Papers
12
Total Citations
137
H-Index
7
About
Junde Qi is a prominent researcher specializing in robotic manufacturing, precision machining, and intelligent process control, with a particular focus on robotic belt grinding systems and industrial robot calibration. His work addresses one of the most pressing challenges in advanced manufacturing: bridging the gap between the inherent flexibility of industrial robots and the high-precision demands of modern machining applications. Qi's most influential contributions include developing novel calibration methods that integrate kinematic modeling with spatial interpolation algorithms to significantly enhance robot absolute positioning accuracy, earning 28 citations, and pioneering surface roughness prediction models for robotic belt grinding using generalized regression neural networks, cited 25 times. His research on positioning error compensation and optimized measurement space has further solidified his reputation in precision robotics. A distinctive thread running through Qi's portfolio is his sustained investigation of abrasive belt wear — encompassing quantitative evaluation, on-machine measurement using structured light scanning, and its effects on residual stress distributions in aerospace superalloys like GH4169. This comprehensive approach to understanding tool degradation reflects his commitment to real-world manufacturing reliability. With research spanning turbine blade grinding, posture optimization, and adaptive parameter planning, Qi's cumulative body of work, totaling over 130 citations, represents meaningful advances in intelligent robotic manufacturing systems.
Research Focus
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