Depth-based Grasp Detection
Depth-Based Grasp Detection is a grasp detection approach that utilizes depth information from 3D sensor data as the primary modality to identify and localize feasible grasp poses for robotic manipulation.
21
Publications
1.1K
Citations
84
Authors
27
Institutions
Publications per year
2017–2026
15
Parents
21
Folding Clothes Autonomously: A Complete Pipeline
Andreas Doumanoglou, Jan Stria, Georgia Peleka et al. · IEEE Transactions on Robotics · 2016 · 125 citations
Grasping with application to an autonomous checkout robot
Ellen Klingbeil, Deepak Rao, Blake Carpenter et al. · 2011 · 92 citations
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Imperial College London
London, United Kingdom
2 h-index
3 publications
225 citations

Harbin Institute of Technology
Harbin, China
2 h-index
5 publications
356 citations
Northwest Institute of Mechanical and Electrical Engineering
Xianyang, China
1 h-index
1 publications
17 citations

Beihang University
Beijing, China
1 h-index
3 publications
60 citations
Universitat Politècnica de Catalunya
Barcelona, Spain
1 h-index
4 publications
524 citations
Consejo Superior de Investigaciones Científicas
Madrid, Spain
1 h-index
4 publications
524 citations
Stanford University
Stanford, United States
1 h-index
6 publications
552 citations
Beijing Academy of Artificial Intelligence
Beijing, China
1 h-index
2 publications
168 citations
1–8 of 27
Repository · 4 publications · 237 citations
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1 publications · 46 citations
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Conference · 1 publications · 94 citations
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1 publications · 84 citations
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1 publications · 30 citations
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