Object Grasp Planning

Object Grasp Planning is a computational method in robot manipulation that determines optimal configurations for a robotic end-effector to securely acquire and stabilize a target object based on its geometry, physics, and environmental constraints.

156

Publications

7.6K

Citations

522

Authors

164

Institutions

Publications per year

2017–2026

51

Authors

522

  1. KG
    Ken Goldberg

    University of California, Berkeley, United States

    7 publications · 914 citations

    7

    h-index

  2. KH
    Kensuke Harada

    National Institute of Advanced Industrial Science and Technology, Japan

    7 publications · 223 citations

    7

    h-index

  3. TA
    Tamim Asfour

    Karlsruhe Institute of Technology, Germany

    5 publications · 180 citations

    5

    h-index

  4. JM
    Jeffrey Mahler

    University of California, Berkeley, United States

    4 publications · 773 citations

    4

    h-index

  5. KN
    Kazuyuki Nagata

    National Institute of Advanced Industrial Science and Technology, Japan

    4 publications · 116 citations

    4

    h-index

1–5 of 522

Venues

  1. IEEE Robotics and Automation Letters

    8 publications · 328 citations

    8

    h-index

  2. arXiv (Cornell University)

    Repository · 5 publications · 148 citations

    5

    h-index

  3. The International Journal of Robotics Research

    IJRR · 5 publications · 715 citations

    5

    h-index

  4. Robotics and Autonomous Systems

    5 publications · 247 citations

    5

    h-index

  5. Experimental Brain Research

    3 publications · 102 citations

    3

    h-index

1–5