dynamic-obstacle-avoidance

[RA-L'25] A Simple LiDAR-centric End-to-end Navigation Framework in Dynamic Environments

OmniRisk: omnidirectional trajectory-risk learning for agile quadrotor dynamic avoidance. One forward pass scores every maneuver onboard; real-world evasion at up to 15 m/s.

A safe interval motion planning framework for quadrotors with dynamic moving obstacles.

V550 Ackermann autonomous navigation with TD3, ROS 2 Humble Nav2, Gazebo, MPPI, Hybrid-A*, and dynamic warehouse obstacle avoidance.

A hierarchical reinforcement learning (HRL) framework that lets a biped with no hip or ankle roll walk to a goal while avoiding both static and dynamic obstacles. Navigation and gait are learned as two coupled Soft Actor–Critic (SAC) policies trained jointly in PyBullet.

Reproducible non-LLM adaptive CBF-MPC baselines for dynamic obstacle prediction and rule-based gamma tuning.

Model Predictive Control Tracker for TurtleBot

Reproducible MPC-ED and MPC-CBF baselines for dynamic obstacle avoidance with gamma sweeps and result figures.

Block D closest-paper language-tuned MPC-CBF baselines for dynamic obstacle safety