Xinghua Qu
Papers
7
Total Citations
154
H-Index
5
About
Xinghua Qu is a prominent researcher specializing in precision measurement, industrial robotics, and advanced sensing technologies. His work sits at the intersection of metrology and automation, with a particular focus on enhancing the accuracy and intelligence of robotic systems in industrial environments. Qu's most impactful contributions address a fundamental challenge in modern manufacturing: improving the absolute positional accuracy of industrial robots. His 2015 paper on multi-sensor combined measurement and data fusion, garnering 50 citations, introduced an innovative framework integrating visual and angle sensors to correct robot manipulator pose errors in real time. Building on this, his 2016 work on laser tracker-based online path compensation (48 citations) provided practical solutions for deploying robots in high-precision applications previously beyond their capability. His research on coordinate transformation methods (28 citations) further streamlined industrial calibration workflows. Qu's earlier work explored laser-guided measurement robots and a novel wheel-legged climbing robot, demonstrating broad engineering versatility. His more recent research into FMCW LiDAR reflects his continued engagement with cutting-edge sensing technologies for dynamic industrial measurement. Collectively, his publications have accumulated over 150 citations, establishing him as a meaningful contributor to the fields of robotic calibration, large-scale metrology, and intelligent manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4Design and CAD-directed inspection planning of laser-guided measuring robot14 citations · 2008
- 5
- 6Design and Motion Analysis of Wheel-Legged Climbing Robot4 citations · 2006
- 7Inspection planning control of laser guided measurement robot2 citations · 2008