Conflict-Based Search for Multi Agent Path Finding with Asynchronous Actions

TL;DR

This paper introduces CBS-AA, a complete and optimal conflict-based search algorithm for multi-agent path finding with asynchronous actions, overcoming limitations of previous methods and significantly improving scalability.

Contribution

The paper presents CBS-AA, a novel conflict-based search algorithm that guarantees completeness and optimality for MAPF with asynchronous actions, addressing the incompleteness of prior approaches.

Findings

CBS-AA reduces search branches by up to 90%.

It guarantees completeness and optimality for MAPF with asynchronous actions.

Conflict resolution techniques enhance scalability.

Abstract

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%.