Long-Yi Chang

National Chin-Yi University of Technology

Papers

Total Citations

H-Index

About

Long-Yi Chang is a researcher whose work centers on the control and autonomy of underwater robotic systems, with a particular focus on vision-based navigation and station-keeping in challenging deep-water environments. His most-cited paper, "Visual servo control for the underwater robot station-keeping" (2017), introduces a novel integration of visual servo techniques with a fuzzy-PID controller to enable precise position-holding for underwater robots, which are notoriously susceptible to disturbances from water currents and external forces. This contribution addresses a critical bottleneck in underwater robotics: maintaining stable, controlled operations without drifting. While his citation count is currently modest, the technical depth of his work—combining computer vision with adaptive control theory—lays important groundwork for advancing autonomous underwater vehicle (AUV) capabilities in real-world, high-disturbance settings. Chang’s research is particularly valuable for applications in ocean exploration, underwater infrastructure inspection, and environmental monitoring, where reliable station-keeping is essential for data collection and manipulation tasks.