Optimized fuzzy controller for mobile robot navigation in a cluttered environment

Obstacle avoidance and path planning are the most important problems in mobile robots. In this paper, a fuzzy logic controller has been constructed in order to train an intelligent robot. Gradient method is used to optimize consequences of a Sugeno fuzzy logic controller for the mobile robot navigation, in order to reach a target in a clutterd environment. Not only simulation results are shown in this paper, but also 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.