运动规划
机器人
数学优化
粒子群优化
最短路径问题
路径(计算)
启发式
计算机科学
弹道
规划师
人工智能
数学
理论计算机科学
物理
图形
程序设计语言
天文
作者
Chen Zhang,Yibin Li,Lelai Zhou
出处
期刊:IEEE robotics and automation letters
日期:2022-06-30
卷期号:7 (3): 8130-8137
被引量:13
标识
DOI:10.1109/lra.2022.3187529
摘要
In an environment with limited space and dense goal configuration, the path of robot team is forced to coincide without much adjustment space, which is a challenge for multi-robot collaborative path planning. In this work, a novel Optimal Path and Timetable Planning (OPTP) method is proposed. The OPTP firstly generates the near-shortest paths for each robot by an RRT*-based planner. Then the timetables for each robot in the path-time space are created by the improved Particle Swarm Optimization (PSO) method. A heuristic bias is added to the PSO optimizer to efficiently mediate the conflict near the goal configuration. The OPTP achieves the near-shortest moving distance of the multi-robot team, as well as the near-optimal navigation makespan in face of complex obstacles, narrow channels, and dense goal configurations. The compared simulations and real-world experiments verify the effectiveness of the OPTP method.
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