Traffic Flow Optimisation for Lifelong Multi-Agent Path Finding (Extended Abstract)

Zhe Chen, Daniel Harabor, Jiaoyang Li, Peter J. Stuckey

Abstract: Multi-Agent Path Finding (MAPF) is a fundamental problem in robotics that asks us to compute collision-free paths for a team of agents, all moving across a shared map. Existing scalable approaches struggle as the number of agents grows, as they typically plan free-flow optimal paths, which creates congestion. To tackle this issue, we propose a new approach for MAPF where agents are guided to their destination by following congestion-avoiding paths. Empirically, we report large improvements in overall throughput for lifelong MAPF while coordinating more than ten thousand agents.