This paper proposes a novel framework to handle a multi-agent path finding problem under a limited communication range constraint, where all agents must have a connected communication channel to the rest of the team. Many existing approaches to multi-agent path finding (e.g., leader-follower platooning) overcome computational challenges of planning in this domain by planning one agent at a time in a fixed order. However, fixed leader-follower approaches can become stuck during planning, limiting their practical utility in dense-clutter environments. To overcome this limitation, we develop dynamic leading multi-agent path finding, which allows for dynamic reselection of the leading agent during path planning whenever progress cannot be made. The experiments show the efficiency of our framework, which can handle up to 25 agents with more than 90% success-rate across five environment types where baselines routinely fail.

本文针对多智能体路径规划在有限通信范围下的挑战提出了一种新框架，解决了现有固定领导者-跟随者方法在密集环境中因规划阻滞而导致的局限性。通过动态重新选择领先智能体，本研究在路径规划过程中能够有效维持团队的通信连接，实现了高达90%以上的成功率，能够处理多达25个智能体的复杂任务。

在有限通信范围约束下的多智能体路径规划通过动态领先