<![CDATA[This research discusses the implementation of a Fuzzy Logic Controller (FLC) on an e-puck robot for wall following navigation. The goal is to develop an efficient and adaptive control system for robot navigation in complex environments. The method used includes designing an FLC with three inputs from ultrasonic sensors (ps5, ps6, ps7) and two outputs to control the left and right motor speeds. The fuzzy inference system uses the Mamdani method with a fuzzification process, inference based on rule base, and defuzzification using Mean of Maximal (MOM). Tests were carried out in a maze arena to evaluate the robot's performance in following walls. The results show that the FLC implementation succeeded in controlling the movement of the e-puck robot well, as indicated by a decrease in sensor reading error and motor speed stability over time. Analysis of GPS coordinate graphs also shows the robot's ability to navigate complex environments. In conclusion, the fuzzy logic approach is proven to be effective in handling uncertainty and providing adaptive control for wall following tasks in e-puck robots.]]>
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