Xiaowei Yue
Papers
8
Total Citations
110
H-Index
4
About
Xiaowei Yue is a leading researcher in advanced manufacturing systems, specializing in robotic quality inspection, autonomous multi-robot coordination, and data-driven process monitoring. His work bridges robotics, optimization, and manufacturing intelligence to enhance precision and efficiency in production environments. Yue’s major contributions include developing coverage path planning methods that control measurement uncertainty for robotic optical inspection, significantly improving dimensional verification of sheet structures (37 citations). He also pioneered a robust asymmetric kernel function for Bayesian optimization, enabling effective image defect detection in complex manufacturing systems (37 citations). His research extends to task allocation and coordinated motion planning for multi-robot systems, addressing challenges in distributed spot welding and optical inspection across multi-station assembly lines. More recently, Yue has advanced self-supervised learning techniques using streaming video data for real-time anomaly detection and progress prediction in repetitive production systems. With over 110 citations across his top papers, Yue’s work is highly impactful, offering practical solutions for small-scale customized manufacturing and human-robot integrated workflows. His achievements include pioneering trajectory planning methods for online robotic measurement and convex optimization for free-form surface inspection, positioning him as a key innovator in smart manufacturing and quality control.
Research Focus
Key Achievements
Top Papers
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