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Gait Generation for a Hopping Robot Via Iterative Learning Control Based on Variational Symmetry

  • Satoshi Satoh
  • Kenji Fujimoto
  • Sang-Ho Hyon
Conference paper
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 366)

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.

Keywords

Cost Function Hamiltonian System Stance Phase Iterative Learning Control Variational Symmetry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Satoshi Satoh
    • 1
  • Kenji Fujimoto
    • 2
  • Sang-Ho Hyon
    • 3
  1. 1.Department of Mechanical Science and Engineering, Graduate School of EngineeringNagoya UniversityNagoyaJapan
  2. 2.Department of Mechanical Science and Engineering, Graduate School of EngineeringNagoya UniversityNagoyaJapan
  3. 3.Computational Neuroscience LaboratoriesATRKyotoJapan

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