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Three of the mechanisms believed to be responsible for leg coordination in the stick insect, Carausius morosus, are used to control the straight-line locomotion of a hexapod robot on a smooth surface. The robot walks with a continuum of statically stable insectlike gaits in response to a single, scalar user input that controls the speed of locomotion. This control strategy is highly robust in the sense that the controller continues to maintain its basic function of causing the robot to walk effectively despite large perturbations to the controller. This controller robustness was demonstrated by inducing a wide variety of lesions (severing of connections) and performing parameter sensitivity studies.

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We present fully distributed neural network architecture for controlling the locomotion of a hexapod robot. The design of this network is directly based on work on the neuroethology of insect locomotion. Previously, we demonstrated in simulation that this controller could generate a continuous range of statically stable insect-like gaits as the activity of a single command neuron was varied and that it was robust to a variety of lesions. We now report that the controller can be utilized to direct the locomotion of an actual six-legged robot, and that it exhibits a range of gaits and degree of robustness in the real world that is quite similar to that observed in simulation.