Dynamic Gait Generation

Dynamic Gait Generation is a computational method in mobile robot locomotion that synthesizes adaptive, real-time footfall and body motion patterns by leveraging system dynamics and environmental feedback, distinguishing it from static or pre-programmed gait approaches through its reliance on continuous dynamic stability and temporal responsiveness.

110

Publications

4K

Citations

301

Authors

117

Institutions

Publications per year

2017–2026

26

Authors

301

  1. FA
    Fumihiko Asano

    Japan Advanced Institute of Science and Technology, Japan

    16 publications · 511 citations

    13

    h-index

  2. ZL
    Zhiwei Luo

    Kobe University, Japan

    14 publications · 539 citations

    12

    h-index

  3. YF
    Yasuhiro Fukuoka

    Ibaraki University, Japan

    4 publications · 227 citations

    4

    h-index

  4. AD
    Aaron D. Ames

    California Institute of Technology, United States

    4 publications · 250 citations

    4

    h-index

  5. LL
    Leonardo Lanari

    Sapienza University of Rome, Italy

    4 publications · 180 citations

    4

    h-index

1–5 of 301

Venues

  1. IEEE Transactions on Robotics

    6 publications · 509 citations

    6

    h-index

  2. IEEE Robotics and Automation Letters

    5 publications · 135 citations

    5

    h-index

  3. Journal of the Robotics Society of Japan

    4 publications · 68 citations

    4

    h-index

  4. Robotica

    4 publications · 146 citations

    4

    h-index

  5. Robotics and Autonomous Systems

    3 publications · 111 citations

    3

    h-index

1–5