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 self-inhibited 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.

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In this chapter, the authors will propose the active gait generation of a quadruped robot. We developed the quadruped robot system using self-inhibited pulse-type hardware neuron models (P-HNMs) as a solution to elucidate the gait generation method. We feedbacked pressures at the robot system’s each foot to P-HNM and varied the joints’ angular velocity individually. We experimented with making the robot walk from an upright position on a flat floor. As a result of the experiment, we confirmed that the robot system spontaneously 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 suggest that animals may generate gait using a similarly simple method because P-HNM mimics biological neurons’ function. Furthermore, it shows that our robot system can generate gaits adaptively and quite easily.