Human-robot Interaction Learning

Human-Robot Interaction Learning is an academic research area within Robot Learning that focuses on enabling robots to acquire skills and behaviors through dynamic, bidirectional interactions with humans, distinguishing itself by integrating human feedback, social cues, and collaborative strategies into the learning process.

1.7K

Publications

82.6K

Citations

4.5K

Authors

1K

Institutions

Publications per year

2017–2026

804

Authors

4.5K

  1. CB
    Cynthia Breazeal

    Massachusetts Institute of Technology, United States

    36 publications · 4K citations

    30

    h-index

  2. AB
    Aude Billard

    École Polytechnique Fédérale de Lausanne, Switzerland

    27 publications · 2.2K citations

    22

    h-index

  3. SC
    Sylvain Calinon

    Idiap Research Institute, Switzerland

    25 publications · 2.5K citations

    20

    h-index

  4. KD
    Kerstin Dautenhahn

    University of Hertfordshire, United Kingdom

    26 publications · 1.2K citations

    18

    h-index

  5. BS
    Brian Scassellati

    Yale University, United States

    20 publications · 2K citations

    18

    h-index

1–5 of 4.5K

Venues

  1. arXiv (Cornell University)

    Repository · 55 publications · 3K citations

    25

    h-index

  2. Frontiers in Robotics and AI

    35 publications · 1.1K citations

    21

    h-index

  3. IEEE Robotics and Automation Letters

    37 publications · 1.4K citations

    21

    h-index

  4. IEEE Transactions on Autonomous Mental Development

    TAMD · 21 publications · 1.2K citations

    20

    h-index

  5. Robotics and Autonomous Systems

    25 publications · 1.5K citations

    20

    h-index

1–5