{"type":"ScholarlyArticle","title":"Euclidean Pathfinding with Compressed Path Databases","authors":[{"name":"Bojie Shen","slug":"bojie-shen","given":"Bojie","family":"Shen","affiliation":"Faculty of Information Technology , Monash University , Melbourne , Australia"},{"name":"Muhammad Aamir Cheema","slug":"muhammad-aamir-cheema","given":"Muhammad Aamir","family":"Cheema","affiliation":"Faculty of Information Technology , Monash University , Melbourne , Australia"},{"name":"Daniel Harabor","slug":"daniel-harabor","given":"Daniel","family":"Harabor","affiliation":"Faculty of Information Technology , Monash University , Melbourne , Australia"},{"name":"Peter J. Stuckey","slug":"peter-j-stuckey","given":"Peter J.","family":"Stuckey","affiliation":"Faculty of Information Technology , Monash University , Melbourne , Australia"}],"abstract":"We consider optimal and anytime algorithms for the Euclidean Shortest Path Problem (ESPP) in two dimensions. Our approach leverages ideas from two recent works: Polyanya, a mesh-based ESPP planner which we use to represent and reason about the environment, and Compressed Path Databases, a speedup technique for pathfinding on grids and spatial networks, which we exploit to compute fast candidate paths. In a range of experiments and empirical comparisons we show that: (i) the auxiliary data structures required by the new method are cheap to build and store; (ii) for optimal search, the new algorithm is faster than a range of recent ESPP planners, with speedups ranging from several factors to over one order of magnitude; (iii) for anytime search, where feasible solutions are needed fast, we report even better runtimes.","doi":"10.24963/ijcai.2020/584","url":"https://ijcai.org/proceedings/2020/584","pdf":"https://ijcai.org/proceedings/2020/0584.pdf","markdown":"https://ijcai.org/proceedings/2020/584.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/584","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Robotics","track":"Main track","number":584,"pages":{"first":4229,"last":4235},"keywords":["Heuristic Search and Game Playing: Heuristic Search","Robotics: Motion and Path Planning"],"videos":[{"label":"Video","url":"https://videos.ijcai20.org/25000/file_25000.m3u8","length_sec":285,"provider":"hls"}],"references":[{"position":1,"raw":"[Botea, 2011] Adi Botea. 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