提出新算法解决连续环境中的多智能体路径规划问题
Multi-agent Path Finding in Continuous Environment
- 高层用冲突搜索，底层用RRT*生成平滑路径
- 在多种场景下验证，性能优于现有连续路径规划方法
- 适合需要平滑运动轨迹的机器人协同任务
本文研究连续环境下的多智能体路径规划（CE-MAPF）问题，其中智能体沿光滑曲线移动，碰撞通过空间域避让解决。提出一种新的连续环境冲突基于搜索（CE-CBS）算法，将冲突基于搜索（CBS）作为高层搜索框架，结合RRT*进行低层路径规划。在多种不同设置和实例上测试了该算法，实验结果表明，其在性能上与考虑连续性的其他MAPF算法（如连续时间MAPF）相当甚至更优。
原文摘要 · Abstract (English)
We address a variant of multi-agent path finding in continuous environment (CE-MAPF), where agents move along sets of smooth curves. Collisions between agents are resolved via avoidance in the space domain. A new Continuous Environment Conflict-Based Search (CE-CBS) algorithm is proposed in this work. CE-CBS combines conflict-based search (CBS) for the high-level search framework with RRT* for low-level path planning. The CE-CBS algorithm is tested under various settings on diverse CE-MAPF instances. Experimental results show that CE-CBS is competitive w.r.t. to other algorithms that consider continuous aspect in MAPF such as MAPF with continuous time.
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