Intelligent Systems
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Efficient Multi-Contact Pattern Generation with Sequential Convex Approximations of the Centroidal Dynamics

2021

Article

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This article investigates the problem of efficient computation of physically consistent multicontact behaviors. Recent work showed that under mild assumptions, the problem could be decomposed into simpler kinematic and centroidal dynamic optimization problems. Based on this approach, we propose a general convex relaxation of the centroidal dynamics leading to two computationally efficient algorithms based on iterative resolutions of second-order cone programs. They optimize centroidal trajectories, contact forces, and importantly the timing of the motions. We include the approach in a kinodynamic optimization method to generate full-body movements. Finally, the approach is embedded in a mixed-integer solver to further find dynamically consistent contact sequences. Extensive numerical experiments demonstrate the computational efficiency of the approach, suggesting that it could be used in a fast receding horizon control loop. Executions of the planned motions on simulated humanoids and quadrupeds and on a real quadruped robot further show the quality of the optimized motions.

Author(s): Brahayam Ponton and Majid Khadiv and Avadesh Meduri and Ludovic Righetti
Journal: IEEE Transactions on Robotics
Volume: Early access
Pages: 1-19
Year: 2021
Month: February
Publisher: IEEE

Department(s): Movement Generation and Control
Bibtex Type: Article (article)
Paper Type: Journal

Digital: True
DOI: 10.1109/TRO.2020.3048125
ISBN: 1941-0468
State: Published
URL: https://ieeexplore.ieee.org/document/9350175

BibTex

@article{ponton2021efficient,
  title = {Efficient Multi-Contact Pattern Generation with Sequential Convex Approximations of the Centroidal Dynamics},
  author = {Ponton, Brahayam and Khadiv, Majid and Meduri, Avadesh and Righetti, Ludovic},
  journal = {IEEE Transactions on Robotics},
  volume = {Early access},
  pages = {1-19},
  publisher = {IEEE},
  month = feb,
  year = {2021},
  doi = {10.1109/TRO.2020.3048125},
  url = {https://ieeexplore.ieee.org/document/9350175},
  month_numeric = {2}
}