioning in Urban Canyons. Bai, X., Wen, W.*, Hsu, L.T. IEEE Transactions on Aerospace and Electronic Systems, 2022.
+
+
GNSS Outlier Mitigation via Graduated Non-convexity Factor Graph Optimization. Wen, W., Zhang, G., Hsu, L.T. IEEE Transactions on Vehicular Technology, 71(1), 297-310, 2021.
+
+
Factor Graph Optimization for GNSS/INS Integration: A Comparison with the Extended Kalman Filter. Wen, W., Pfeifer, T., Bai, X., Hsu, L.T. NAVIGATION: Journal of the Institute of Navigation, 68(2), 315-331, 2021.
+
+
+
2018–2020
+
+
+
Object-Detection-Aided GNSS and Its Integration With Lidar in Highly Urbanized Areas. Wen, W., Zhang, G., Hsu, L.T. IEEE Intelligent Transportation Systems Magazine, 12(3), 53-69, 2020.
+
+
GNSS NLOS Exclusion Based on Dynamic Object Detection Using LiDAR Point Cloud. Wen, W., Zhang, G., Hsu, L.T. IEEE Transactions on Intelligent Transportation Systems, 2019.
+
+
Correcting NLOS by 3D LiDAR and Building Height to Improve GNSS Single Point Positioning. Wen, W., Zhang, G., Hsu, L.T. NAVIGATION: Journal of the Institute of Navigation, 66(4), 705-718, 2019.
+
+
Tightly Coupled GNSS/INS Integration via Factor Graph and Aided by Fish-eye Camera. Wen, W., Bai, X., Kan, Y.C., Hsu, L.T. IEEE Transactions on Vehicular Technology, 68(11), 10651-10662, 2019.
Inside GNSS — Feature on perceived environment aided GNSS positioning
+
Innovation Award from TechConnect
+
Best Presentation Award in ION GNSS+ 2020 — Session on Navigation in Urban Environments
+
+
+{% include section.html %}
+
+## Acknowledgement and Collaborators
+
+
+This research was funded by government and industry partners, including Hong Kong Polytechnic University, Guangdong Basic and Applied Basic Research Foundation, Riemann Laboratory, and Huawei Technologies.
+
+
+
+
+
+
+{% include section.html %}
+
+{% assign posts = site.posts | where: "research_direction", "gnss" | sort: "date" | reverse %}
+
+## Projects ({{ posts.size }})
+
+{% for post in posts %}
+ {% include post-excerpt.html title=post.title url=post.url image=post.image content=post.content excerpt=post.excerpt date=post.date author=post.author tags=post.tags last_modified_at=post.last_modified_at %}
+{% endfor %}
diff --git a/research/humanoid.md b/research/humanoid.md
new file mode 100644
index 000000000..5decf5fed
--- /dev/null
+++ b/research/humanoid.md
@@ -0,0 +1,114 @@
+---
+title: Embodied AI for Humanoid/Legged Robotics
+---
+
+# 🤖 Embodied AI for Humanoid/Legged Robotics
+
+
+Humanoid and legged robots represent the next frontier of embodied AI — machines that can perceive, reason, and physically interact with the world in a human-like manner. This research focuses on developing large AI models and vision-language-action (VLA) frameworks that enable humanoid and legged robots to autonomously navigate, manipulate, and collaborate in complex real-world environments.
+
+
+
+Our approach integrates three core pillars:
+
+
Foundation Models for Robotic Perception and Control — We develop vision-language-action models that bridge high-level semantic understanding with low-level motor control, enabling robots to interpret natural language instructions and execute complex manipulation and locomotion tasks. Our models leverage large-scale pre-training on multimodal data (vision, language, proprioception) and are fine-tuned for real-world deployment on humanoid platforms.
+
Bio-Inspired Embodied Intelligence — Drawing inspiration from biological locomotion and sensorimotor systems, we design control architectures that enable robust and adaptive walking, running, climbing, and manipulation on diverse terrains. Our work combines reinforcement learning, model predictive control, and sim-to-real transfer to achieve agile and stable locomotion for legged robots in unstructured environments.
+
Multimodal Learning for Humanoid Robots — We investigate how robots can learn from multimodal sensory inputs (RGB-D cameras, IMUs, tactile sensors, force/torque sensors) to build rich world models that support whole-body planning and contact-rich manipulation. Our research enables humanoid robots to perform tasks in human-centric environments such as homes, offices, and warehouses.
Integrated Planning and Control on Manifolds: Factor Graph Representation and Toolkit. Yang, P., Wen, W., Yang, R., Zhang, Y., Hu, J., Chen, Y., Xiao, N., Zhao, J. IEEE International Conference on Robotics & Automation (ICRA), 2026.
+
+
Unified Sufficient Conditions for Exact Convex Relaxation of Nonconvex Optimal Control Problems. Yang, R., Wen, W., Yang, P., Zhao, Z. and Huang, F. IEEE Transactions on Aerospace and Electronic Systems, 2025.(IF: 5.7, JCR Q1)
+
+
EIRM-RL: Epistemic Integrity Risk Monitoring Inspired Safe Reinforcement Learning for Trustworthy Autonomous Navigation. Zhang, Y., Wang, Y., Wen, W. IEEE Internet of Things Journal, 13(2), 3500-3512, 2025.(IF: 8.9, JCR Q1)
+
+
Learning Safe, Optimal, Real-Time Flight Interaction with Deep Confidence-enhanced Reachability Guarantee. Zhang, Y., Wang, Y., Yan, P., Wen, W. IEEE Transactions on Intelligent Transportation Systems, 2025.(IF: 8.4, JCR Q1, Citations: 2)
+
+
Tightly Joined Positioning and Control Model for Unmanned Aerial Vehicles Based on Factor Graph Optimization. Yang, P., Wen, W.*, Bai, S., Hsu, L.T. IEEE Transactions on Vehicular Technology, 2025.(IF: 7.1, JCR Q1, Citations: 4)
+
+
Online Dynamic Model Calibration for Reliable Control of Quadrotor Based on Factor Graph Optimization. Yang, P., Wen, W.*, Bai, S., Hu, J. IEEE Transactions on Aerospace and Electronic Systems, 2025.(IF: 5.7, JCR Q1, Citations: 2)
+
+
Safe-Assured Learning-Based Deep SE(3) Motion Joint Planning and Control for UAV Interactions with Dynamic Environments. Zhang, Y., Wen, W., Yan, P. IEEE ITSC 2024.(Citations: 4)
+
+
Tightly Joining Positioning and Control for Trustworthy Unmanned Aerial Vehicles Based on Factor Graph Optimization in Urban Transportation. Yang, P., Wen, W. IEEE ITSC 2023.(Citations: 7)
+
+{% include section.html %}
+
+## Acknowledgement and Collaborators
+
+
+This research is supported by The Hong Kong Polytechnic University and industry partners. We collaborate with leading research groups in embodied AI and robotics worldwide.
+
+
+{% include section.html %}
+
+{% assign posts = site.posts | where: "research_direction", "humanoid" | sort: "date" | reverse %}
+
+## Projects ({{ posts.size }})
+
+{% for post in posts %}
+ {% include post-excerpt.html title=post.title url=post.url image=post.image content=post.content excerpt=post.excerpt date=post.date author=post.author tags=post.tags last_modified_at=post.last_modified_at %}
+{% endfor %}
diff --git a/research/index.md b/research/index.md
index 4f3eaf54a..413243c9a 100644
--- a/research/index.md
+++ b/research/index.md
@@ -1,35 +1,190 @@
---
-title: Publications
+title: Research
nav:
- order: 2
- tooltip: Published works
+ order: 3
+ tooltip: Research projects and directions
---
-# {% include icon.html icon="fa-solid fa-microscope" %}Publications
+# {% include icon.html icon="fa-solid fa-flask" %}Research Topics
-
+
+Our research aims to build algorithm foundations for embodied AI that enable trustworthy perception, navigation, and control of autonomous systems. We develop practical embodied AI-driven autonomous systems — including drones, intelligent vehicles, and legged/humanoid robots — with end-to-end learning and safety certification capabilities, enabling them to perceive, reason, and interact with the physical world safely and reliably for the future society. Our work spans large AI models for autonomous systems, foundation models and vision-language-action models for robotic perception and control, AI-enabled multi-sensor fusion, and software-hardware co-design for efficient embodied AI systems.
+
+
+
+Research Directions:
+1) 3D LiDAR Aided GNSS Positioning — AI-driven GNSS positioning (RTK, PPP, PPP-RTK), 3D LiDAR aided NLOS/multipath mitigation, multi-sensor fusion for robust urban navigation;
+2) Safety-certifiable Multi-Sensor Fusion — safety-certifiable AI for autonomous navigation, AI-enabled multi-sensor fusion (LiDAR/Camera/IMU/GNSS), integrity monitoring and navigation-control joint optimization;
+3) End-to-End and Safety-Certifiable Autonomous Vehicles — end-to-end learning for self-driving, safety certification for logistics applications, V2X-assisted connected autonomous driving;
+4) Embodied AI for Humanoid/Legged Robotics — large AI models and vision-language-action models for robotic perception and control, bio-inspired embodied intelligence, multimodal learning for humanoid/legged robots;
+5) Embodied Drones for City Maintenance and Manipulation — intelligent drones and UAV swarm systems, aerial manipulation for urban infrastructure, software-hardware co-design for efficient embodied AI drone systems;
+6) Embodied AI for Robotics Education — AI-powered robotics education platforms, hands-on project-based learning with drones and ground robots, GitHub-based collaborative learning pedagogy, bridging academic research and industry-ready skills.
+
diff --git a/research/vehicles.md b/research/vehicles.md
new file mode 100644
index 000000000..4daf1bc4d
--- /dev/null
+++ b/research/vehicles.md
@@ -0,0 +1,128 @@
+---
+title: End-to-End Autonomous Vehicles
+---
+
+# 🚗 End-to-End and Safety-Certifiable Autonomous Vehicles for Logistics Applications
+
+
+Autonomous vehicles hold transformative potential for logistics and urban mobility, yet deploying them safely in real-world environments remains a grand challenge. This research focuses on developing end-to-end learning frameworks and safety-certifiable navigation systems for autonomous vehicles in logistics applications — from campus delivery and last-mile transportation to urban freight operations.
+
+
+
+Our approach integrates three core elements:
+
+
End-to-End Autonomous Driving — We develop neural network architectures that learn to drive directly from raw sensor inputs (LiDAR, camera, IMU, GNSS) to control outputs, enabling autonomous vehicles to handle complex urban scenarios including dense traffic, dynamic obstacles, and GPS-degraded environments. Our end-to-end pipelines unify perception, prediction, planning, and control into a single differentiable framework.
+
Safety Certification and Integrity Monitoring — Unlike conventional black-box approaches, our systems incorporate rigorous safety certification mechanisms. We design integrity monitoring algorithms that quantify the trustworthiness of navigation solutions in real time, enabling the vehicle to detect unsafe states and trigger fail-safe maneuvers. This is critical for logistics applications where reliability and regulatory compliance are paramount.
+
Real-World Deployment for Logistics — We bridge the gap between research and application by developing full-stack autonomous vehicle platforms for logistics use cases, including campus patrol, autonomous delivery, and connected fleet management. Our platforms feature multi-sensor fusion (GNSS-RTK/LiDAR/Camera/IMU), V2X communication, and robust localization in challenging urban canyon environments.
+
+
+
+
+
+
+
End-to-End and Safety-Certifiable Autonomous Vehicles for Logistics Applications
+
+
+
+
+
Autonomous Vehicle Platform for Campus Logistics and Urban Navigation
Sept 2022, we welcome the PolyU Campus Facilities and Sustainability Office (CFSO) and Health and Safety Office (HSO) to attend the demonstration of AAE/CFSO Campus Security Patrol with Unmanned Ground Vehicle (UGV)
Integrated Planning and Control on Manifolds: Factor Graph Representation and Toolkit. Yang, P., Wen, W., Yang, R., Zhang, Y., Hu, J., Chen, Y., Xiao, N., Zhao, J. IEEE International Conference on Robotics & Automation (ICRA), 2026.
+
+
EIRM-RL: Epistemic Integrity Risk Monitoring Inspired Safe Reinforcement Learning for Trustworthy Autonomous Navigation. Zhang, Y., Wang, Y., Wen, W. IEEE Internet of Things Journal, 13(2), 3500-3512, 2025.(IF: 8.9, JCR Q1)
+
+
Learning Safe, Optimal, Real-Time Flight Interaction with Deep Confidence-enhanced Reachability Guarantee. Zhang, Y., Wang, Y., Yan, P., Wen, W. IEEE Transactions on Intelligent Transportation Systems, 2025.(IF: 8.4, JCR Q1)
+
+
Safety-quantifiable Line Feature-based Monocular Visual Localization with 3D Prior Map. Zheng, X., Wen, W.*, Hsu, L.T. IEEE Transactions on Intelligent Transportation Systems, 2025.(IF: 8.4, JCR Q1, Citations: 3)
+
+
Continuous Error Map Aided Adaptive Multi-Sensor Integration for Connected Autonomous Vehicles in Urban Scenarios. Huang, F., Wen, W.*, Zhang, G., Su, D., Huang, Y. IEEE Transactions on Instrumentation and Measurement, 2025.(IF: 5.9, JCR Q1, Citations: 4)
+
+
Fault Detection Algorithm for Gaussian Mixture Noises: An Application in Lidar/IMU Integrated Localization Systems. Yan, P., Li, Z., Huang, F., Wen, W., Hsu, L.T. NAVIGATION: Journal of the Institute of Navigation, 72(1), 2025.(IF: 3.1, JCR Q1, Citations: 6)
+
+
Safety-Quantifiable Planar-Feature-based LiDAR Localization with a Prior Map for Intelligent Vehicles in Urban Scenarios. Zhang, J., Liu, X., Wen, W.*, Hsu, L.T. IEEE Transactions on Intelligent Vehicles, 2024.(IF: 14.3, JCR Q1, Citations: 2)
+
+
A Novel Consistent-Robust SINS/GNSS/NHC Integrated Navigation Method for Autonomous Vehicles Under Intermittent GNSS Outage. Du, S., Huang, Y.*, Wen, W., Zhang, Y. IEEE Transactions on Intelligent Vehicles, 2024.(IF: 14.3, JCR Q1, Citations: 13)
+
+
Tightly-coupled Visual/Inertial/Map Integration with Observability Analysis for Reliable Localization of Intelligent Vehicles. Zheng, X., Wen, W.*, Hsu, L.T. IEEE Transactions on Intelligent Vehicles, 2024.(IF: 14.3, JCR Q1, Citations: 3)
+
+
Integration of Vehicle Dynamic Model and System Identification Model for Extending the Navigation Service Under Sensor Failures. Yan, P., Wen, W.*, Hsu, L.T. IEEE Transactions on Intelligent Vehicles, 2023.(IF: 14.3, JCR Q1, Citations: 11)
+
+
Dynamic Object-Aware LiDAR Odometry Aided by Joint Weightings Estimation in Urban Areas. Huang, F., Wen, W., Zhang, J.*, Wang, C., Hsu, L.T. IEEE Transactions on Intelligent Vehicles, 2023.(IF: 14.3, JCR Q1, Citations: 9)
+
+
ECMD: An Event-Centric Multisensory Driving Dataset for SLAM. Chen, P., Guan, W., Huang, F., Zhong, Y., Wen, W., Hsu, L.T., Lu, P.* IEEE Transactions on Intelligent Vehicles, 2023.(IF: 14.3, JCR Q1, Citations: 31)
+
+
An Improved Inertial Preintegration Model in Factor Graph Optimization for High Accuracy Positioning of Intelligent Vehicles. Zhang, L., Wen, W.*, Zhang, T., Hsu, L.T. IEEE Transactions on Intelligent Vehicles, 2023.(IF: 14.3, JCR Q1, Citations: 16)
+
+
UrbanLoco: A Full Sensor Suite Dataset for Mapping and Localization in Urban Scenes. Wen, W., Zhou, Y., Zhang, G., Fahandezh-Saadi, S., Bai, X., Zhan, W., Tomizuka, M., Hsu, L.T. IEEE ICRA 2020, 2310-2316.(Citations: 184)
+
+
UrbanNav: An Open-sourced Multisensory Dataset for Benchmarking Positioning Algorithms Designed for Urban Areas. Hsu, L.T., Kubo, N., Wen, W., Chen, W., Liu, Z., Suzuki, T., Meguro, J. ION GNSS+ 2021.(Citations: 149)
+
+{% include section.html %}
+
+## Acknowledgement and Collaborators
+
+
+This research is supported by government and industry partners, including the Hong Kong Polytechnic University, Guangdong Basic and Applied Basic Research Foundation, Hong Kong Smart Traffic Fund, Innovation and Technology Fund, Huawei Technologies, Meituan, Tencent, and iDriverplus. We also collaborate closely with the Mechanical Systems Control Lab at the University of California, Berkeley, and the Chemnitz University of Technology in Germany.
+
+Teaching is one of the most important parts of our academic mission. We are passionate about inspiring young students to explore the frontiers of aerospace engineering, AI, and autonomous systems.
+
Artificial Intelligence in Unmanned Autonomous Systems
+
Undergraduate course · PolyU AAE
+
Covers AI fundamentals for autonomous drones and ground robots, including perception, planning, and decision-making using deep learning and reinforcement learning.
GNSS positioning (SPP, DGNSS, RTK), visual navigation, state estimation using Kalman filtering and factor graph optimization. Includes video lectures and hands-on tutorials.
As Associate Programme Leader, drafted MSc in Low-altitude Economy proposal to meet emerging industry needs in drone technology and urban air mobility.
+
+
+
+
💻
+
GitHub-based Learning Pedagogy
+
Pioneered GitHub-based collaborative learning with 50+ code examples; adopted by Wuhan University, Beihang University, and UC Berkeley.
+
+
+
+
🤖
+
Hands-on Project-Based Learning
+
ROS car projects, drone programming workshops (PX4/ArduPilot), MATLAB/Python demonstrations, and deep learning frameworks integration.
-Our lab is made up of a highly engaged and collaborative team of researchers. We recognize that diverse teams do better research. We foster an environment where team members are treated equally, and where we respect and admire our differences. The team includes postdocs, students at all levels, staff, and our lab mascots.
+Our lab is made up of a highly engaged and collaborative team of researchers. We recognize that diverse teams do better research. We foster an environment where team members are treated equally, and where we respect and admire our differences. The team includes postdocs, students at all levels, staff, and our lab mascots.
+---
+
+
+{% assign pi_members = site.members | where: "role", "pi" %}
+{% assign postdoc_members = site.members | where: "role", "postdoc" %}
+{% assign phd_members = site.members | where: "role", "phd" %}
+{% assign ms_members = site.members | where: "role", "ms" %}
+{% assign phd_ms_count = phd_members.size | plus: ms_members.size %}
+{% assign ra_members = site.members | where: "role", "ra" %}
+{% assign under_members = site.members | where: "role", "under" %}
+{% assign visiting_members = site.members | where: "role", "visiting" %}
+{% assign alumni_members = site.members | where: "role", "alumni" %}
+
+
Faculty / Principal Investigator ({{ pi_members.size }})
+Dr. Weisong Wen is an Assistant Professor at the Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, and the Director of the Trustworthy AI and Autonomous Systems Laboratory (TAS Lab). He is also a member of IEEE and the Institute of Navigation (ION). Dr. Wen aims to build algorithm foundations for embodied AI that enable trustworthy perception, navigation, and control of autonomous systems. In particular, he aims to develop practical embodied AI-driven autonomous systems (drones, intelligent vehicles, and humanoid robots) with end-to-end learning and safety certification capabilities, enabling them to perceive, reason, and interact with the physical world safely and reliably for the future society.
+
+
+Dr. Wen received a BEng degree in Mechanical Engineering from Beijing Information Science and Technology University (BISTU) in 2015, and a MEng degree from the China Agricultural University (CAU) in 2017. He received a PhD degree from The Hong Kong Polytechnic University (PolyU) supervised by Dr. Li-ta Hsu in 2020. He was also a visiting PhD student at the University of California, Berkeley (UC Berkeley) in 2018, supervised by Dr. Zhan and Prof. Tomizuka.
+
+
+He has published more than 62 SCI journal papers and 56 conference papers (total citations: 2,600+, h-index: 27) and has secured over HK$28M in research funding as PI. He was ranked in the World's Top 2% Most-cited Scientists by Stanford University in both 2023 and 2024. He won the Innovation Award from TechConnect 2021, the Best Presentation Award from ION in 2020, the Top Cited Paper Award from NAVIGATION (Journal of ION) in 2022, and the Faculty of Engineering Research Grant Achievement Award from PolyU in 2025. He is also the Associate Editor of IEEE Transactions on Vehicular Technology (JCR Q1, IF: 7.1).
+
-#### Faculty (Principal Investigator)
-{% include list_pi.html data="members" component="portrait_pi" filters="role == 'pi'" %}
-#### Postdoctoral Fellows
-{% include list_students.html data="members" component="portrait_students" filters="role == 'postdoc'" %}
-#### Ph.D./MPhil Students
-{% include list_students.html data="members" component="portrait_students" filters="role == 'phd'" %}
-
-{% include list_students.html data="members" component="portrait_students" filters="role == 'ms'" %}
-#### Research/Project Assistant
-{% include list_students.html data="members" component="portrait_students" filters="role == 'ra'" %}
-#### Undergraduate Students
-{% include list_students.html data="members" component="portrait_students" filters="role == 'under'" %}
-#### Visiting Scholar/Students
-{% include list_students.html data="members" component="portrait_students" filters="role == 'visiting'" %}
-#### Alumni
-{% include list_students.html data="members" component="portrait_students" filters="role == 'alumni'" %}
+
-To fulfill our mission to advance collaborative approaches and practical solutions to global poverty challenges, PolyU TAS Lab strives to foster diversity, equity, inclusion, and belonging in all we do.
+
-We strive to do so as a moral imperative and also because:
+---
-- Diversity drives richer ideas and solutions.
+#### Inclusion and Diversity
-- Equity ensures that all voices are heard and valued.
+To fulfill our mission to advance collaborative approaches and practical solutions to global challenges, PolyU TAS Lab strives to foster diversity, equity, inclusion, and belonging in all we do.
-- Inclusion results in a seat at the decision-making table.
+We strive to do so as a moral imperative and also because:
-- Belonging means that we all feel welcome and confident in our roles.
+- Diversity drives richer ideas and solutions.
+- Equity ensures that all voices are heard and valued.
+- Inclusion results in a seat at the decision-making table.
+- Belonging means that we all feel welcome and confident in our roles.
As such, TAS Lab is committed to:
-- Dedicating time and creating safe spaces for people to voice diverse perspectives in decision making, teaching, research, and in our work with community partners.
-
-- Acknowledging, working to understand, and repairing the power imbalances that have historically marginalized many voices, including in the field of international development.
+- Dedicating time and creating safe spaces for people to voice diverse perspectives in decision making, teaching, research, and in our work with community partners.
+- Acknowledging, working to understand, and repairing the power imbalances that have historically marginalized many voices, including in the field of international development.
+- Progressively becoming more diverse, equitable, and inclusive, and ultimately becoming an anti-racist organization.
-- Progressively becoming more diverse, equitable, and inclusive, and ultimately becoming an anti-racist organization.
In this way, we aim for TAS Lab staff, students, and collaborators around the world to be able to design for a more equitable world.
-
+---
#### We are grateful for the continued support we receive from:
@@ -75,7 +224,6 @@ In this way, we aim for TAS Lab staff, students, and collaborators around the wo
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style="width: 100%; height: auto; object-fit: cover; max-width: 250px; margin: 30px auto; vertical-align: middle;">
-
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style="width: 100%; height: auto; object-fit: cover; max-width: 120px; margin: 30px auto; vertical-align: middle;">
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@@ -85,9 +233,7 @@ In this way, we aim for TAS Lab staff, students, and collaborators around the wo
style="width: 100%; height: auto; object-fit: cover; max-width: 250px; margin: 30px auto; vertical-align: middle;">
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@@ -99,4 +245,4 @@ In this way, we aim for TAS Lab staff, students, and collaborators around the wo
style="width: 100%; height: auto; object-fit: cover; max-width: 120px; margin: 30px auto; vertical-align: middle;">
-