Non-programmed gait generation of quadruped robot using pulse-type hardware neuron models

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ORIGINAL ARTICLE

Non‑programmed gait generation of quadruped robot using pulse‑type hardware neuron models Yuki Takei1 · Katsuyuki Morishita1 · Riku Tazawa1 · Koichi Katsuya1 · Ken Saito1 Received: 15 April 2020 / Accepted: 23 August 2020 © The Author(s) 2020

Abstract In this paper, the authors will propose the active gait generation of a quadruped robot. The theory that quadruped animals unconsciously generate gaits by some system based on neural networks in the spinal cord is widely accepted. However, how biological neurons or neural networks can generate gaits is not clear. To clarify the gait generation method, one of the solutions is using the neuron model similar to the biological neuron. We developed the quadruped robot system using selfinhibited pulse-type hardware neuron models (P-HNMs), which can output the electrical activity similar to those of biological neurons. The P-HNMs consist of the cell body model and the inhibitory synaptic model. The cell body model periodically outputs pulsed voltages; the inhibitory synaptic model inhibits the pulsed voltages. The pulse period can change by varying the synaptic weight control voltage applied to the P-HNMs. We varied the synaptic weight control voltage according to the pressure on the robot’s toes. Also, we changed the angle of the robot’s joints by a constant angle each time the P-HNMs output a pulse. As a result of the walking experiment, we confirmed that the robot generates walk gait and trot gait according to the moving speed. Also, we clarified the process by which the robot actively generates gaits from the upright state. These results show that animals may not use many biological neurons to generate gaits. Furthermore, the results suggest the possibility of realizing simple and bio-inspired robot control. Keywords  Gait generation · Pulse-type hardware neuron model (P-HNM) · Quadruped robot · Self-inhibit

1 Introduction

This work was presented in part at the 25th International Symposium on Artificial Life and Robotics (Beppu, Oita, January 22–24, 2020). * Yuki Takei [email protected]‑u.ac.jp Katsuyuki Morishita [email protected]‑u.ac.jp Riku Tazawa [email protected]‑u.ac.jp Koichi Katsuya [email protected]‑u.ac.jp Ken Saito [email protected]‑u.ac.jp 1



Nihon University, 7‑24‑1 Narashinodai, Funabashi, Chiba 274‑8501, Japan

Quadruped animals change the gait according to the locomotion speed by adjusting leg movements [1]. The experiments using decerebrated cats show that gaits generated were unconsciously by some systems based on neural networks in the spinal cord [2–4]. Thus, implementing the gait generation mechanism of animals on a walking robot will allow the active gait generation with a simple control system. There are various studies for elucidating the mechanism by which animals gait generation method [5, 6]. However, the information processing of biological neurons is difficult to analyze. Therefore, research has been conducted to estimate the gait generation mechanism using robots. Research using a biped machine with passive join