Papers

11

Total Citations

80

H-Index

5

About

Yinhui Xie is a robotics and automation researcher whose work centers on robotic surface finishing, force control systems, and intelligent manufacturing. With a career spanning nearly two decades, Xie has made significant contributions to advancing precision machining processes, particularly robotic polishing and grinding of mold steel. His most impactful work employs rigorous optimization frameworks — including Response Surface Method, Taguchi Method, and AI-driven approaches such as XGBoost — to systematically enhance surface quality parameters like roughness (Ra), earning over 20 citations on his leading study alone. Xie's research into adaptive impedance control for curved mold polishing (15 citations) reflects a sophisticated understanding of how robots must dynamically respond to complex geometries in real-world manufacturing environments. Beyond surface finishing, he has extended his expertise into agricultural robotics, developing a visually guided oolong tea harvesting robot that addresses efficiency and quality challenges in precision agriculture. His earlier foundational work on B-spline path planning, 6-DOF 3D printing, and spray coating systems underscores the breadth of his contributions to intelligent robotic applications. Collectively, Xie's research bridges theoretical control methods and practical industrial deployment, making his work highly relevant to students and engineers in advanced manufacturing and robotics.

Research Focus

Key Achievements

5
H-Index
11
Papers
80
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Process Optimization of Robotic Polishing for Mold Steel Based on Response Surface Method
20 citations · 2022
📈 Most Prolific Year: 2024 (3 Papers)
🤝 Key Collaborators: 32
🏛 Institutions: Chinese Academy of Sciences, Quanzhou Institute of Equipment Manufacturing Haixi Institute

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago