Conflict-Based Search for Multi Agent Path Finding with Asynchronous Actions
This addresses a practical limitation in MAPF for robotics and logistics by enabling asynchronous actions, though it is incremental as it builds on existing conflict-based search methods.
The paper tackles the problem of Multi-Agent Path Finding with asynchronous actions, which avoids the unrealistic assumption of synchronized actions in prior work, and proposes CBS-AA, a method that guarantees completeness and optimality while reducing branches by up to 90% in tests.
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%.