Robot Learning

Robot learning is a research discipline at the intersection of machine learning and robotics that studies algorithms and techniques enabling robotic systems to autonomously acquire skills and adapt to dynamic environments through experiential learning from interactive data.

5.2K

Publications

270.8K

Citations

11.6K

Authors

2K

Institutions

Publications per year

2017–2026

2.8K

Authors

11.6K

  1. SL
    Sergey Levine

    University of California, Berkeley, United States

    130 publications · 13.2K citations

    53

    h-index

  2. PA
    Pieter Abbeel

    University of California, Berkeley, United States

    80 publications · 10.9K citations

    48

    h-index

  3. JP
    Jan Peters

    Technische Universität Darmstadt, Germany

    69 publications · 4K citations

    36

    h-index

  4. AB
    Aude Billard

    École Polytechnique Fédérale de Lausanne, Switzerland

    46 publications · 4.6K citations

    31

    h-index

  5. SC
    Sylvain Calinon

    Idiap Research Institute, Switzerland

    46 publications · 4.3K citations

    30

    h-index

1–5 of 11.6K

Venues

  1. arXiv (Cornell University)

    Repository · 492 publications · 26.7K citations

    76

    h-index

  2. IEEE Robotics and Automation Letters

    156 publications · 7.3K citations

    46

    h-index

  3. Robotics and Autonomous Systems

    102 publications · 10.1K citations

    42

    h-index

  4. The International Journal of Robotics Research

    IJRR · 50 publications · 6.6K citations

    36

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 62 publications · 3.8K citations

    31

    h-index

1–5

See also

Robot Learning

Core Methods

Applications

Evaluation

Limitations