Robust Robot Learning
Robust Robot Learning is a methodological framework in safe robot learning that ensures reliable adaptation and performance of robotic systems under environmental uncertainties, model inaccuracies, and unexpected disturbances by explicitly incorporating resilience to variations and failures during the learning process.
34
Publications
1.3K
Citations
111
Authors
55
Institutions
Publications per year
2017–2026
17
Parents
34
RobotGPT: Robot Manipulation Learning From ChatGPT
Yixiang Jin, Dingzhe Li, A Yong et al. · IEEE Robotics and Automation Letters · 2024 · 90 citations
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École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
2 h-index
6 publications
1.1K citations

Delft University of Technology
Delft, The Netherlands
2 h-index
6 publications
164 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
3 publications
88 citations
Nanyang Technological University
Singapore, Singapore
2 h-index
5 publications
181 citations
Equipes Traitement de l'Information et Systèmes
Cergy-Pontoise, France
2 h-index
5 publications
117 citations
Massachusetts Institute of Technology
Cambridge, United States
2 h-index
2 publications
55 citations

University of Central Florida
Orlando, United States
2 h-index
2 publications
37 citations

Beijing University of Posts and Telecommunications
Beijing, China
1 h-index
1 publications
90 citations
1–8 of 55
3 publications · 192 citations
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1 publications · 20 citations
1
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1 publications · 49 citations
1
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1 publications · 43 citations
1
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1 publications · 50 citations
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