Dong Hyeon Kim

Papers

Total Citations

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About

Dong Hyeon Kim is a researcher in robotics and computer vision, with a primary focus on visual servoing and autonomous manipulation. His most cited work, "6-DOF Robot Arm Visual Servoing with Canny Edge-Based Object Detection" (2021, 5 citations), introduces a practical approach to controlling robotic arms using vision sensors. By leveraging OpenCV’s machine vision library, Kim developed a method to detect object contours and central points, enabling precise, real-time feedback for six-degree-of-freedom robot arms. This contribution addresses a key challenge in industrial automation: integrating low-cost, vision-based control without relying on expensive sensors. His research bridges the gap between classical edge detection algorithms and modern robotic control, offering a scalable solution for tasks like pick-and-place and assembly. While his citation count is modest, his work represents a foundational step in making visual servoing more accessible for small-scale and educational robotics. Kim’s approach emphasizes efficiency and reproducibility, making it valuable for students and engineers entering the field of robot vision. His ongoing efforts continue to explore the intersection of computer vision and autonomous systems, aiming to enhance robot adaptability in dynamic environments.