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Development of a hardware CPG model for controlling both legs of a musculoskeletal humanoid robot with gait and gait cycle change by higher center and sensory information

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Abstract

Most conventional biped robots process leg movements and information from each sensor by numerical calculation using a CPU. However, to cope with diverse environments, the numerical calculations are enormous, so they must be processed at high speed using a high-performance CPU and high power consumption. On the other hand, focusing on human motor control, it is believed that basic motor patterns such as walking and running are generated by a neural network called the central pattern generator (CPG), which is localized in the spinal cord and is independent of calculation. We previously focused on pulse-type hardware neural networks (P-HNNs), in which the neural network was composed of analog electronic circuits, and developed a hardware CPG model for controlling a single leg of a musculoskeletal humanoid robot. However, to actually move a biped robot, a CPG model that takes into account both legs and sensory information is required. Therefore, this study aims to develop a hardware CPG model for controlling both legs of a musculoskeletal humanoid robot whose gait changes according to the higher center and sensory information. We report on a hardware CPG model configured by circuit simulation confirmed the generation of walking and running patterns.

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Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This study was supported in part by JSPS KAKENHI, Grant-in-Aid for Scientific Research JP22K04016. In addition, this work was partially supported by the research grant of Nihon University and NUROS.

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Authors and Affiliations

  1. Graduate School of Science and Technology, Nihon University, Chiba, Japan

    Tatsumi Goto, Takumi Ishihama & Kentaro Yamazaki

  2. College of Science and Technology, Nihon University, Chiba, Japan

    Rina Okamoto, Yugo Kokubun, Minami Kaneko & Fumio Uchikoba

Authors
  1. Tatsumi Goto
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  2. Rina Okamoto
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  3. Takumi Ishihama
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  4. Kentaro Yamazaki
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  5. Yugo Kokubun
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  6. Minami Kaneko
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  7. Fumio Uchikoba
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Corresponding author

Correspondence to Tatsumi Goto.

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This work was submitted and accepted for the Journal Track of the joint symposium of the 29th International Symposium on Artificial Life and Robotics, the 9th International Symposium on BioComplexity, and the 7th International Symposium on Swarm Behavior and Bio-Inspired Robotics (Beppu, Oita and Online, January 24–26, 2024).

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Goto, T., Okamoto, R., Ishihama, T. et al. Development of a hardware CPG model for controlling both legs of a musculoskeletal humanoid robot with gait and gait cycle change by higher center and sensory information. Artif Life Robotics (2024). https://doi.org/10.1007/s10015-024-00939-6

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  • DOI: https://doi.org/10.1007/s10015-024-00939-6

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