Robotics· 1996
Probabilistic roadmaps for path planning in high-dimensional configuration spaces
On the reading lists
- #124 in the Top 500 (2026 edition)
- #5 in Robotics (2026 edition)
Why it matters
Established PRM, making sampling-based planning practical in high-dimensional configuration spaces.
Condensed from the expert lists' notes.
Reading it
Difficulty: Intermediate
Read this first: configuration spaces; graph search.
The record
Editor's notes
- Readability check: pass: Sampling-based motion planning, still standard. (AI draft (Claude), not yet reviewed, 2026-10-29)
Data sources
Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.