Implementation of Fuzzy Logic Control on a Robotic Arm Prototype for Object Position Detection - Suryaman; Tegar Dwi Pangestu; Rina Mardiati; Aan Eko Setiawan; Siti Hadiaty Yuningsih; Kiki Zakaria (International Journal of Research in Community Services, 2026)
The rapid advancement of robotics technology has significantly enhanced industrial automation, enabling continuous, precise, andefficient operations. This study aims to design and implement a Fuzzy Logic Control (FLC) system based on the Mamdanimethod in a robotic arm prototype capable of detecting and classifying object positions automatically. The prototype utilizes anArduino Mega 2560 microcontroller as the main controller and a Pixy2 CMUCam5 vision sensor for object detection. Two maininput parameters are used: Turn (object position) and Area (object distance from the camera). The control outputs are the angularpositions of the base and elbow servos. Experimental results show that the FLC system achieves high accuracy with a mean errorof 0.25% for the base servo and 0.27% for the elbow servo, compared to simulation and manual calculations. Furthermore, thefuzzy-based system demonstrated superior efficiency in detecting object positions (center, left, right) compared to non-fuzzycontrol. These findings indicate that implementing Mamdani Fuzzy Logic significantly improves the precision and responsivenessof robotic arm movement in object detection and manipulation tasks