Papers
39
Total Citations
607
H-Index
15
About
Zhaoheng Liu is a distinguished researcher whose work sits at the intersection of robotics, manufacturing engineering, and structural dynamics. His research has made substantial contributions to robotic machining processes — particularly robotic grinding and milling — with a sustained focus on improving precision, stability, and process monitoring in industrial automation. Liu's most influential contributions include pioneering work on depth-of-cut prediction for robotic belt grinding (64 citations) and developing image-processing-based tool wear monitoring systems (46 citations), both of which address critical challenges in automating surface finishing operations. His investigation into chatter stability during high-speed robotic milling (39 citations) has helped clarify longstanding debates about whether classical regenerative chatter theory applies to flexible robotic systems — a question with major practical implications for aerospace and automotive manufacturing. A recurring theme across his body of work is the dynamic behavior of robotic structures. His studies on flexible-joint manipulator vibration, harmonic drive torsional stiffness, and hexapod machining platforms reflect a deep commitment to understanding mechanical compliance in robotic systems. His modal analysis and system identification research further underscores this expertise. Collectively accumulating over 350 citations, Liu's work provides both theoretical foundations and practical tools for the next generation of intelligent robotic manufacturing.
Research Focus
Key Achievements
Top Papers
- 1Prediction of depth of cut for robotic belt grinding64 citations · 2016
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