MR.CAP: Multi-robot Joint Control and Planning for Object Transport

Overview

With the recent influx in demand for multi-robot systems throughout industry and academia, there is an increasing need for faster, robust, and generalizable path planning algorithms. Similarly, given the inherent connection between control algorithms and multi-robot path planners, there is in turn an increased demand for fast, efficient, and robust controllers. We propose a scalable joint path planning and control algorithm for multi-robot systems with constrained behaviours based on factor graph optimization. We demonstrate our algorithm on a series of hardware and simulated experiments. Our algorithm is consistently able to recover from disturbances and avoid obstacles while outperforming state-of-the-art methods in optimization time, path deviation, and inter-robot errors. The code is open source.

Paper Code

Video

Results

Obstacle Scalability — Results from scalability experiments. Obstacle scalability experiment highlights how with an increase in environment complexity, our approach is able to scale constantly, and outperform comparable approaches by a significant margin. In robot scalability, we are also consistently able to outperform the state of the art approaches.

Robot Scalability — Results from scalability experiments. Obstacle scalability experiment highlights how with an increase in environment complexity, our approach is able to scale constantly, and outperform comparable approaches by a significant margin. In robot scalability, we are also consistently able to outperform the state of the art approaches.

Citation

@ARTICLE{10380779,
  author={Jaafar, Hussein Ali and Kao, Cheng-Hao and Saeedi, Sajad},
  journal={IEEE Control Systems Letters}, 
  title={MR.CAP: Multi-Robot Joint Control and Planning for Object Transport}, 
  year={2024},
  volume={},
  number={},
  pages={1-1},
  doi={10.1109/LCSYS.2024.3349989}}

Appendix

See the following figures for more details on the algorithm such as Pareto Frontiers and optimization time comparisons.