Learning-based Force Control
Learning-Based Force Control is a force control paradigm that employs data-driven learning algorithms to adaptively regulate contact forces by generalizing from experience, distinguishing it from model-based or fixed-gain control approaches through its reliance on learned representations of system dynamics and environmental interactions.
61
Publications
2.6K
Citations
172
Authors
78
Institutions
Publications per year
2017–2026
22
Parents
61
An overview of robot force control
Ahmad Hemami · Robotica · 1997 · 318 citations
Engineering, Mechanical Engineering, Robotics Engineering +17
1–5 of 61
172
4
h-index
National Institute of Advanced Industrial Science and Technology, Japan
3 publications · 203 citations
3
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National Institute of Advanced Industrial Science and Technology, Japan
3 publications · 203 citations
3
h-index
2
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Advanced Telecommunications Research Institute International, Japan
2 publications · 51 citations
2
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1–5 of 172
78

National Institute of Advanced Industrial Science and Technology
Tsukuba, Japan
3 h-index
4 publications
354 citations
The University of Osaka
Osaka, Japan
3 h-index
12 publications
812 citations

University of Genoa
Genoa, Italy
3 h-index
5 publications
137 citations

South China University of Technology
Guangzhou, China
2 h-index
6 publications
184 citations
Bristol Robotics Laboratory
Bristol, United Kingdom
2 h-index
3 publications
77 citations

Fukuoka Institute of Technology
Fukuoka, Japan
2 h-index
3 publications
52 citations
Technical University of Munich
Munich, Germany
2 h-index
4 publications
440 citations

Italian Institute of Technology
Genoa, Italy
2 h-index
4 publications
378 citations
1–8 of 78
3 publications · 226 citations
3
h-index
2 publications · 57 citations
2
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2 publications · 429 citations
2
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2 publications · 48 citations
2
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1 publications · 28 citations
2
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1–5