MAPFExpert
Belief-Aware Multi-Agent Path Finding under Map Uncertainty
This arXiv preprint describes MAGIC, a framework that adds online spatial belief inference to multi-agent path finding under unknown map obstacles. On standard MAPF benchmarks it reduces executed sum of costs on 96.3% of instances and scales to 800 agents. The work is relevant for warehouse robot fleets that must route around fallen pallets, spills, or other local map discrepancies without building expensive contingent plans.