Yubin Wu

Huazhong University of Science and Technology, Xi'an High Tech University

Papers

Total Citations

H-Index

About

Yubin Wu’s research lies at the intersection of industrial automation, robot vision, and robust control systems, addressing critical challenges in both perception and stability. In his most cited work, “Robot visual guide with Fourier-Mellin based visual tracking” (2019, 11 citations), Wu tackles the demanding problem of target pose estimation for industrial robots. He presents a solution using binocular stereo vision enhanced by Fourier-Mellin transform, significantly improving tracking robustness and speed—a key contribution for real-time automation tasks. This work demonstrates his ability to bridge theoretical image processing with practical robotic guidance. Wu also advances control theory in “Novel Robust Stability Criteria of Uncertain Systems with Interval Time-Varying Delay” (2020, 2 citations), where he introduces a time-delay segmentation method and multiple integrals functional to reduce conservatism in stability analysis. This is particularly relevant for automatic robot control systems where delays are inevitable. While his citation counts are still growing, Wu’s work showcases a dual focus: enhancing robot perception through vision and ensuring reliable control through rigorous stability criteria. His contributions are especially valuable for students and researchers exploring practical, robust solutions in industrial robotics and automation.