Library for large-scale coverage control using robot swarms
Project description
See full documentation at https://KumarRobotics.github.io/CoverageControl/
Introduction
Coverage control is the problem of navigating a robot swarm to collaboratively monitor features or a phenomenon of interest not known a priori.
The library provides a simulation environment, algorithms, and GNN-based architectures for the coverage control problem.
Key features:
- The core library is written in
C++
andCUDA
to handle large-scale simulations - There are
python
bindings that interface with the core library - Several Centroidal Voronoi Tessellation (CVT)-based algorithms (aka Lloyd's algorithms)
- Learnable Perception-Action-Communication (LPAC) architecture for the coverage control problem is implemented in
PyTorch
andPyTorch Geometric
Getting Started
The library is available as a pip
package. To install the package, run the following command:
pip install coverage_control
See Installation for more details on installation.
See Quick Start guide for a quick introduction to the library.
Citation
@article{agarwal2024lpac,
title = {LPAC: Learnable Perception-Action-Communication Loops with
Applications to Coverage Control},
author = {Saurav Agarwal and Ramya Muthukrishnan and
Walker Gosrich and Vijay Kumar and Alejandro Ribeiro},
year = {2024},
eprint = {2401.04855},
archivePrefix = {arXiv},
primaryClass = {cs.RO}
}
LPAC: Learnable Perception-Action-Communication Loops with Applications to Coverage Control.
Saurav Agarwal, Ramya Muthukrishnan, Walker Gosrich, Vijay Kumar, and Alejandro Ribeiro.
arXiv preprint arXiv:2401.04855 (2024).
Acknowledgements
- PyTorch
- PyTorch Geometric
- Eigen
- pybind11
- CGAL
- JSON for Modern C++
- CUDA Samples
- gnuplot-iostream
- hungarian-algorithm-cpp
- toml++
Support and Funding
The work was performed at the GRASP Laboratory and the Alelab, University of Pennsylvania, USA.
This work was supported in part by grants ARL DCIST CRA W911NF-17-2-0181 and ONR N00014-20-1-2822.
Contributors
- Saurav Agarwal
- Ramya Muthukrishnan
License
The library is licensed under the GPL-3.0 License. The documentation is not under the GPL-3.0 License and is licensed under the CC BY-NC-SA 4.0 License.
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