Sensor-driven neural control for omnidirectional locomotion and versatile reactive behaviors of walking machines

Abstract

This article describes modular neural control structures for different walking machines utilizing discrete-time neurodynamics. A simple neural oscillator network serves as a central pattern generator producing the basic rhythmic leg movements. Other modules, like the velocity regulating and the phase switching networks, enable the machines to perform omnidirectional walking as well as reactive behaviors, like obstacle avoidance and different types of tropisms. These behaviors are generated in a sensori-motor loop with respect to appropriate sensor inputs, to which a neural preprocessing is applied. The neuromodules presented are small so that their structure–function relationship can be analysed. The complete controller is general in the sense that it can be easily adapted to different types of even-legged walking machines without changing its internal structure and parameters.