An analog neural oscillator circuit for locomotion controller in quadruped walking robot

In this report, we propose an analog neural oscillator circuit for a locomotion controller in a quadruped walking robot. Animal locomotion, such as walking, running, swimming and flying, is based on periodic rhythmic movements. These rhythmic movements are driven by the biological neural network, called the central pattern generator (CPG). In recent years, many researchers have applied CPG to the locomotion controller for walking robots. However, most of the CPG controllers have been developed with digital processors, and thus have several problems, such as higher power consumption. Hence, we designed an analog circuit as a neural oscillator underlying a CPG controller. The proposed circuit is based on the Amari-Hopfield model, which is suitable for analog circuit implementation because of its simple transfer function. Furthermore, the proposed circuit operates in the subthreshold region. As a result, it can reduce power consumption. By numerical analysis, simulations and experiments, the proposed circuit is shown to have the capability to generate stable rhythmic patterns in noisy environments.