In this paper, we solve the classical Multi-agent Pathfinding (MAPF) problem. Existing approaches struggle to solve dense MAPF instances. In this paper, we propose a Corridor Generating Algorithm for MAPF, namely CGA-MAPF. In CGA-MAPF, the agents build \emph{corridors}, a set of connected vertices, from current locations towards agents' goals and evacuate other agents out of the corridors to avoid collisions and deadlocks. The proposed algorithm has a reachability property, i.e. every agent is guaranteed to reach its goal location at some point. In the experimental section, we demonstrate that CGA-MAPF outperforms baseline algorithms in terms of success rate across diverse MAPF benchmark grids, achieving state-of-the-art performance.

翻译：本文研究了经典的多智能体路径规划问题。现有方法难以解决密集的MAPF实例。本文提出了一种用于MAPF的走廊生成算法，即CGA-MAPF。在CGA-MAPF中，智能体从当前位置向目标位置构建由连通顶点集合构成的\emph{走廊}，并将其他智能体疏散出走廊以避免碰撞和死锁。所提算法具有可达性保证，即每个智能体都能在某个时刻到达其目标位置。实验部分表明，在多种MAPF基准网格上，CGA-MAPF在成功率方面优于基线算法，实现了最先进的性能。