Papers
2
Total Citations
40
H-Index
2
About
Xiang Qu is an emerging researcher specializing in robotic manufacturing and precision machining, with a particular focus on the complex challenges of robotic milling processes. His work sits at the intersection of robotics, machining dynamics, and manufacturing optimization — a field critical to advancing automated industrial production. Qu's most notable contribution, published in 2023, addresses profile error-oriented optimization of end-effector feed direction and posture during robotic free-form milling, a technically demanding problem that has garnered 32 citations in a short period, signaling strong community interest. This work provides practical frameworks for improving dimensional accuracy in complex surface machining tasks performed by industrial robots. His subsequent 2024 study on chatter stability in robotic milling — examining the nuanced influence of low-frequency vibrations across three directional axes — further deepens understanding of one of the most persistent challenges in robotic machining: structural vibration and its effect on surface quality and tool life. Together, these contributions position Qu as a focused and productive voice in robotic machining research, offering both theoretical insights and engineering solutions relevant to researchers, automation engineers, and advanced manufacturing practitioners seeking to push the boundaries of robotic precision machining.
Research Focus
Key Achievements
Top Papers
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