Fuzzy Steering Control For Wall-Following Behavior Of A Mobile Robot In Webots Simulation
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Abstract
Navigation logic plays a crucial role in enabling mobile robots to move autonomously and safely within structured environments. This study presents the development and simulation of a wall-following mobile robot designed to navigate along predefined boundaries while avoiding frontal obstacles. The simulation is implemented in the Webots environment, where the robot employs infrared proximity sensors integrated with a fuzzy logic–based control algorithm. Crisp distance measurements obtained from sensors PS5, PS6, and PS7 are fuzzified into linguistic variables, namely Near, Medium, and Far. Based on the defined input and output membership functions, the fuzzy controller determines appropriate steering actions, including strong turning and forward motion. The proposed approach evaluates the relationship between proximity sensor thresholds and the resulting steering velocity control, demonstrating the effectiveness of fuzzy inference in regulating wall-following behavior.
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