Robust Multi-Agent Pathfinding with Continuous Time

Abstract

Multi-Agent Pathfinding (MAPF) is the problem of finding plans for multiple agents such that every agent moves from its start location to its goal location without collisions. If unexpected events delay some agents during plan execution, it may not be possible for the agents to continue following their plans without causing any collision. We define and solve a T-robust MAPF problem that seeks plans that can be followed even if some delays occur, under the generalized MAPFR setting with continuous time notions. The proposed approach is complete and provides provably optimal solutions. We also develop an exact method for collision detection among agents that can be delayed. We experimentally evaluate our proposed approach in terms of efficiency and plan cost.