Fuzzy Logic Sensor Fusion for Obstacle Avoidance Mobile Robot

Autonomous mobile robots have in recent times gained interest from many researchers. A reliable collision avoidance methodology is needed for effective navigation. Normally robots are fitted with transducers such as ultrasonic sensors, infrared and camera for detecting environment. However, they are usually unreliable because of pertinent problems of dealing with vagueness in the surroundings. Many researcher present three input Fuzzy Controller for obstacle avoidance robots usually resulting in dead zone and difficulties in avoiding obstacles. A fusion model using Fuzzy logic is proposed. It uses eight input distance sensors, two output variables and twenty seven fuzzy rules for robot navigation. Simulations are performed to validate feasibility and efficacy of proposed model using V-REP and MATLAB software.