2019/05/24 by Keisuke Okumura, Yasumasa Tamura, Okumura, Keisuke +3
Computer Science · Engineering · #Distributed #FOS: Computer and information sciences #Maritime Navigation and Safety #Multiagent Systems (cs.MA) #Parallel #Robotic Path Planning Algorithms #Robotics (cs.RO) #Vehicle Routing Optimization Methods #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.1905.10149
openalex publication_date 2019/05/24 · openalex created_date 2024/04/10 · openalex updated_date 2026/07/28
The problem of Multi-agent Path Finding (MAPF) consists in providing agents with efficient paths while preventing collisions. Numerous solvers have been developed so far since MAPF is critical for practical applications such as automated warehouses. The recently-proposed Priority Inheritance with Backtracking (PIBT) is a promising decoupled method that solves MAPF iteratively with flexible priorities. The method is aimed to be decentralized and has a very low computational cost, but it is shortsighted in the sense that it plans only one step ahead, thus occasionally resulting in inefficient plannings. This work proposes a generalization of PIBT, called windowed PIBT (winPIBT), that introduces a configurable time window. winPIBT allows agents to plan paths anticipating multiple steps ahead. We prove that, similarly to PIBT, all agents reach their own destinations in finite time as long as the environment is a graph with adequate properties, e.g., biconnected. Experimental results over various scenarios confirm that winPIBT mitigates livelock situations occurring in PIBT, and usually plans more efficient paths given adequate window size.