IO Mocap Visualization

io_mocap_visualization is a ROS 2 package designed to visualize human motion capture data. It bridges external Motion Capture (MoCap) data published on custom topics (e.g., /io_fusion/tf) to standard ROS 2 TF frames, enabling real-time or playback visualization in RViz2 using custom URDF models.

Getting Started

1. Prerequisites

• ROS 2 Distribution: Humble or newer.
• Dependencies:

sudo apt install ros-$ROS_DISTRO-robot-state-publisher \
                 ros-$ROS_DISTRO-joint-state-publisher-gui \
                 ros-$ROS_DISTRO-rviz2

2. Installation

Clone this repository into the src folder of your ROS 2 workspace:

cd ~/ros2_ws/src
git clone git@github.com:ioai-tech/io_mocap_visualization.git

3. Build the Workspace

Navigate back to the workspace root and build using colcon:

cd ~/ros2_ws
colcon build --packages-select io_mocap_visualization
source install/setup.bash

4. Launch Visualization

Start the visualization node, which initializes the robot_state_publisher, the TF relay, and RViz2:

ros2 launch io_mocap_visualization io_mocap_visualization.launch.py

5. Playback Data

To visualize motion from a recorded ROS 2 bag file containing the /io_fusion/tf topic, use the --clock flag to ensure time synchronization:

ros2 bag play <your_ros2_bag_path> --clock

System Architecture

The package functions by re-routing specific mocap data to the standard ROS 2 visualization pipeline:

Input: ROS 2 Bag sends /io_fusion/tf(tf2_msgs/msg/TFMessage).

Relay: The tf_relay node listens to /io_fusion/tf and publishes to /tf.

Model: robot_state_publisher loads the URDF and maintains the model structure.

Display: RViz2 renders the blender_human model based on the calculated transforms.