A hardware CPG model for bipedal gait control using pulse-type hardware neural networks(P-HNN) that mimics a brainstem spinal cord projection and can switch gait using an electronic circuit is reported. Using the electronic circuit, neural network circuits can be developed that mimic a nervous system of living organisms and can substitute for a spinal cord function. Humans and animals generate gait locomotion by a central pattern generator (CPG) localized in the spinal cord. In addition, it is known that signals from a higher center nervous is input to the brainstem spinal cord projection to switch gait. We proposed the hardware CPG model using the P-HNN that can switch control signal patterns depending on the state of a pulse signal, which is assumed to be the upper center nervous. Generation and switching of control signals for walking and running were confirmed from circuit simulations and actual measurements of discrete circuits.
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