Multi-Agent Path Finding (MAPF), which involves finding collision-free paths
for multiple robots, is crucial in various applications. Lifelong MAPF, where
targets are reassigned to agents as soon as they complete their initial
objectives, offers a more accurate approximation of real-world warehouse
planning. In this paper, we present a novel mechanism named Caching-Augmented
Lifelong MAPF (CAL-MAPF), designed to improve the performance of Lifelong MAPF.
We have developed a new map grid type called cache for temporary item storage
and replacement and designed a lock mechanism for it to improve the stability
of the planning solution. This cache mechanism was evaluated using various
cache replacement policies and a spectrum of input task distributions. We
identified three main factors significantly impacting CAL-MAPF performance
through experimentation: suitable input task distribution, high cache hit rate,
and smooth traffic. Overall, CAL-MAPF has demonstrated potential for
performance improvements in certain task distributions, maps and agent
configurations.

本文介绍了一种名为 Caching-Augmented Lifelong MAPF（CAL-MAPF）的新机制，用于改善 Lifelong MAPF 的性能，并通过实验证明了在某些任务分布、地图和代理配置下，CAL-MAPF 具备提升性能的潜力。