LaCAM: Search-Based Algorithm for Quick Multi-Agent Pathfinding
Abstract
We propose a novel complete algorithm for multi-agent pathfinding (MAPF) called lazy constraints addition search for MAPF (LaCAM). MAPF is a problem of finding collision-free paths for multiple agents on graphs and is the foundation of multi-robot coordination. LaCAM uses a two-level search to find solutions quickly, even with hundreds of agents or more. At the low-level, it searches constraints about agents' locations. At the high-level, it searches a sequence of all agents' locations, following the constraints specified by the low-level. Our exhaustive experiments reveal that LaCAM is comparable to or outperforms state-of-the-art sub-optimal MAPF algorithms in a variety of scenarios, regarding success rate, planning time, and solution quality of sum-of-costs.
Cite
Text
Okumura. "LaCAM: Search-Based Algorithm for Quick Multi-Agent Pathfinding." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I10.26377Markdown
[Okumura. "LaCAM: Search-Based Algorithm for Quick Multi-Agent Pathfinding." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/okumura2023aaai-lacam/) doi:10.1609/AAAI.V37I10.26377BibTeX
@inproceedings{okumura2023aaai-lacam,
title = {{LaCAM: Search-Based Algorithm for Quick Multi-Agent Pathfinding}},
author = {Okumura, Keisuke},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2023},
pages = {11655-11662},
doi = {10.1609/AAAI.V37I10.26377},
url = {https://mlanthology.org/aaai/2023/okumura2023aaai-lacam/}
}