Yufeng Ding

Papers

Total Citations

101

H-Index

About

Yufeng Ding is a leading researcher in intelligent robotic manufacturing, with a primary focus on force control and adaptive automation for surface polishing. His work addresses a critical challenge in industrial robotics: maintaining stable, constant contact force during the automated polishing of complex, concave curved surfaces. In his highly cited 2018 paper (54 citations), Ding proposed a novel method for industrial robot polishing that significantly improves surface quality by ensuring consistent pressure, a breakthrough for precision manufacturing. Building on this, his 2022 study (47 citations) introduced an innovative approach combining impedance control with reinforcement learning, enabling polishing robots to autonomously learn and optimize force parameters for enhanced stability and efficiency. This work represents a major step toward fully intelligent, self-optimizing robotic systems. With a combined impact of over 100 citations on these foundational studies alone, Ding’s research is shaping the future of automated surface finishing, offering practical solutions for industries requiring high-precision, defect-free surfaces. His contributions are essential reading for students and engineers advancing force-controlled robotics and intelligent manufacturing.