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.
翻译:我们提出一种新型的多试剂路由探测(MAPF)的完整算法,称为对MAPF(LaCAM)的懒惰限制附加搜索。MAPF是一个在图形上找到多个物剂的无碰撞路径的问题,是多机器人协调的基础。LACAM使用双层搜索来迅速找到解决方案,即使有数百个或更多的物剂。在低层,它搜索代理人所在地的限制因素。在高层,它搜索所有物剂所在地的顺序,并遵循低层规定的限制。我们详尽的实验显示,LACAM在各种情景中,在成功率、规划时间和成本总和的解决方案质量方面,都与最先进的亚最佳MAPFS算法相近或超过。