Abstract
Any-angle path planning is an extension of traditional path-planning algorithms that aims to generate smoother and shorter paths in graphs by allowing any-angle moves between vertices, rather than being restricted by edges. Many any-angle path-planning algorithms have been proposed, such as Theta*, Block A* and Anya, but most of them are designed only for static environments, which is not applicable when dynamic obstacles are present. Time-Optimal Any-Angle Safe-Interval Path Planning (TO-AA-SIPP) was developed to fill this gap, which can find an optimal collision-free any-angle path that minimizes the traversal time. However, as indicated by its authors, TO-AA-SIPP may not be efficient enough to be used in multi-agent pathfinding (MAPF). Therefore, this paper presents a new algorithm Zeta*-SIPP to improve TO-AA-SIPP by means of 1) reducing useless search nodes that have no contribution to finding optimal solutions, and 2) introducing Field of View (FoV) instead of Line of Sight (LoS) to speed up visibility checks with static obstacles. Benchmark experiments showed that Zeta*-SIPP reduced the computation time of TO-AA-SIPP by around 70%-90% on average.
Original language | English |
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Title of host publication | Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence |
Editors | Kate Larson |
Publisher | International Joint Conferences on Artificial Intelligence (IJCAI) |
Pages | 6823-6830 |
Number of pages | 8 |
ISBN (Electronic) | 978-1-956792-04-1 |
Publication status | Published - 2024 |
Event | 33rd International Joint Conference on Artificial Intelligence - International Convention Center Jeju (ICC Jeju), Jeju Island, Korea, Republic of Duration: 3 Aug 2024 → 9 Aug 2024 Conference number: 33 https://ijcai24.org/ |
Conference
Conference | 33rd International Joint Conference on Artificial Intelligence |
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Abbreviated title | IJCAI 2024 |
Country/Territory | Korea, Republic of |
City | Jeju Island |
Period | 3/08/24 → 9/08/24 |
Internet address |
Funding
The authors would like to thank the financial support from the China Scholarship Council (CSC) No. 202106830036.Keywords
- any-angle path planning
- multi-agent path finding (MAPF)
- safe-interval path planning
- heuristic search