Intelligent Control of Mobile Agent Based on Fuzzy Neural Network in Intelligent Robotic Space

Abstract

This paper introduces Fuzzy Neural Network controller to increase the ability of a mobile robot in reacting to the dynamic environments. States of robot and environment, for examples, the distance between the mobile robot and obstacles and the velocity of mobile robot, are used as the inputs of fuzzy logic controller. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a sensor fusion technique is introduced, where the sensory data of ultrasonic sensors and a vision sensor are fused into the identification process. Preliminary experiment and results are shown to demonstrate the merit of the introduced navigation control algorithm.KeywordsCost FunctionMobile RobotMobile AgentFuzzy Inference SystemObstacle AvoidanceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.