Multi-Agent Corridor Reasoning for Multi-Agent Path Finding

Abstract The Multi-Agent Path Finding (MAPF) problem is a computationally challenging task that involves coordinating collision-free trajectories for multiple cooperative agents. Although existing methods address corridor symmetry, where agents encounter repeated bidirectional conflicts in constrained environments, they typically focus exclusively on pairwise agent interactions. Our observations reveal that such pairwise symmetry frequently arises when multiple agents traverse shared corridors, necessitating repeated applications of the corridor reasoning technology over extended durations. To overcome this limitation, we propose a multi-agent corridor reasoning (MAC) technology capable of resolving group-level corridor symmetry in a single optimization step. Our theoretical analysis demonstrates that this technology preserves the completeness and optimality guarantees of Conflict-Based Search (CBS). By integrating MAC technology with CBSH-RTC, we developed CBSH-MACRT, which significantly outperforms state-of-the-art algorithms (CBSH-RTC and CBSH with mutex propagation) on standardized MAPF benchmarks, improving success rates by 8–40% and cutting runtimes by 14–67%.