Chaoqun Wu

Wuhan University of Technology

Papers

7

Total Citations

119

H-Index

7

About

Chaoqun Wu is a leading researcher in intelligent manufacturing and robotic automation, with a focus on welding and machining systems. His work centers on laser vision sensing, arc voltage control, and the digitization of industrial processes. Wu’s major contributions include developing a teaching-free welding position guidance method for fillet welds, which eliminates complex manual calibration and enhances efficiency—a paper that has garnered 27 citations. He also advanced tube-to-tubesheet welding by integrating automation with digitization, addressing challenges in circular seam arc length control through arc voltage sensing, a critical innovation for improving weld quality in dense seam configurations. His research extends to robotic machining, where he proposed a region-based framework for intelligent manufacturing, and to abrasive belt grinding of zirconia ceramics, using chip-thickness models to suppress crack initiation and propagation. With over 100 total citations across his most-cited works, Wu’s impact is evident in his practical solutions for calibration, path planning, and foot contact detection in wheel-legged robots. His work bridges theory and application, making him a key figure in advancing robotic precision and autonomy in manufacturing.

Research Focus

Key Achievements

7
H-Index
7
Papers
119
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
A teaching-free welding position guidance method for fillet weld based on laser vision sensing and EGM technology
27 citations · 2022
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 22
🏛 Institutions: Wuhan University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago