Papers
3
Total Citations
22
H-Index
2
About
Yinan Xiao is a researcher advancing intelligent manufacturing through robotic automation and smart process optimization. His primary research areas include robotic grinding trajectory planning, surface quality prediction, and additive manufacturing. Xiao’s most impactful work, "Automatic Aluminum Alloy Surface Grinding Trajectory Planning of Industrial Robot Based on Weld Seam Recognition and Positioning" (17 citations), introduces a novel method for planning grinding trajectories on curved surfaces, significantly improving the efficiency of large aluminum alloy surface finishing by integrating weld seam recognition and defect positioning. This contribution addresses critical challenges in aerospace manufacturing, where precision and automation are paramount. In his 2025 study on surface-roughness prediction for small-batch workpieces, Xiao proposes the Response Surface Methodology-BP Neural Network (RSM-BPNN) model, enabling accurate surface quality forecasting under varying sample sizes—a key enabler for smart manufacturing. His work also extends to construction innovation, as seen in his research on Injection 3D Concrete Printing combined with vector-based graphic statics. With a growing citation record, Xiao’s research bridges robotics, materials processing, and data-driven modeling, offering practical solutions for high-precision industrial applications.
Research Focus
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Top Papers
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