Robot Perception Features

Robot Perception Features is a methodological construct in robotics that comprises distinctive, measurable patterns or attributes extracted from sensory data to enable machines to interpret and understand environmental states and object properties for effective interaction.

39

Publications

1.4K

Citations

124

Authors

47

Institutions

Publications per year

2017–2026

11

Authors

124

  1. UN
    Ulrich Nehmzow

    University of Essex, United Kingdom

    2 publications · 67 citations

    2

    h-index

  2. SS
    Sebastian Scherer

    Carnegie Mellon University, United States

    2 publications · 47 citations

    2

    h-index

  3. SS
    Sanjiv Singh

    Carnegie Mellon University, United States

    2 publications · 47 citations

    2

    h-index

  4. KW
    Katsumi Watanabe

    The University of Tokyo, Japan

    2 publications · 40 citations

    2

    h-index

  5. HH
    Hongmei He

    Second Affiliated Hospital of Chongqing Medical University, China

    2 publications · 63 citations

    2

    h-index

1–5 of 124

Venues

  1. Robotics and Autonomous Systems

    2 publications · 124 citations

    3

    h-index

  2. ArXiv.org

    Repository · 2 publications · 67 citations

    2

    h-index

  3. IEEE Transactions on Cognitive and Developmental Systems

    TCDS · 2 publications · 139 citations

    2

    h-index

  4. 2

    h-index

  5. Robotics

    1 publications · 10 citations

    1

    h-index

1–5