Multi-Agent Pathfinding with Continuous Time
This addresses the challenge of efficient pathfinding for multiple agents in continuous-time scenarios, which is incremental as it adapts existing methods like SIPP and CBS.
The paper tackles the problem of Multi-Agent Pathfinding (MAPF) by proposing a complete and provably optimal algorithm that operates in continuous time without relying on grids or uniform action durations, achieving optimal solutions as demonstrated in standard benchmarks.
Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents such that every agent reaches its goal and the agents do not collide. Most prior work on MAPF was on grids, assumed agents' actions have uniform duration, and that time is discretized into timesteps. We propose a MAPF algorithm that does not rely on these assumptions, is complete, and provides provably optimal solutions. This algorithm is based on a novel adaptation of Safe interval path planning (SIPP), a continuous time single-agent planning algorithm, and a modified version of Conflict-based search (CBS), a state of the art multi-agent pathfinding algorithm. We analyze this algorithm, discuss its pros and cons, and evaluate it experimentally on several standard benchmarks.