Enhancing PIBT via Multi-Action Operations

TL;DR

This paper improves the PIBT MAPF solver by adding multi-action capabilities, enabling better handling of orientation and rotation actions, and achieves state-of-the-art results in online large-scale MAPF scenarios.

Contribution

The paper introduces multi-action operations to PIBT, enhancing its ability to manage orientation and rotation, and combines it with graph-guidance and large neighborhood search for superior performance.

Findings

Enhanced PIBT with multi-action operations improves handling of rotation actions.

Combined approach achieves state-of-the-art performance in online LMAPF-T.

Maintains PIBT's efficiency while expanding its capabilities.

Abstract

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.