Fly-inspired sensory feedback in a reaction-diffusion neural system for locomotion control in a hexapod robot

Abstract

In this paper the implementation of a stable locomotion controller with sensory feedback on a hexapod robot structure is reported. Inspiration comes from recent results on the insect Drosophila melanogaster neural networks in charge for the control and modulation of basic crawling motion, where the role of sensory feedback is emphasized. A simple neural network, acting as a locomotion controller was designed and implemented. The phase stability, essential for a reliable gait generation, is assured exploiting tools from Partial contraction theory, whereas sensory feedback is used to locally modify the motor neuron dynamics to improve the robot dexterity in front of uneven terrains. Experimental results are reported in an autonomous hexapod robot, where the locomotion controller and sensory feedback are implemented in a commercial microcontroller low cost platform.