Autonomous navigation control for mobile robots based on emotion and environment cognition

Abstract

A new autonomous navigation control system for mobile robots is presented, in which the learning and decision making model based on emotion and cognition is introduced into the control architecture of behavior-based robot system. Dynamic system approach is applied to design the basic behaviors. Continuous environment perceptions are classified into categories by Adaptive Resonance Theory-2 (ART2) networks, which are used as the environmental cognitive states in learning and decision making. Rational behavior-coordination mechanism is developed by the on-line learning of emotion and environmental cognitive. Simulations have demonstrated that the emotion and environmental cognition can obviously improve the efficiency of the learning and decision making process, and enhance the capability of autonomous navigation in behavior-based robot system under unknown environment.