FUZZY LOGIC APPROACH FOR LINE FOLLOWING MOBILE ROBOT USING AN ARRAY OF DIGITAL SENSORS

ABSTRACT The fuzzy concept that uses reasoning rather than exact computation has been proven and successfully applied in many applications. Implementing fuzzy logic generally involves three basic procedures; (1) fuzzification, or fuzzy inference process that converts crisp sensors value into fuzzy world, (2) computation, where the fuzzy value being treated, and (3) defuzzification, where the fuzzy output is converted back into crisp values mainly for actuators. Fuzzification revolves within the context of converting sensors data into fuzzy world. Using analog sensor for fuzzification has been long discussed by numerous literatures as the analog sensors has ranges. However, converting digital sensors into fuzzy world is much challenging than analog sensors due to the limited logical digital output. In this paper, we explain our technique in fuzzification of an array of digital sensors with an application to a line following mobile robot. We also discuss the Pugh selection matrix in order to choose the most effective mobile robot design. Then, we apply fuzzy logic control system to the developed mobile robot. Our present results for the LFR motion control yield in much faster and efficient tracking comparable to PID and switching algorithm that uses the same platform. Keywords: Fuzzy logic, Fuzzification, Line following robot, Pugh matrix