Safe Robot Learning

Safe Robot Learning is a subfield of robot learning that focuses on ensuring the learning process and resulting behaviors of robots adhere to safety constraints to prevent harm to humans, the environment, or the robot itself during training and deployment.

125

Publications

6.6K

Citations

439

Authors

124

Institutions

Publications per year

2017–2026

103

Authors

439

  1. DS
    Daniel S. Brown

    The University of Texas at Austin, United States

    6 publications · 123 citations

    6

    h-index

  2. SN
    Scott Niekum

    The University of Texas at Austin, United States

    5 publications · 108 citations

    5

    h-index

  3. JI
    Julian Ibarz

    Google (United States), United States

    4 publications · 303 citations

    4

    h-index

  4. AP
    Angela P. Schoellig

    University of Toronto, Canada

    4 publications · 722 citations

    4

    h-index

  5. VB
    Vincent Berenz

    Max Planck Institute for Intelligent Systems, Germany

    4 publications · 137 citations

    4

    h-index

1–5 of 439

Venues

  1. arXiv (Cornell University)

    Repository · 25 publications · 698 citations

    16

    h-index

  2. IEEE Robotics and Automation Letters

    10 publications · 684 citations

    10

    h-index

  3. IEEE Transactions on Robotics

    4 publications · 315 citations

    4

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 568 citations

    3

    h-index

  5. MPG.PuRe (Max Planck Society)

    Repository · 2 publications · 71 citations

    2

    h-index

1–5