Papers
4
Total Citations
26
H-Index
3
About
Yunfei Miao is a rising expert in the dynamics and control of industrial robots for high-precision machining, with a particular focus on mobile manipulators and composite material processing. His research centers on three interconnected challenges: dynamic parameter identification, stiffness enhancement, and chatter prediction in robotic milling systems. Miao’s major contributions include developing a novel method for identifying robot dynamic parameters using frequency response functions, which enables more accurate modeling of robotic behavior under load. He has also proposed a stiffness strengthening approach for mobile industrial robots performing in-situ milling, addressing a critical limitation of these systems. His work on multi-modal chatter prediction, which accounts for configuration-dependent dynamics, represents a significant advance in improving machining quality and stability. To date, his most cited papers have garnered 9 citations each, reflecting growing interest in his practical solutions for manufacturing automation. Miao’s research is particularly notable for its application to carbon fiber reinforced polymer (CFRP) machining, where he has developed layout optimization strategies for in-situ processing systems. His work bridges the gap between robotics theory and industrial implementation, offering engineers actionable methods to enhance robot accuracy and productivity in real-world manufacturing environments.
Research Focus
Key Achievements
Top Papers
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