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A neuro-fuzzy approach to obstacle avoidance of a nonholonomic mobile robot

In this paper, a neuro-fuzzy control system is developed for obstacle avoidance of nonholonomic mobile robot built in the ARIS lab. A combination of four infrared sensors is equipped to detect the distance to obstacles around the mobile robot. The distance information is processed by the proposed neuro-fuzzy controller to adjust the velocities of two separate driven wheels of the robot. Eighteen fuzzy rules are developed for the obstacle avoidance. Experiments demonstrate the effectiveness of the developed neuro-fuzzy controller.