Real-world Adaptation
Real-World Adaptation is a methodological contribution in the field of Sim-To-Real Transfer that enables robotic systems to adjust simulated policies or models to perform effectively in physical environments by addressing discrepancies arising from sensor noise, environmental dynamics, and hardware variability.
35
Publications
2.7K
Citations
111
Authors
51
Institutions
Publications per year
2017–2026
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51

Universitat Autònoma de Barcelona
Cerdanyola del Vallès, Spain
3 h-index
10 publications
1K citations
McGovern Institute for Brain Research
Cambridge, United States
2 h-index
4 publications
188 citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
1 h-index
3 publications
120 citations
Sorbonne Paris Cité
Paris, France
1 h-index
3 publications
108 citations
Yale University
New Haven, United States
1 h-index
1 publications
493 citations
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo"
Pisa, Italy
1 h-index
5 publications
165 citations
West China Medical Center of Sichuan University
Chengdu, China
1 h-index
3 publications
72 citations
University of Geneva
Geneva, Switzerland
1 h-index
1 publications
36 citations
1–8 of 51
Repository · 4 publications · 365 citations
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1 publications · 18 citations
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Repository · 1 publications · 13 citations
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1 publications · 15 citations
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1 publications · 17 citations
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