LaCAM: Search-Based Algorithm for Quick Multi-Agent Pathfinding

Authors

  • Keisuke Okumura Tokyo Institute of Technology

DOI:

https://doi.org/10.1609/aaai.v37i10.26377

Keywords:

MAS: Multiagent Planning, ROB: Motion and Path Planning, ROB: Multi-Robot Systems, PRS: Deterministic Planning, SO: Heuristic Search

Abstract

We propose a novel complete algorithm for multi-agent pathfinding (MAPF) called lazy constraints addition search for MAPF (LaCAM). MAPF is a problem of finding collision-free paths for multiple agents on graphs and is the foundation of multi-robot coordination. LaCAM uses a two-level search to find solutions quickly, even with hundreds of agents or more. At the low-level, it searches constraints about agents' locations. At the high-level, it searches a sequence of all agents' locations, following the constraints specified by the low-level. Our exhaustive experiments reveal that LaCAM is comparable to or outperforms state-of-the-art sub-optimal MAPF algorithms in a variety of scenarios, regarding success rate, planning time, and solution quality of sum-of-costs.

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Published

2023-06-26

How to Cite

Okumura, K. (2023). LaCAM: Search-Based Algorithm for Quick Multi-Agent Pathfinding. Proceedings of the AAAI Conference on Artificial Intelligence, 37(10), 11655-11662. https://doi.org/10.1609/aaai.v37i10.26377

Issue

Section

AAAI Technical Track on Multiagent Systems