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About

Fatchul Arifin is a researcher whose work sits at the intersection of robotics, computer vision, and intelligent control systems. His primary research areas include autonomous aerial robotics, human-robot interaction, and machine learning for visual perception. Arifin’s most impactful contribution is the development of a face-tracking system for quadcopters, detailed in his highly cited 2021 paper “Face Tracking for Flying Robot Quadcopter based on Haar Cascade Classifier and PID Controller” (22 citations). This work integrates classical computer vision techniques with robust PID control, enabling a drone to autonomously detect and follow a human face—a foundational capability for applications in surveillance, cinematography, and assistive robotics. More recently, he has advanced into deep learning for affective computing, as seen in his 2023 study on “Enhanced Emotion Recognition in Videos” (2 citations), where he employs Convolutional Neural Networks to classify human facial expressions from video streams. Arifin also contributes to industrial automation, having simulated the kinematics of a 6-DOF welding manipulator using V-REP PRO EDU. His research demonstrates a consistent drive to bridge perception and action, making robots more responsive to human presence and intent.