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Locomotion of snake-like robots using adaptive neural oscillators

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Abstract

This paper proposes a CPG-based control architecture using a frequency-adaptive oscillator for undulatory locomotion of snake-like robots. The control architecture consists of a network of neural oscillators that generates desired oscillatory output signals with specific phase lags. A key feature of the proposed architecture is a self-adaptation process that modulates the parameters of the CPG to adapt the motion of the robot to varying coefficients of body-ground friction. This process is based on the frequency-adaptation rule of the oscillator that is designed to learn the periodicity of sensory feedback signals. It has an important meaning of establishing a closed-loop CPG much more robust against environmental and/or system parameter changes. We verify the validity of the proposed locomotion control system employing a simulated snake-like robot moving over terrains with different friction coefficients with a constant velocity.

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Authors and Affiliations

  1. School of Information Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa, 923-1292, Japan

    Jae-Kwan Ryu & Nak Young Chong

  2. Center for Cognitive Robotics Research, Korea Institute of Science and Technology, 39-1 Hawolgok-dong, Seongbuk-gu, Seoul, 136-791, Korea

    Bum Jae You

  3. Center for Robotics and Intelligent Machines, College of Computing, Georgia Institute of Technology, 85 5th Street, Atlanta, GA, 30332, USA

    Henrik I. Christensen

Authors
  1. Jae-Kwan Ryu
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  2. Nak Young Chong
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  3. Bum Jae You
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  4. Henrik I. Christensen
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Correspondence to Jae-Kwan Ryu.

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Ryu, JK., Chong, N.Y., You, B.J. et al. Locomotion of snake-like robots using adaptive neural oscillators. Intel Serv Robotics 3, 1–10 (2010). https://doi.org/10.1007/s11370-009-0049-4

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  • DOI: https://doi.org/10.1007/s11370-009-0049-4

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