Robotic Manipulation Learning

Robotic Manipulation Learning is a methodological framework within self-supervised robot learning that enables robots to acquire dexterous control policies for interacting with objects in unstructured environments through autonomous data generation and task-relevant representation learning.

496

Publications

31.9K

Citations

1.5K

Authors

310

Institutions

Publications per year

2017–2026

343

Authors

1.5K

  1. SL
    Sergey Levine

    University of California, Berkeley, United States

    53 publications · 6.9K citations

    34

    h-index

  2. PA
    Pieter Abbeel

    University of California, Berkeley, United States

    39 publications · 9.3K citations

    29

    h-index

  3. CF
    Chelsea Finn

    University of California, Berkeley, United States

    27 publications · 2.6K citations

    19

    h-index

  4. YZ
    Yuke Zhu

    Stanford University, United States

    19 publications · 1.2K citations

    15

    h-index

  5. SS
    Silvio Savarese

    Stanford University, United States

    19 publications · 1.1K citations

    15

    h-index

1–5 of 1.5K

Venues

  1. arXiv (Cornell University)

    Repository · 130 publications · 8.1K citations

    40

    h-index

  2. IEEE Robotics and Automation Letters

    32 publications · 1.7K citations

    22

    h-index

  3. Robotics and Autonomous Systems

    15 publications · 1K citations

    14

    h-index

  4. Conference on Robot Learning

    Conference · 8 publications · 449 citations

    8

    h-index

  5. The International Journal of Robotics Research

    IJRR · 6 publications · 936 citations

    6

    h-index

1–5