Human-in-the-loop Robot Learning

Human-In-The-Loop Robot Learning is a robotic learning framework in which human expertise, feedback, or intervention is integrated as an active component during the learning process to improve data efficiency and ensure safety, distinguishing it from fully autonomous or purely data-driven approaches.

42

Publications

2.2K

Citations

176

Authors

80

Institutions

Publications per year

2017–2026

24

Variants

Hitl Robot Learning

Authors

176

  1. HI
    Hiroshi Ishiguro

    The University of Osaka, Japan

    3 publications · 164 citations

    3

    h-index

  2. HB
    Heni Ben Amor

    Arizona State University, United States

    3 publications · 164 citations

    3

    h-index

  3. EÖ
    Erhan Öztop

    Özyeğin University, Türkiye

    2 publications · 41 citations

    2

    h-index

  4. YX
    Yangsheng Xu

    Chinese University of Hong Kong, Hong Kong SAR China

    2 publications · 113 citations

    2

    h-index

  5. TM
    Takashi Minato

    The University of Osaka, Japan

    2 publications · 147 citations

    2

    h-index

1–5 of 176

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 87 citations

    4

    h-index

  2. Autonomous Robots

    3 publications · 77 citations

    3

    h-index

  3. Frontiers in Neurorobotics

    1 publications · 12 citations

    1

    h-index

  4. Journal of Intelligent & Robotic Systems

    1 publications · 46 citations

    1

    h-index

  5. 1

    h-index

1–5