Enhancing PIBT via Multi-Action Operations
About
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.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Multi-Agent Task Scheduling | Room |A| = 200 (test) | Throughput1.26e+4 | 4 | |
| Multi-Agent Task Scheduling | Maze |A| = 400 (test) | Throughput2.01e+3 | 4 | |
| Task Scheduling | Warehouse Room map | Throughput1.88e+4 | 4 |