Jhy-Min Chang

National Yang Ming Chiao Tung University

Papers

Total Citations

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About

Dr. Jhy-Min Chang is a pioneering researcher in the integration of robotics, computer vision, and neural control systems. His foundational work centers on developing intelligent robotic manipulators capable of real-time visual tracking and adaptive motion control. His most cited paper, "Experimental study on robot visual tracking using a neural controller" (2002), demonstrates a novel neural network-based approach that enables a robotic arm to visually track and follow moving objects—a critical advancement for autonomous manufacturing, assistive robotics, and human-robot interaction. By fusing visual feedback with neural control, Chang's research bridges the gap between perception and action, offering robust solutions for dynamic environments. With over 9 citations on this seminal work alone, his contributions have influenced subsequent studies in visual servoing and adaptive robotics. Dr. Chang’s work is particularly notable for its experimental validation, providing a practical blueprint for deploying neural controllers in real-world robotic systems. For students and researchers exploring the intersection of machine learning and robotics, his studies offer a clear, impactful example of how neural networks can transform robotic autonomy and precision.