Evolutionary algorithm based neural network controller optimization for autonomous mobile robot navigation

Abstract

A neural network based navigation algorithm is proposed for mobile robots using ultrasonic sensors. The neural network has a dynamically reconfigurable structure which can not only optimize the weights but also the input sensory connectivity in order to meet any user-defined objective. Further, in order to enhance generalization capability of a single network, a modular network is used in which each network module is optimized for a specific local environment based on environment classification. Both computer simulation and real experiments show the effective performance of the algorithm.