Depth-based Grasp Detection

Depth-Based Grasp Detection is a grasp detection approach that utilizes depth information from 3D sensor data as the primary modality to identify and localize feasible grasp poses for robotic manipulation.

21

Publications

1.1K

Citations

84

Authors

27

Institutions

Publications per year

2017–2026

15

Authors

84

  1. HZ
    Hao Zhu

    Peking University, China

    2 publications · 76 citations

    2

    h-index

  2. YQ
    Yuzhe Qin

    University of California San Diego, United States

    2 publications · 76 citations

    2

    h-index

  3. RW
    Robert W. Platt

    McGill University, Canada

    2 publications · 194 citations

    2

    h-index

  4. AT
    Andreas ten Pas

    Northeastern University, United States

    2 publications · 194 citations

    2

    h-index

  5. RC
    Rui Chen

    National University of Defense Technology, China

    2 publications · 76 citations

    2

    h-index

1–5 of 84

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 237 citations

    4

    h-index

  2. 1

    h-index

  3. Conference on Robot Learning

    Conference · 1 publications · 94 citations

    1

    h-index

  4. 1

    h-index

  5. MATEC Web of Conferences

    1 publications · 30 citations

    1

    h-index

1–5