Abstract
This paper proposes a novel framework to generate optimal gait trajectories for a one-legged hopping robot via iterative learning control. This method generates gait trajectories which are solutions of a class of optimal control problems without using precise knowledge of the plant model. It is expected to produce natural gait movements such as that of a passive walker. Some numerical examples demonstrate the effectiveness of the proposed method.
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Satoh, S., Fujimoto, K., Hyon, SH. (2007). Gait Generation for a Hopping Robot Via Iterative Learning Control Based on Variational Symmetry. In: Allgüwer, F., et al. Lagrangian and Hamiltonian Methods for Nonlinear Control 2006. Lecture Notes in Control and Information Sciences, vol 366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73890-9_15
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DOI: https://doi.org/10.1007/978-3-540-73890-9_15
Publisher Name: Springer, Berlin, Heidelberg
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