2011/09/14 by Alexander Shkolnik, Russ Tedrake, Shkolnik, Alexander +1 · 1 citation
Computer Science · #FOS: Computer and information sciences #Formal Methods in Verification #Machine Learning and Algorithms #Natural Language Processing Techniques #Robotics (cs.RO)
paper · pdf · doi:10.48550/arxiv.1109.3145
openalex publication_date 2011/09/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A simple sample-based planning method is presented which approximates connected regions of free space with volumes in Configuration space instead of points. The algorithm produces very sparse trees compared to point-based planning approaches, yet it maintains probabilistic completeness guarantees. The planner is shown to improve performance on a variety of planning problems, by focusing sampling on more challenging regions of a planning problem, including collision boundary areas such as narrow passages.