Self-supervised Manipulation Learning

Self-Supervised Manipulation Learning is a machine learning approach within robotic manipulation that autonomously generates supervisory signals from raw, unlabeled interaction data to learn control policies without explicit human-provided labels.

40

Publications

1.9K

Citations

111

Authors

32

Institutions

Publications per year

2017–2026

38

Authors

111

  1. SL
    Sergey Levine

    University of California, Berkeley, United States

    10 publications · 685 citations

    10

    h-index

  2. CF
    Chelsea Finn

    University of California, Berkeley, United States

    9 publications · 572 citations

    9

    h-index

  3. FE
    Frederik Ebert

    University of California, Berkeley, United States

    5 publications · 498 citations

    5

    h-index

  4. LF
    Li Fei-Fei

    Stanford University, United States

    4 publications · 138 citations

    4

    h-index

  5. SS
    Silvio Savarese

    Stanford University, United States

    4 publications · 138 citations

    4

    h-index

1–5 of 111

Venues

  1. arXiv (Cornell University)

    Repository · 14 publications · 717 citations

    11

    h-index

  2. IEEE Robotics and Automation Letters

    4 publications · 274 citations

    4

    h-index

  3. Conference on Robot Learning

    Conference · 1 publications · 36 citations

    1

    h-index

  4. Sensors

    1 publications · 18 citations

    1

    h-index

  5. IEEE Transactions on Multimedia

    1 publications · 29 citations

    1

    h-index

1–5