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Enhancing PIBT via Multi-Action Operations

Published: November 12, 2025 | arXiv ID: 2511.09193v2

By: Egor Yukhnevich, Anton Andreychuk

Potential Business Impact:

Helps robots move faster and avoid bumping.

Business Areas:
Artificial Intelligence Artificial Intelligence, Data and Analytics, Science and Engineering, Software

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.

Country of Origin
🇷🇺 Russian Federation

Page Count
16 pages

Category
Computer Science:
Multiagent Systems