Hexapod locomotion control through a CNN based decentralized system

In this paper the decentralized locomotion control of a bio-inspired hexapod robot is realized by using cellular neural networks (CNNs). This approach is inspired by the model of decentralized locomotion control in the stick insect, where local influences, based on the leg status, revealed by contact sensors, coordinates the CNN cells devoted to control each of the legs. To prove the suitability of the approach, simulations of the control system when applied to a simplified dynamic hexapod model are presented. The good results obtained open the way to the realization of the control on the hexapod robot.