Locomotion Skill Learning
Locomotion Skill Learning is a computational framework within robotics and artificial intelligence that enables autonomous agents to acquire and refine complex movement behaviors through interaction with environments, distinguished from generic motor learning by its focus on adaptive, context-sensitive, and often hierarchical control policies for effective locomotion across diverse terrains and dynamic conditions.
61
Publications
6.5K
Citations
218
Authors
67
Institutions
Publications per year
2017–2026
36
Parents
61
Learning agile and dynamic motor skills for legged robots
Jemin Hwangbo, Joonho Lee, Alexey Dosovitskiy et al. · Science Robotics · 2019 · 1.4K citations · Full text
Xue Bin Peng, Glen Berseth, KangKang Yin et al. · ACM Transactions on Graphics · 2017 · 512 citations
ANYmal parkour: Learning agile navigation for quadrupedal robots
David Hoeller, Nikita Rudin, Dhionis Sako et al. · Science Robotics · 2024 · 220 citations
1–5 of 61
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67

University of British Columbia
Vancouver, Canada
7 h-index
18 publications
3.2K citations
Georgia Institute of Technology
Atlanta, United States
6 h-index
8 publications
362 citations
Google (United States)
Mountain View, United States
6 h-index
30 publications
1.3K citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
6 publications
339 citations
University of California, Berkeley
Berkeley, United States
5 h-index
9 publications
509 citations
National University of Singapore
Singapore, Singapore
2 h-index
2 publications
594 citations

University of Amsterdam
Amsterdam, The Netherlands
2 h-index
2 publications
80 citations
The University of Texas at Austin
Austin, United States
2 h-index
7 publications
487 citations
1–8 of 67
TOG · 7 publications · 1.2K citations
7
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Repository · 7 publications · 240 citations
7
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4 publications · 237 citations
4
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3 publications · 1.8K citations
3
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2 publications · 103 citations
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