Object Detection For Robotics

Object Detection for Robotics is a computational framework within robotic perception that enables machines to identify and locate objects in visual data by integrating detection algorithms with robotic system constraints, distinguishing it from general object detection through its focus on real-time performance, embodiment, and action-oriented accuracy requirements.

629

Publications

25.4K

Citations

2.2K

Authors

616

Institutions

Publications per year

2017–2026

323

Authors

2.2K

  1. LN
    Lorenzo Natale

    Italian Institute of Technology, Italy

    7 publications · 197 citations

    7

    h-index

  2. SB
    Sven Behnke

    University of Bonn, Germany

    6 publications · 321 citations

    6

    h-index

  3. DK
    Danica Kragić

    KTH Royal Institute of Technology, Sweden

    5 publications · 182 citations

    5

    h-index

  4. CB
    Chiara Bartolozzi

    Italian Institute of Technology, Italy

    5 publications · 296 citations

    5

    h-index

  5. LR
    Lorenzo Rosasco

    University of Genoa, Italy

    5 publications · 140 citations

    5

    h-index

1–5 of 2.2K

Venues

  1. Sensors

    25 publications · 869 citations

    19

    h-index

  2. arXiv (Cornell University)

    Repository · 15 publications · 554 citations

    13

    h-index

  3. IEEE Robotics and Automation Letters

    9 publications · 453 citations

    9

    h-index

  4. 9

    h-index

  5. The International Journal of Robotics Research

    IJRR · 9 publications · 879 citations

    9

    h-index

1–5