Safe Robot Learning
Safe Robot Learning is a subfield of robot learning that focuses on ensuring the learning process and resulting behaviors of robots adhere to safety constraints to prevent harm to humans, the environment, or the robot itself during training and deployment.
125
Publications
6.6K
Citations
439
Authors
124
Institutions
Publications per year
2017–2026
103
Parents
125
Richard Cheng, Gábor Orosz, Richard M. Murray et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 2019 · 533 citations · Full text
Reachability-based safe learning with Gaussian processes
Anayo K. Akametalu, Jaime F. Fisac, Jeremy Gillula et al. · 2014 · 262 citations
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439
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124
Stanford University
Stanford, United States
7 h-index
13 publications
864 citations
University of California, Berkeley
Berkeley, United States
7 h-index
24 publications
2.6K citations
Massachusetts Institute of Technology
Cambridge, United States
5 h-index
16 publications
1.5K citations
The University of Texas at Austin
Austin, United States
5 h-index
14 publications
342 citations
University of Michigan
Ann Arbor, United States
4 h-index
7 publications
631 citations
Tsinghua University
Beijing, China
4 h-index
12 publications
562 citations
Google (United States)
Mountain View, United States
4 h-index
10 publications
583 citations
Max Planck Society
Munich, Germany
4 h-index
4 publications
108 citations
1–8 of 124
Repository · 25 publications · 698 citations
16
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10 publications · 684 citations
10
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4 publications · 315 citations
4
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Conference · 3 publications · 568 citations
3
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Repository · 2 publications · 71 citations
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