Abstract
This article introduces a new approach to locomotion control in six-legged robots. The approach is inspired by the model of decentralized locomotion control in the stick insect introduced by one of the authors and makes use of second-order nonlinear systems to realize the neuron-like dynamics of the sub-units of the whole control system. Each of these sub-units controls the behavior of a leg and is coordinated with the others by means of local influences based on the leg status, revealed by contact sensors. The suitability of the approach has been shown by using cellular nonlinear networks (CNNs) to implement the leg controllers. Simulations of the CNN-based locomotion control demonstrate its robustness with respect to different initial conditions and the property of pattern recovery after the external blocking of a leg.
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