Model-based Manipulation

Model-Based Manipulation is a manipulation learning approach that relies on an explicitly constructed dynamic or kinematic model of the environment to plan and execute robotic interactions through predictive simulation and optimization.

95

Publications

5K

Citations

309

Authors

98

Institutions

Publications per year

2017–2026

35

Authors

309

  1. LF
    Li Fei-Fei

    Stanford University, United States

    3 publications · 124 citations

    3

    h-index

  2. TH
    Tsutomu Hasegawa

    Kyushu University, Japan

    3 publications · 194 citations

    3

    h-index

  3. AM
    Aaron M. Dollar

    Yale University, United States

    3 publications · 833 citations

    3

    h-index

  4. TM
    Thomas M. Howard

    Carnegie Mellon University, United States

    3 publications · 82 citations

    3

    h-index

  5. YZ
    Yilin Zhu

    Zhejiang University, China

    2 publications · 175 citations

    2

    h-index

1–5 of 309

Venues

  1. arXiv (Cornell University)

    Repository · 6 publications · 374 citations

    6

    h-index

  2. IEEE Robotics and Automation Letters

    4 publications · 290 citations

    4

    h-index

  3. 3

    h-index

  4. Conference on Robot Learning

    Conference · 2 publications · 34 citations

    2

    h-index

  5. 2

    h-index

1–5