Learning From Corrective Feedback
Learning From Corrective Feedback is a machine learning framework within human-robot interaction that enables a robot to iteratively improve its behavior by incorporating human-provided corrective signals that indicate deviations from desired actions.
29
Publications
977
Citations
100
Authors
47
Institutions
Publications per year
2017–2026
14
29
Robot trajectory learning through practice
C.G. Atkeson, Joseph McIntyre · 1986 · 158 citations
Engineering, Mechanical Engineering, Robotics Engineering +14
Learning from Physical Human Corrections, One Feature at a Time
Andrea Bajcsy, Dylan P. Losey, Marcia K. O’Malley et al. · 2018 · 74 citations · Full text
Correcting Robot Plans with Natural Language Feedback
Pratyusha Sharma, Balakumar Sundaralingam, Valts Blukis et al. · 2022 · 67 citations · Full text
1–5 of 29
100
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47
University of Chile
Santiago, Chile
3 h-index
6 publications
210 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
7 publications
125 citations

Boğaziçi University
Istanbul, Türkiye
2 h-index
4 publications
62 citations
Universität Hamburg
Hamburg, Germany
2 h-index
5 publications
82 citations
Cambridgeshire and Peterborough NHS Foundation Trust
Cambridge, United Kingdom
1 h-index
2 publications
44 citations
The University of Texas at Austin
Austin, United States
1 h-index
2 publications
28 citations
University of Wisconsin–Madison
Madison, United States
1 h-index
6 publications
90 citations
University of Cambridge
Cambridge, United Kingdom
1 h-index
5 publications
110 citations
1–8 of 47
1 publications · 115 citations
1
h-index
1 publications · 25 citations
1
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1 publications · 15 citations
1
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1 publications · 17 citations
1
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1 publications · 35 citations
1
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