Conflict-Based Search for Multi Agent Path Finding with Asynchronous Actions
AI 摘要
提出了Conflict-Based Search with Asynchronous Actions (CBS-AA) 算法,解决了多智能体异步路径规划问题。
主要贡献
- 提出了完整且最优的CBS-AA算法
- 绕过了CCBS因连续等待时间导致的无限状态空间问题
- 开发了冲突解决技术以提高CBS-AA的可扩展性
方法论
提出了新的搜索方法CBS-AA,并在此基础上开发了冲突解决技术,并通过实验验证。
原文摘要
Multi-Agent Path Finding (MAPF) seeks collision-free paths for multiple agents from their respective start locations to their respective goal locations while minimizing path costs. Most existing MAPF algorithms rely on a common assumption of synchronized actions, where the actions of all agents start at the same time and always take a time unit, which may limit the use of MAPF planners in practice. To get rid of this assumption, Continuous-time Conflict-Based Search (CCBS) is a popular approach that can find optimal solutions for MAPF with asynchronous actions (MAPF-AA). However, CCBS has recently been identified to be incomplete due to an uncountably infinite state space created by continuous wait durations. This paper proposes a new method, Conflict-Based Search with Asynchronous Actions (CBS-AA), which bypasses this theoretical issue and can solve MAPF-AA with completeness and solution optimality guarantees. Based on CBS-AA, we also develop conflict resolution techniques to improve the scalability of CBS-AA further. Our test results show that our method can reduce the number of branches by up to 90%.