Distance-Constrained Unlabeled Multi-Agent Pathfinding
Abstract
We study a graph pathfinding problem Distance- Independent Unlabeled Multi-Agent Pathfinding, finding a set of collision-free paths between two sets where agents must stay at pairwise distance at least at all times. This additional constraint, generalizing collision modeling for classical MAPF, targets aspects of real-world multi-agent coordination. This additional distance constraint makes feasibility (i.e., whether a solution exists) PSPACE-complete, in contrast to standard (unlabeled) MAPF, where it can be decided in polynomial time. We address the challenge via two complementary approaches: (i) reduction-based optimal algorithms with a feasibility-preserving compression procedure, and (ii) a configuration generator-based search. Despite the hardness, empirical results show that our algorithm can handle hundreds of agents in a practical timeframe.
Cite
@article{arxiv.2605.11503,
title = {Distance-Constrained Unlabeled Multi-Agent Pathfinding},
author = {Takahiro Suzuki and Yuma Tamura and Keisuke Okumura},
journal= {arXiv preprint arXiv:2605.11503},
year = {2026}
}