arXiv:2505.10387cs.MAcs.AI2025-05被引 2

大尺寸智能体路径规划难题被证明无法快速求解

Multi-Agent Path Finding For Large Agents Is Intractable

  • 将传统路径规划扩展至考虑实体大小,引入新冲突类型
  • 首次证明大智能体路径规划问题为NP难,无法多项式求解
  • 通过3SAT问题归约构建实例,验证可满足性与路径存在性等价

多智能体路径规划(MAPF)旨在寻找一组图上的路径,使智能体同步沿路径移动时避免冲突。在主流的经典MAPF模型中,忽略智能体大小,仅考虑同一时间占据同一顶点或使用同一条边的冲突。但在机器人等实际应用中,考虑智能体尺寸至关重要,以确保方案可安全执行。引入大智能体后,新增一种冲突:当一个智能体沿边移动时,其身体与另一智能体(即使静止于不同顶点)发生重叠。此前未明确此类冲突使问题难度提升多少。已知经典MAPF在无向图上可多项式求解,但尚未有完整多项式算法解决大智能体情况。本文首次证明该问题为NP-hard,若P≠NP,就不存在多项式时间算法。证明基于将经典的3SAT问题(已知NP完全)归约到该路径规划问题:对任意3SAT公式,可构造特定图、起点与终点,使得原公式可满足当且仅当路径规划实例有解。

原文摘要 · Abstract (English)

The multi-agent path finding (MAPF) problem asks to find a set of paths on a graph such that when synchronously following these paths the agents never encounter a conflict. In the most widespread MAPF formulation, the so-called Classical MAPF, the agents sizes are neglected and two types of conflicts are considered: occupying the same vertex or using the same edge at the same time step. Meanwhile in numerous practical applications, e.g. in robotics, taking into account the agents' sizes is vital to ensure that the MAPF solutions can be safely executed. Introducing large agents yields an additional type of conflict arising when one agent follows an edge and its body overlaps with the body of another agent that is actually not using this same edge (e.g. staying still at some distinct vertex of the graph). Until now it was not clear how harder the problem gets when such conflicts are to be considered while planning. Specifically, it was known that Classical MAPF problem on an undirected graph can be solved in polynomial time, however no complete polynomial-time algorithm was presented to solve MAPF with large agents. In this paper we, for the first time, establish that the latter problem is NP-hard and, thus, if P!=NP no polynomial algorithm for it can, unfortunately, be presented. Our proof is based on the prevalent in the field technique of reducing the seminal 3SAT problem (which is known to be an NP-complete problem) to the problem at hand. In particular, for an arbitrary 3SAT formula we procedurally construct a dedicated graph with specific start and goal vertices and show that the given 3SAT formula is satisfiable iff the corresponding path finding instance has a solution.

路径规划NP难多智能体

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