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A Novel Hardware-Efficient CPG Model Based on Nonlinear Dynamics of Asynchronous Cellular Automaton

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Neural Information Processing (ICONIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10639))

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Abstract

A novel hardware-efficient central pattern generator (CPG) model based on the nonlinear dynamics of an asynchronous cellular automaton is presented. It is shown that the presented model can generate multi-phase synchronized periodic signals, which are suitable for controlling a snake robot. Then, the presented model is implemented on a field programmable gate array (FPGA) and is connected to a snake robot hardware. It is shown by real machine experiments that the presented model can realize rhythmic spinal locomotions of the snake robot. Moreover, it is shown that the presented model consumes much fewer hardware resources (FPGA slices) than a standard simple CPG model.

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Authors and Affiliations

  1. Kyoto Sangyo University, 1-3 Motoyama, Kamigamo, Kitaku, Kyoto, 605-8555, Japan

    Kentaro Takeda & Hiroyuki Torikai

Authors
  1. Kentaro Takeda
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  2. Hiroyuki Torikai
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Corresponding author

Correspondence to Kentaro Takeda .

Editor information

Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Derong Liu

  2. Guangdong University of Technology, Guangzhou, China

    Shengli Xie

  3. South China University of Technology, Guangzhou, China

    Yuanqing Li

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Dongbin Zhao

  5. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

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Takeda, K., Torikai, H. (2017). A Novel Hardware-Efficient CPG Model Based on Nonlinear Dynamics of Asynchronous Cellular Automaton. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10639. Springer, Cham. https://doi.org/10.1007/978-3-319-70136-3_86

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  • DOI: https://doi.org/10.1007/978-3-319-70136-3_86

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70135-6

  • Online ISBN: 978-3-319-70136-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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