Ai-Yun Zang

Shandong Institute of Automation, Ocean University of China

Papers

Total Citations

H-Index

About

Ai-Yun Zang is a robotics researcher whose work bridges the gap between sensor innovation and autonomous perception in challenging environments. Her early contributions include the development of a high-accuracy, low-cost orientation sensor for mobile robots, combining magnetic sensors and accelerometers to deliver real-time absolute orientation data—a foundational tool for autonomous navigation. More recently, Zang has tackled the complexities of undersea robotics, where she introduced a graph-based registration and blending method for stitching undersea images. This work addresses the severe appearance ambiguity caused by limited light and local disturbances, enabling clearer visual perception for underwater robots. Though her citation counts are modest—6 and 5 respectively—her research demonstrates a focused trajectory from sensor design to applied computer vision in extreme environments. Zang’s work is particularly relevant for students and researchers interested in low-cost sensing solutions and the unique challenges of underwater autonomy, where robust perception remains a critical bottleneck.