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Integrated genetic algorithms and fuzzy control approach for optimization mobile robot navigation

This paper presents an optimal fuzzy logic controller design using optimization techniques. The fuzzy logic controller (FLC) has been developed and implemented for the motion of the robot from an initial position towards another desired position, taking into account the kinematic constraints. First, we have carried out a simulation of a fuzzy logic based controller which determines the speed values of each driving wheel, while seeking the goal. Secondly, an optimization of this controller has been realized using gradient method and genetic algorithms. A comparison between these methods has been effected. Not only simulation results are shown in this paper, but the “real-time” implementation has been realized onto the mini robot Khepera II. Simulation results verify successfully the application of the proposed method to real motion situations.