Multi-Agent Path Finding with Temporal Jump Point Search

Autor:	Shuli Hu, Daniel D. Harabor, Graeme Gange, Peter J. Stuckey, Nathan R. Sturtevant
Rok vydání:	2022
Zdroj:	Proceedings of the International Conference on Automated Planning and Scheduling. 32:169-173
ISSN:	2334-0843 2334-0835
DOI:	10.1609/icaps.v32i1.19798
Popis:	Temporal Jump Point Search (JPST) is a recently introduced algorithm for grid-optimal pathfinding among dynamic temporal obstacles. In this work we consider JPST as a low-level planner in Multi-Agent Path Finding (MAPF). We investigate how the canonical ordering of JPST can negatively impact MAPF performance and we consider several strategies which allow us to overcome these limitations. Experiments show our new CBS/JPST approach can substantially improve on CBS/SIPP, a contemporary and leading method from the area.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a1efbcc01c60cccee133ed2e4af9dbc5 https://doi.org/10.1609/icaps.v32i1.19798 Zobrazit plný text záznamu