Reinforcement Learning Visual Servoing
Reinforcement Learning Visual Servoing is a visual servoing method that employs reinforcement learning to autonomously learn control policies mapping visual feedback to robot actions, distinguishing itself from classical and model-based visual servoing approaches by optimizing control through trial-and-error interaction with the environment.
35
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1.5K
Citations
104
Authors
43
Institutions
Publications per year
2017–2026
24
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Decoupled Visual Servoing With Fuzzy <i>Q</i>-Learning
Haobin Shi, Xuesi Li, Wei Pan et al. · IEEE Transactions on Industrial Informatics · 2016 · 112 citations
Sim2Real Viewpoint Invariant Visual Servoing by Recurrent Control
Fereshteh Sadeghi, Alexander Toshev, Eric Jang et al. · 2018 · 108 citations
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National Sun Yat-sen University
Kaohsiung City, Taiwan
5 h-index
5 publications
282 citations

Northwestern Polytechnical University
Xi'an, China
5 h-index
17 publications
990 citations

University of Alberta
Edmonton, Canada
3 h-index
12 publications
391 citations

Australian National University
Canberra, Australia
2 h-index
4 publications
148 citations

University of Alicante
Alicante, Spain
2 h-index
2 publications
62 citations
University of California, Berkeley
Berkeley, United States
2 h-index
4 publications
195 citations

Zhejiang University of Technology
Hangzhou, China
2 h-index
9 publications
620 citations
Örebro University
Örebro, Sweden
2 h-index
3 publications
73 citations
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2 publications · 179 citations
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Repository · 2 publications · 83 citations
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2 publications · 198 citations
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ISJ · 1 publications · 22 citations
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1 publications · 68 citations
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