Sujing Qin
Papers
1
Total Citations
2
H-Index
1
About
Sujing Qin is a researcher specializing in precision manufacturing and robotic automation, with a particular focus on sensor-based calibration and machining processes. Her work addresses critical challenges in robotic grinding, where accurate 3D coordinate system calibration is essential for high-quality surface finishing. Her most-cited paper, "Dimensionality reduction calibration of a robotic grinding head’s 3D coordinate system using a 1D laser sensor" (2025), introduces an innovative method that simplifies complex calibration tasks by reducing dimensionality, enabling efficient and precise alignment with minimal sensor input. This approach has practical implications for improving the accuracy and reliability of robotic grinding in industrial applications, reducing setup time and cost. While her citation count is still growing, her work contributes to the broader field of intelligent manufacturing and sensor integration. Qin’s research is particularly valuable for engineers and researchers seeking to enhance robotic precision through cost-effective, streamlined calibration techniques. Her contributions highlight the potential of dimensionality reduction strategies in advancing automated manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1