Concepedia

Contact-rich Control

Contact-Rich Control is a control framework in aerial manipulation that enables autonomous aerial vehicles to perform stable and precise physical interactions with environments through intentional, sustained, and dynamically responsive contact, distinguishing it from traditional non-contact flight control by explicitly accounting for force and torque exchange during interaction.

37

Publications

1.8K

Citations

146

Authors

48

Institutions

Publications per year

2017–2026

29

Parents

Publications

37

Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones

Suraj Nair, Michael Luo, Krishnan Srinivasan et al. · IEEE Robotics and Automation Letters · 2021 · 197 citations

, , +17

Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost

Henry Zhu, Abhishek Gupta, Aravind Rajeswaran et al. · 2019 · 172 citations

, , +17

Learning Force Control for Contact-Rich Manipulation Tasks With Rigid Position-Controlled Robots

Cristian C. Beltran-Hernandez, Damien Petit, Ixchel G. Ramírez-Alpizar et al. · IEEE Robotics and Automation Letters · 2020 · 151 citations · Full text

, , +17

Sampling-based contact-rich motion control

Libin Liu, KangKang Yin, Michiel van de Panne et al. · ACM Transactions on Graphics · 2010 · 132 citations

, , +14

Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry

Siyuan Dong, Devesh K. Jha, Diego Romeres et al. · 2021 · 92 citations

, , +17

1–5 of 37

Authors

146

  1. HZ
    Henry Zhu

    Google (United States), United States

    2 publications · 191 citations

    2

    h-index

  2. KY
    KangKang Yin

    University of British Columbia, Canada

    2 publications · 166 citations

    2

    h-index

  3. OS
    Oren Spector

    Technion – Israel Institute of Technology, Israel

    2 publications · 64 citations

    2

    h-index

  4. JI
    Julian Ibarz

    Google (United States), United States

    2 publications · 217 citations

    2

    h-index

  5. SN
    Suraj Nair

    Stanford University, United States

    2 publications · 217 citations

    2

    h-index

1–5 of 146

Institutions

48

  1. Stanford University

    Stanford, United States

    5 h-index

    14 publications

    876 citations

  2. Tsinghua University

    Beijing, China

    4 h-index

    10 publications

    550 citations

  3. Google (United States)

    Mountain View, United States

    4 h-index

    4 publications

    408 citations

  4. University of California, Berkeley

    Berkeley, United States

    4 h-index

    14 publications

    717 citations

  5. Massachusetts Institute of Technology

    Cambridge, United States

    4 h-index

    14 publications

    844 citations

  6. Florida State University

    Tallahassee, United States

    3 h-index

    6 publications

    90 citations

  7. Carnegie Mellon University

    Pittsburgh, United States

    3 h-index

    12 publications

    653 citations

  8. ETH Zurich

    Zurich, Switzerland

    2 h-index

    10 publications

    270 citations

1–8 of 48

Venues

  1. IEEE Robotics and Automation Letters

    9 publications · 603 citations

    9

    h-index

  2. arXiv (Cornell University)

    Repository · 4 publications · 69 citations

    4

    h-index

  3. Journal of Research in Music Education

    2 publications · 50 citations

    2

    h-index

  4. IEEE Transactions on Robotics

    2 publications · 159 citations

    2

    h-index

  5. 2022 International Conference on Robotics and Automation (ICRA)

    Conference · 1 publications · 30 citations

    1

    h-index

1–5