Enhancing PIBT via Multi-Action Operations
This work addresses a specific bottleneck in MAPF for applications requiring efficient path planning with orientation constraints, representing an incremental improvement over existing methods.
The paper tackles the limitation of the PIBT solver in Multi-Agent Path Finding (MAPF) scenarios with orientation and rotation actions by enhancing it with multi-action operations, achieving state-of-the-art performance in the online LMAPF-T setting.
PIBT is a rule-based Multi-Agent Path Finding (MAPF) solver, widely used as a low-level planner or action sampler in many state-of-the-art approaches. Its primary advantage lies in its exceptional speed, enabling action selection for thousands of agents within milliseconds by considering only the immediate next timestep. However, this short-horizon design leads to poor performance in scenarios where agents have orientation and must perform time-consuming rotation actions. In this work, we present an enhanced version of PIBT that addresses this limitation by incorporating multi-action operations. We detail the modifications introduced to improve PIBT's performance while preserving its hallmark efficiency. Furthermore, we demonstrate how our method, when combined with graph-guidance technique and large neighborhood search optimization, achieves state-of-the-art performance in the online LMAPF-T setting.