Collaborative Robot Learning

Collaborative Robot Learning is a machine learning framework that enables robots to acquire collaborative behaviors through shared experiences and interactive feedback from human partners, distinguishing it from autonomous or isolated robot learning approaches by emphasizing bidirectional, joint adaptation in human-robot teams.

94

Publications

5.7K

Citations

289

Authors

108

Institutions

Publications per year

2017–2026

48

Authors

289

  1. MK
    Masayoshi Kanoh

    Chukyo University, Japan

    5 publications · 95 citations

    5

    h-index

  2. FJ
    Felix Jimenez

    Chukyo University, Japan

    5 publications · 95 citations

    5

    h-index

  3. CB
    Cynthia Breazeal

    Massachusetts Institute of Technology, United States

    4 publications · 515 citations

    4

    h-index

  4. AL
    Andrea Lockerd

    Massachusetts Institute of Technology, United States

    4 publications · 515 citations

    4

    h-index

  5. SC
    Sylvain Calinon

    Idiap Research Institute, Switzerland

    4 publications · 558 citations

    4

    h-index

1–5 of 289

Venues

  1. Robotics and Computer-Integrated Manufacturing

    3 publications · 499 citations

    3

    h-index

  2. IEEE Robotics and Automation Letters

    2 publications · 33 citations

    2

    h-index

  3. IEEE Access

    2 publications · 85 citations

    2

    h-index

  4. Computers & Education

    2 publications · 281 citations

    2

    h-index

  5. 2

    h-index

1–5