Multi-Agent Path Finding with Temporal Jump Point Search
Shuli Hu, Daniel Harabor, Graeme Gange, Peter Stuckey and Nathan Sturtevant
Abstract: 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.
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