Fuzzy Logic Triggered Line Ensuing Robot with Edge and Obstacle Avoidance

Optimization of line-following robot results in improved speed, accuracy, and overall performance of the robot. Fuzzy logic controllers excel in managing complex, nonlinear systems by incorporating uncertainty and imprecision into decision-making processes. In this paper we are going to show a low-cost Line Following Robot (LFR) with various aspects of line following robot using fuzzy logic with the help of an Arduino microcontroller followed by defuzzification using the Mean of Maximum (MOM) method which is simple and easy to implement yet providing substantially good results and a comparison has been made with traditional switching line-following robot with obstacle sense to fuzzy control line and PID controlled robot and the fuzzy logic robot following robot few of the major modifications along with the typical fuzzy logic controller is the presence of ultrasonic sensors for obstacle detection and avoidance through logic along with that the system has been developed for edge detection and avoidance through the infrared sensors through logic these have increases the versatility and the scope of the project to a vast margin.