Yaqiu Liu
Papers
1
Total Citations
2
H-Index
1
About
Yaqiu Liu is a researcher focused on advancing precision robotics and manufacturing automation, with a particular emphasis on kinematic modeling and calibration for industrial manipulators. Their most-cited work, "Research on SDH Model Calibration Algorithm for Robotic Arm Based on Differential Transform" (2022), addresses a critical challenge in modern manufacturing: improving the accuracy of robotic arms through refined calibration techniques. By integrating the Standard Denavit-Hartenberg (SDH) model with differential transform methods, Liu’s research enhances the positional precision of industrial robots, directly supporting the growing demand for higher-quality, more reliable automation in manufacturing. This contribution is especially relevant as industries push for greater efficiency and functionality in robotic systems. While their citation count is currently modest, the work signals a foundational step toward more robust calibration algorithms. Liu’s research aligns with the broader trend of data-driven optimization in robotics, offering practical solutions for real-world industrial applications. Their focus on bridging theoretical modeling with applied calibration techniques positions them as a contributor to the next generation of smarter, more accurate manufacturing tools.
Research Focus
Key Achievements
Top Papers
- 1