Papers
7
Total Citations
321
H-Index
6
About
Zepeng Li is a leading researcher in robotic machining, whose work is fundamentally reshaping how complex parts are milled with industrial robots. His primary research areas include robotic milling dynamics, chatter suppression, and posture planning for precision manufacturing. Li’s major contributions lie in tackling the core challenges of robotic milling—namely, the structural flexibility and posture-dependent stiffness that cause regenerative chatter and force-induced errors. His highly cited 2021 review (186 citations) systematically outlined these challenges and future trends, serving as a cornerstone for the field. He pioneered methods like the virtual repulsive potential field algorithm for posture trajectory planning and the force-induced error index (FEI) for configuration optimization, directly improving machining accuracy. Li also advanced the understanding of robot structural modes and chatter stability boundaries, developing operational impact excitation methods to identify dynamic compliance in movement states. With over 320 total citations, his work bridges the gap between theoretical dynamics and practical robotic manufacturing, offering self-adaptive agents and flexible posture planning that enable high-precision, efficient milling of large structural parts—a critical achievement for modern aerospace and automotive industries.
Research Focus
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