Approaches in adaptation of fuzzy cognitive maps for navigation purposes

Abstract

This paper deals with automatic adaptation of fuzzy cognitive maps (FCM) for navigation and obstacle avoidance of robotic vehicles. Various modifications of Hebbian learning as well as least mean square methods were used and experimentally compared on a simulation model of a vehicle to extract and evaluate their properties for setting-up parameters of FCM.