Concepedia

Learning-based Grasp Planning

Learning-Based Grasp Planning is a computational approach within grasp planning that utilizes machine learning models trained on data to predict effective grasp configurations, distinguishing itself from analytic or rule-based methods by leveraging learned patterns from experience or demonstration.

31

Publications

1.3K

Citations

129

Authors

44

Institutions

Publications per year

2017–2026

19

Parents

Publications

31

Combining active learning and reactive control for robot grasping

Oliver Kroemer, Renaud Detry, Justus Piater et al. · Robotics and Autonomous Systems · 2010 · 156 citations · Full text

, , +16

Learning to grasp objects with multiple contact points

Quoc V. Le, David Kamm, Arda F Kara et al. · 2010 · 124 citations

, , +16

Learning and Evaluation of the Approach Vector for Automatic Grasp Generation and Planning

Staffan Ekvall, Danica Kragić · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · 2007 · 112 citations

, , +17

Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations

Michael Laskey, Jonathan Lee, Caleb Chuck et al. · 2016 · 78 citations · Full text

, , +15

Deep learning can accelerate grasp-optimized motion planning

Jeffrey Ichnowski, Yahav Avigal, Vishal Satish · Science Robotics · 2020 · 70 citations

, , +14

1–5 of 31

Authors

129

  1. TH
    Tucker Hermans

    University of Utah, United States

    4 publications · 146 citations

    4

    h-index

  2. QL
    Qingkai Lu

    University of Utah, United States

    4 publications · 146 citations

    4

    h-index

  3. KG
    Ken Goldberg

    University of California, Berkeley, United States

    4 publications · 194 citations

    4

    h-index

  4. BS
    Balakumar Sundaralingam

    University of Utah, United States

    3 publications · 91 citations

    3

    h-index

  5. JI
    Jeffrey Ichnowski

    University of California, Berkeley, United States

    3 publications · 133 citations

    3

    h-index

1–5 of 129

Institutions

44

  1. University of California, Berkeley

    Berkeley, United States

    5 h-index

    32 publications

    1.5K citations

  2. University of Utah

    Salt Lake City, United States

    4 h-index

    13 publications

    467 citations

  3. Nvidia (United States)

    Santa Clara, United States

    2 h-index

    8 publications

    146 citations

  4. Max Planck Institute for Biological Cybernetics

    Tübingen, Germany

    2 h-index

    4 publications

    364 citations

  5. University of Liège

    Liège, Belgium

    2 h-index

    4 publications

    364 citations

  6. University of Maryland, College Park

    College Park, United States

    2 h-index

    6 publications

    243 citations

  7. Huazhong University of Science and Technology

    Wuhan, China

    2 h-index

    5 publications

    122 citations

  8. Universität Hamburg

    Hamburg, Germany

    2 h-index

    6 publications

    102 citations

1–8 of 44

Venues

  1. Robotics and Autonomous Systems

    4 publications · 212 citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 71 citations

    2

    h-index

  3. Sensors

    1 publications · 45 citations

    1

    h-index

  4. 1

    h-index

  5. 1

    h-index

1–5