Enhancing PIBT via Multi-Action Operations
Yukhnevich, Egor, Andreychuk, Anton
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Nov-14-2025
- Country:
- Asia > Russia (0.04)
- Europe > Russia
- Central Federal District > Moscow Oblast > Moscow (0.04)
- Genre:
- Research Report > New Finding (0.68)
- Technology: