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Transition to an optimal periodic gait by simultaneous input and parameter optimization method of Hamiltonian systems

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Abstract

This paper is concerned with a gait transition to an optimal periodic gait by a simultaneous input and parameter optimization technique of Hamiltonian systems. First, a continuous-time dynamics of a passive walking/running robot between the touchdown and lift-off is considered as a Hamiltonian system. Then, the control input and some robot parameters, such as the mass, inertia, link length, and so on, are optimized using learning optimal control of Hamiltonian systems, which has been developed by the authors. This method allows one to simultaneously obtain an optimal feedforward input and optimal parameters, which (at least locally) minimize a given cost function. The main advantage is that the precise model of the dynamics of the plant system is not required using a symmetric property of Hamiltonian systems, called variational symmetry. We formulate an optimal gait generation scheme via the learning optimal control, where the robot keeps walking and the gait is optimized with respect to the control input and some adjustable robot parameters simultaneously. As a result, the gait transition to an optimal periodic one is achieved.

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Authors and Affiliations

  1. Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, 739-8527, Japan

    Satoshi Satoh & Masami Saeki

  2. Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto, 606-8501, Japan

    Kenji Fujimoto

Authors
  1. Satoshi Satoh
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  2. Kenji Fujimoto
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  3. Masami Saeki
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Corresponding author

Correspondence to Satoshi Satoh.

Additional information

This work was partially supported by JSPS Grant-in-Aid for Young Scientists (B) (No. 15K18089).

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Satoh, S., Fujimoto, K. & Saeki, M. Transition to an optimal periodic gait by simultaneous input and parameter optimization method of Hamiltonian systems. Artif Life Robotics 21, 258–267 (2016). https://doi.org/10.1007/s10015-016-0294-5

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  • DOI: https://doi.org/10.1007/s10015-016-0294-5

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