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ChoiRbot is a ROS 2 toolbox developed within the excellence research program ERC in the project OPT4SMART. ChoiRbot provides a comprehensive set of libraries to execute complex distributed multi-robot tasks, such as model predictive control and task assignment, either in simulation or experimentally. The toolbox focuses on networks of heterogeneous robots without a central coordinator. It provides utilities for the solution of distributed optimization problems and can be also used to implement distributed feedback laws. Specifically, the package allows you to
- Encode distributed optimization and control algorithms
- Perform peer-to-peer communications among robots
- Develop planning and control schemes
- Connect with external motion capture hardware (see also our ROS 2 Vicon Bridge)
- Run experiments on your robotic fleet
- Perform realistic simulations with Gazebo and visualize data with RVIZ
ChoiRbot requires ROS 2 Dashing Diademata to be installed on your system.
It relies on
- numpy
- scipy
- recordclass
- dill
- disropt (optional, but required for several features)
Please, refer to the installation page for a more detailed installation guide.
To install the toolbox, first source your ROS 2 installation. Then create a ROS 2 workspace and, inside the src
directory, run:
git clone https://github.com/OPT4SMART/ChoiRbot.git .
Then, from the parent directory execute:
colcon build --symlink-install
If you are you using ChoiRbot in research work to be published, please cite the accompanying paper
@article{testa2021choirbot,
title={ChoiRbot: A ROS 2 toolbox for cooperative robotics},
author={Testa, Andrea and Camisa, Andrea and Notarstefano, Giuseppe},
journal={IEEE Robotics and Automation Letters},
volume={6},
number={2},
pages={2714--2720},
year={2021},
publisher={IEEE}
}
ChoiRbot is developed by Andrea Testa, Andrea Camisa and Giuseppe Notarstefano
This result is part of a project that has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 638992 - OPT4SMART).