Pathfinding with Lazy Successor Generation
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Abstract (arXiv)
We study a pathfinding problem where only locations (i.e., vertices) are given, and edges are implicitly defined by an oracle answering the connectivity of two locations. Despite its simple structure, this problem becomes non-trivial with a massive number of locations, due to posing a huge branching factor for search algorithms. Limiting the number of successors, such as with nearest neighbors, can reduce search efforts but compromises completeness. Instead, we propose a novel LaCAS* algorithm, which does not generate successors all at once but gradually generates successors as the search progresses. This scheme is implemented with k-nearest neighbors search on a k-d tree. LaCAS* is a complete and anytime algorithm that eventually converges to the optima. Extensive evaluations demonstrate the efficacy of LaCAS*, e.g., solving complex pathfinding instances quickly, where conventional methods falter.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 37 references that are in the map. First posted on arXiv 27 Aug 2024.
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10 of 37 references.
References · 10
- 2019Multi-Agent Pathfinding: Definitions, Variants, and Benchmarkscited by 197
- 2014Informed RRT*: Optimal Sampling-based Path Planning Focused via Direct Sampling of an Admissible Ellipsoidal Heuristiccited by 50
- 2022LaCAM: Search-Based Algorithm for Quick Multi-Agent Pathfindingcited by 50
- 2014Theta*: Any-Angle Path Planning on Gridscited by 26
- 2023Improving LaCAM for Scalable Eventually Optimal Multi-Agent Pathfindingcited by 17
- 2019dRRT*: Scalable and Informed Asymptotically-Optimal Multi-Robot Motion Planningcited by 15
- 2013Finding a needle in an exponential haystack: Discrete RRT for exploration of implicit roadmaps in multi-robot motion planningcited by 11
- 2016A Unifying Formalism for Shortest Path Problems with Expensive Edge Evaluations via Lazy Best-First Search over Paths with Edge Selectorscited by 9
- 2016Densification Strategies for Anytime Motion Planning over Large Dense Roadmapscited by 1
- 2020Fast Planning Over Roadmaps via Selective Densificationcited by 1
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