Papers
4
Total Citations
21
H-Index
3
About
Weilong Huang is a leading researcher in intelligent robotic manufacturing, with a primary focus on robotic polishing and grinding processes for mold steel and curved surfaces. His work addresses critical challenges in automated surface finishing, particularly the need for precise force control and process optimization to achieve uniform, high-quality results. Huang’s major contributions include pioneering the application of the Taguchi method for parameter optimization in force-controlled robotic polishing, a study that has garnered 8 citations. He further advanced the field by developing path planning algorithms based on B-spline curves to ensure stable grinding force control, and by integrating artificial intelligence, specifically the XGBoost algorithm, to predict and optimize polishing outcomes. His research on adaptive impedance control for curved molds provides a robust solution to uneven polishing caused by surface curvature variations. With a growing citation impact, Huang’s work is instrumental in transitioning robotic finishing from manual trial-and-error to data-driven, automated precision, making him a notable figure in manufacturing robotics and surface engineering.
Research Focus
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