Learning Stable and Energetically Economical Walking with RAMone

Audrow Nash; Yu-Ming Chen; Nils Smit-Anseeuw; Petr Zaytsev; C. David Remy

Learning Stable and Energetically Economical Walking with RAMone

Robotics 2017-11-07 v1

Authors: Audrow Nash , Yu-Ming Chen , Nils Smit-Anseeuw , Petr Zaytsev , C. David Remy

Abstract

In this paper, we optimize over the control parameter space of our planar-bipedal robot, RAMone, for stable and energetically economical walking at various speeds. We formulate this task as an episodic reinforcement learning problem and use Covariance Matrix Adaptation. The parameters we are interested in modifying include gains from our Hybrid Zero Dynamics style controller and from RAMone's low-level motor controllers.

Keywords

robot locomotion

Cite

@article{arxiv.1711.01316,
  title  = {Learning Stable and Energetically Economical Walking with RAMone},
  author = {Audrow Nash and Yu-Ming Chen and Nils Smit-Anseeuw and Petr Zaytsev and C. David Remy},
  journal= {arXiv preprint arXiv:1711.01316},
  year   = {2017}
}

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