Applying an intelligent system means the machine is capable of making its own unique decision.
Fuzzy logic is a form of logic that acknowledges other forms of true and false values. With fuzzy logic,
propositions may be diagrammatic with degrees of truthfulness and falsehood. The main aims of this
study are to demonstrate the method to apply fuzzy logic in a structure that uses Arduino as its brain,
and apply it in a line follower mobile robot’s decision making algorithm. This mobile robot consists of
two front wheels and a nub caster at the back. It uses a line follower array that consists of eight infrared
(IR) sensors. The system control is based on the input from IR sensors, which measures the intensity
of light reflected by the track. Data were then transmitted to the microcontroller and will then be sent
the correct command to the motor driver so that the trail can be followed. The performance of the line
follower robot when using the fuzzy logic algorithm was compared to the line follower algorithm, which
uses simple if-else commands. Analysis is primarily on the time taken to complete the track, along
with the behaviour of the robot while manoeuvring. From the results, fuzzy logic is shown to provide a
better performance in terms of the time taken to complete the track compared to the other set of rules. In
addition, from the video recordings, fuzzys are moving smoother as compared to the non-fuzzy logics.