Pareto Optimal Multirobot Motion Planning

• 成果类型: Article
• 署名作者: Zhao, Guoxiang; Zhu, Minghui
• 署名单位: Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2020.3025870
• 发表日期: 2021
• 页码: 3984-3999
• 关键词: planning; Collision avoidance; Robot sensing systems; Pareto optimization; Robot motion; Heuristic algorithms; multirobot coordination; Pareto optimality; robotic motion planning

摘要

This article studies a class of multirobot coordination problems where a team of robots aim to reach their goal regions with minimum time and avoid collisions with obstacles and other robots. A novel numerical algorithm is proposed to identify the Pareto optimal solutions where no robot can unilaterally reduce its traveling time without extending others'. The consistent approximation of the algorithm in the epigraphical profile sense is guaranteed using set-valued numerical analysis. Experiments on an indoor multirobot platform and computer simulations show the anytime property of the proposed algorithm, i.e., it is able to quickly return a feasible control policy that safely steers the robots to their goal regions and it keeps improving policy optimality if more time is given.