Robotic Skill Learning

Robotic Skill Learning is a methodological framework within robot learning that enables a robot to acquire task-specific behaviors through generalized experience, distinguished from other learning paradigms by its focus on mastering reusable, adaptive motor skills from limited interaction data or demonstrations.

525

Publications

30.9K

Citations

1.6K

Authors

420

Institutions

Publications per year

2017–2026

254

Authors

1.6K

  1. SL
    Sergey Levine

    University of California, Berkeley, United States

    30 publications · 3.8K citations

    23

    h-index

  2. JP
    Jan Peters

    Technische Universität Darmstadt, Germany

    27 publications · 2.1K citations

    19

    h-index

  3. DG
    Darwin G. Caldwell

    Italian Institute of Technology, Italy

    18 publications · 1.2K citations

    16

    h-index

  4. SC
    Sylvain Calinon

    Idiap Research Institute, Switzerland

    17 publications · 1.5K citations

    15

    h-index

  5. CF
    Chelsea Finn

    University of California, Berkeley, United States

    14 publications · 1.7K citations

    13

    h-index

1–5 of 1.6K

Venues

  1. arXiv (Cornell University)

    Repository · 44 publications · 2.7K citations

    25

    h-index

  2. Robotics and Autonomous Systems

    15 publications · 538 citations

    15

    h-index

  3. IEEE Robotics and Automation Letters

    15 publications · 471 citations

    14

    h-index

  4. IEEE Transactions on Cognitive and Developmental Systems

    TCDS · 9 publications · 324 citations

    9

    h-index

  5. Frontiers in Robotics and AI

    8 publications · 134 citations

    8

    h-index

1–5