Velocity Obstacle for Polytopic Collision Avoidance for Distributed Multi-Robot Systems

被引:18
作者
Huang, Jihao [1 ]
Zeng, Jun [2 ]
Chi, Xuemin [1 ]
Sreenath, Koushil [2 ]
Liu, Zhitao [1 ]
Su, Hongye [1 ]
机构
[1] Zhejiang Univ, Inst Cyber Syst & Control, State Key Lab Ind Control Technol, Hangzhou 310027, Peoples R China
[2] Univ Calif Berkeley, Dept Mech Engn, Hybrid Robot Grp, Berkeley, CA 94709 USA
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Collision avoidance; Robot kinematics; Navigation; Multi-robot systems; Shape; Robot sensing systems; Real-time systems; Distributed robot systems; collision avoidance; Index Terms; multi-robot systems;
D O I
10.1109/LRA.2023.3269295
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
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.
引用
收藏
页码:3502 / 3509
页数:8
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