Sampling-based Path Refinement
Sampling-Based Path Refinement is a path smoothing method that iteratively improves the feasibility and optimality of a preliminary robotic trajectory by generating and evaluating additional configuration-space samples to locally refine path segments while preserving global connectivity.
9
Publications
1.7K
Citations
32
Authors
13
Institutions
Publications per year
2017–2026
5
Parents
9
CHOMP: Gradient optimization techniques for efficient motion planning
Nathan Ratliff, Matt Zucker, J. Andrew Bagnell et al. · 2009 · 986 citations · Full text
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Hong Kong University of Science and Technology, Hong Kong SAR China
1 publications · 144 citations
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1–5 of 32
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Shanghai Jiao Tong University
Shanghai, China
1 h-index
5 publications
610 citations

The University of Sydney
Sydney, Australia
1 h-index
1 publications
299 citations
Korea Post
Seoul, South Korea
1 h-index
3 publications
33 citations
Hangzhou Dianzi University
Hangzhou, China
1 h-index
5 publications
200 citations

Chinese Academy of Sciences
Beijing, China
1 h-index
1 publications
38 citations
Carnegie Mellon University
Pittsburgh, United States
1 h-index
3 publications
3K citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
1 h-index
3 publications
432 citations
Pohang University of Science and Technology
Pohang, South Korea
1 h-index
3 publications
33 citations
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Repository · 1 publications · 13 citations
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1 publications · 40 citations
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1 publications · 15 citations
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1 publications · 11 citations
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1 publications · 122 citations
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