Learning From Teleoperation
Learning From Teleoperation is a methodological framework in Human-Robot Interaction Learning that enables robots to acquire task-specific behaviors by extracting and generalizing control policies from human-operated teleoperated demonstrations.
84
Publications
4.4K
Citations
290
Authors
95
Institutions
Publications per year
2017–2026
48
84
Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
Tony Z. Zhao, Vikas Kumar, Sergey Levine et al. · 2023 · 448 citations · Full text
Recognizing teleoperated manipulations
Polly K. Pook, D.H. Ballard · 2002 · 105 citations
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University of California, Berkeley
Berkeley, United States
6 h-index
14 publications
5K citations
Stanford University
Stanford, United States
4 h-index
11 publications
1.2K citations
Idiap Research Institute
Martigny-Combe, Switzerland
4 h-index
6 publications
131 citations
Technical University of Munich
Munich, Germany
3 h-index
8 publications
255 citations
Georgia Institute of Technology
Atlanta, United States
3 h-index
8 publications
258 citations
Tsinghua University
Beijing, China
3 h-index
8 publications
468 citations

DEVCOM Army Research Laboratory
Adelphi, United States
3 h-index
4 publications
204 citations

Vanderbilt University
Nashville, United States
3 h-index
6 publications
251 citations
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8 publications · 601 citations
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Repository · 5 publications · 146 citations
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2 publications · 126 citations
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Repository · 1 publications · 12 citations
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1 publications · 21 citations
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