motion_capture_tracking

This repository is a ROS 2 package that can receive data from various motion capture systems:

VICON
Qualisys
OptiTrack
VRPN
NOKOV
FZMotion
Motion Analysis

For most systems, three different tracking modes are available:

Tracking of rigid body poses via the official software (e.g., Vicon Tracker) using unique marker arrangements.
Tracking of rigid body poses with custom frame-to-frame tracking with identical marker arrangements.
Tracking of unlabeled marker positions using custom frame-to-frame tracking.

The data is directly published via tf2 and a /poses topic that supports different QoS settings.

This package was originally developed for Crazyswarm to track up to 50 flying robots.

Building

To build from source, clone the latest version from this repository into your ROS 2 workspace and compile the package using

cd ros_ws/src
git clone --recurse-submodules https://github.com/IMRCLab/motion_capture_tracking
cd ../
colcon build

Usage

ros2 launch motion_capture_tracking launch.py

The various options can be configured in config/cfg.yaml.

Technical Background

The ROS package is a wrapper around libmotioncapture and librigidbodytracker. The former is a C++ library that provides a unified interface over different motion capture SDKs to gather pose informations of rigid bodies and/or pointclouds of unlabeled markers. The latter is a C++ library that takes the following inputs: i) a first-order dynamics model, ii) initial poses of rigid bodies, and iii) at every frame a point cloud. It outputs for every frame the best estimate of the robots' poses.

Some more information on the rigid body pose tracking is available in

@inproceedings{crazyswarm,
  author    = {James A. Preiss* and
               Wolfgang  H\"onig* and
               Gaurav S. Sukhatme and
               Nora Ayanian},
  title     = {Crazyswarm: {A} large nano-quadcopter swarm},
  booktitle = {{IEEE} International Conference on Robotics and Automation ({ICRA})},
  pages     = {3299--3304},
  publisher = {{IEEE}},
  year      = {2017},
  url       = {https://doi.org/10.1109/ICRA.2017.7989376},
  doi       = {10.1109/ICRA.2017.7989376},
  note      = {Software available at \url{https://github.com/USC-ACTLab/crazyswarm}},
}

The unlabeled marker tracking is using an optimal assignment with a min-cost max-flow formulation for each frame.

Related Work

These are current vendor-agnostic alternatives if no custom tracking is needed:

https://github.com/alvinsunyixiao/vrpn_mocap (only VRPN)
https://github.com/ros-drivers/vrpn_client_ros (only VRPN)
https://github.com/MOCAP4ROS2-Project (VRPN, Vicon, Optitrack, Qualisys, Technaid each in separate packages)

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