Extending PiBT to support Heterogeneous Robot Fleets

Arjo Chakravarty, Michael X Grey, M. A. Viraj J. Muthugala, Mohan Rajesh Elara

Keywords: Multi-agent path finding, PIBT

TL;DR: We propose a set of extensions to winPiBT that enable it to handle multi-sized robots.

Abstract: Priority Inheritance and Backtracking (PIBT) has demonstrated significant success as a heuristic for large-scale Multi-Agent Path Finding (MAPF), but its application has been limited to scenarios where all robots move at uniform speeds. This work addresses the critical question of extending PIBT's capabilities to heterogeneous fleets, where robots may vary in size and speed. We introduce a novel collision-checking-based reservation system integrated within the WinPIBT framework and a new backtracking mechanism. Heterogeneous PIBT (HetPIBT) effectively scales to hundreds of robots of various sizes. Our findings confirm that this scheme enables the application of heterogeneous MAPF to large robot populations. To facilitate further research, we also provide a new set of heterogeneous MAPF benchmark scenarios along with a Python package for the generation of such problems and visualization tools. However, we observe that HetPIBT, similar to its homogeneous counterpart, can yield suboptimal solutions. We provide an open source implementation of the algorithm in Rust.

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Submission Number: 13