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A neuromuscular controller for bipedal walking

Although biped robots have been developed using various technologies, they are still well outperformed in some important aspects—such as speed and robustness—by their natural counterparts, humans. In human and animal walking control, stable gaits emerge from the global entrainment between the neuromusculo-skeletal system and the environment.1 Moreover, in human and animal locomotion, the muscle is more than a simple actuator. Some special properties of muscles—the inertia of a limb or the elasticity of a muscle, for example—can tremendously simplify the control demands of the nervous system for walking. Here, we present our design of, and experiments with, a planar biped robot and its reflexive neuromuscular control network. The network is composed of biologically plausible model neurons and a simple muscle model that is simulated with a control algorithm implemented on DC-geared motors. In contrast to other walking robots, our design has no central pattern generator in the form of a neuronal oscillator. Rhythmic patterns are generated by the whole system using the electrical and mechanical properties of the motors, the limbs, and the environment. In the experiments, our biped robot attained a relative walking speed faster than any other current biped robot, and comparable to that of humans.