Dynamics Randomization
Dynamics Randomization is a simulation-based training methodology that systematically varies physical parameters such as mass, friction, and damping within a virtual environment to enhance the robustness of control policies during Sim-To-Real transfer.
11
Publications
1.6K
Citations
59
Authors
20
Institutions
Publications per year
2017–2026
10
Parents
11
Sim-to-Real Transfer of Robotic Control with Dynamics Randomization
2018 · 793 citations · Full text
Learning agile soccer skills for a bipedal robot with deep reinforcement learning
Tuomas Haarnoja, Ben Moran, Guy Lever et al. · Science Robotics · 2024 · 148 citations
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Naver (South Korea)
Seongnam-si, South Korea
1 h-index
4 publications
308 citations
Vector Institute
Toronto, Canada
1 h-index
1 publications
75 citations

National Institute of Advanced Industrial Science and Technology
Tsukuba, Japan
1 h-index
3 publications
96 citations
University of California, Berkeley
Berkeley, United States
1 h-index
2 publications
1.6K citations
Google (United Kingdom)
London, United Kingdom
1 h-index
28 publications
4.1K citations
University College London
London, United Kingdom
1 h-index
1 publications
148 citations

University of British Columbia
Vancouver, Canada
1 h-index
2 publications
150 citations
Google DeepMind (United Kingdom)
London, United Kingdom
1 h-index
28 publications
4.1K citations
1–8 of 20
1 publications · 32 citations
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1 publications · 148 citations
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1 publications · 52 citations
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Repository · 1 publications · 168 citations
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DIA · 1 publications · 145 citations
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