@article{Sturtevant_Buro_2021, title={Improving Collaborative Pathfinding Using Map Abstraction}, volume={2}, url={https://ojs.aaai.org/index.php/AIIDE/article/view/18750}, DOI={10.1609/aiide.v2i1.18750}, abstractNote={<p>In this paper we combine recent pathfinding research on spatial abstractions, partial refinement, and space-time reserva- tions to construct new collaborative pathfinding algorithms. We first present an enhanced version of WHCA* and then show how the ideas from WHCA* can be combined with PRA* to form CPRA*. These algorithms are shown to effectively plan trajectories for many objects simultaneously while avoiding collisions, as the original WHCA* does. These new algorithms are not only faster than WHCA* but also use less memory.</p>}, number={1}, journal={Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment}, author={Sturtevant, Nathan and Buro, Michael}, year={2021}, month={Sep.}, pages={80-85} }