Configuration Space Sampling is a method in robotics motion planning that belongs to the class of probabilistic sampling techniques, specifically distinguished by its generation of discrete configurations within the robot's configuration space to approximate feasible paths while avoiding obstacles.
131
Publications
8.8K
Citations
352
Authors
154
Institutions
Publications per year
2017–2026
41
Publications
131
Path planning in expansive configuration spaces
David Hsu, J.-C. Latombe, R. Motwani · 2002 · 546 citations
The bridge test for sampling narrow passages with probabilistic roadmap planners
David Hsu, Tingting Jiang, John H. Reif et al. · 2004 · 358 citations
1–5 of 131
Authors
352
- NM
9
h-index
- LE
7
h-index
- DH
7
h-index
- ST
6
h-index
- OB
5
h-index
1–5 of 352
Institutions
154
Stanford University
Stanford, United States
9 h-index
22 publications
4.1K citations
Texas A&M University
College Station, United States
8 h-index
24 publications
735 citations
Rice University
Houston, United States
8 h-index
21 publications
1.5K citations
Centre National de la Recherche Scientifique
Paris, France
6 h-index
20 publications
446 citations
National University of Singapore
Singapore, Singapore
5 h-index
8 publications
1.5K citations
Laboratoire d'Analyse et d'Architecture des Systèmes
Toulouse, France
5 h-index
14 publications
336 citations
University of Massachusetts Amherst
Amherst Center, United States
5 h-index
10 publications
608 citations
Chongqing University
Chongqing, China
4 h-index
8 publications
222 citations
1–8 of 154
Venues
- The International Journal of Robotics Research
IJRR · 11 publications · 977 citations
11
h-index
- The Journal of Chemical Physics
7 publications · 1.1K citations
7
h-index
- arXiv (Cornell University)
Repository · 3 publications · 106 citations
3
h-index
- IEEE Transactions on Robotics
3 publications · 493 citations
3
h-index
- ACM Transactions on Graphics
TOG · 2 publications · 141 citations
2
h-index
1–5