Yanlong Zhu
Papers
1
Total Citations
4
H-Index
1
About
Yanlong Zhu is a researcher advancing the field of industrial robotics and precision measurement, with a focus on enhancing the reliability of robotic systems. His key research areas include robot position accuracy, uncertainty evaluation, and measurement science. Zhu’s major contribution lies in developing innovative methods for assessing measurement uncertainty in complex, data-limited scenarios. His most-cited work, "Small sample uncertainty evaluation of industrial robot position accuracy measurement based on grey model" (2024, 4 citations), introduces a novel approach using grey system theory to evaluate the uncertainty of laser tracker measurements for robot positioning—a critical step for improving manufacturing automation and quality control. This work addresses the challenge of small sample sizes, offering a robust framework for industries where extensive data collection is impractical. Though early in his citation impact, Zhu’s research bridges theoretical modeling and practical metrology, providing tools for engineers to enhance robot performance. His achievements highlight a commitment to solving real-world measurement problems, making his work valuable for students and researchers in robotics, precision engineering, and applied statistics.
Research Focus
Key Achievements
Top Papers
- 1