Velocity Obstacle for Polytopic Collision Avoidance for Distributed Multi-Robot Systems
Jihao Huang, Jun Zeng, Xuemin Chi, Koushil Sreenath, Zhitao Liu, Hongye Su
Abstract
Obstacle avoidance for multi-robot navigation with polytopic shapes is challenging. Existing works simplify the system dynamics or consider it as a convex or non-convex optimization problem with positive distance constraints between robots, which limits real-time performance and scalability. Additionally, generating collision-free behavior for polytopic-shaped robots is harder due to implicit and non-differentiable distance functions between polytopes. In this letter, we extend the concept of velocity obstacle (VO) principle for polytopic-shaped robots and propose a novel approach to construct the VO in the function of vertex coordinates and other robot's states. Compared with existing work about obstacle avoidance between polytopic-shaped robots, our approach is much more computationally efficient as the proposed approach for construction of VO between polytopes is optimization-free. Based on VO representation for polytopic shapes, we later propose a navigation approach for distributed multi-robot systems. We validate our proposed VO representation and navigation approach in multiple challenging scenarios including large-scale randomized tests, and our approach outperforms the state of art in many evaluation metrics, including completion rate, deadlock rate, and the average travel distance.
BibTeX
@inproceedings{ral2023_velocityobstacle,
title = {Velocity Obstacle for Polytopic Collision Avoidance for Distributed Multi-Robot Systems},
author = {Jihao Huang and Jun Zeng and Xuemin Chi and Koushil Sreenath and Zhitao Liu and Hongye Su},
booktitle = {RA-L 2023},
year = {2023}
}