Papers
2
Total Citations
17
H-Index
2
About
Le Fan is a robotics researcher specializing in industrial robot calibration and intelligent welding control systems. Her primary research focuses on enhancing the absolute positional accuracy of 6-degree-of-freedom articulated industrial robots, a critical challenge for flexible manufacturing and precision parts fabrication. In her most cited work, "The parameter identification model considering both geometric parameters and joint stiffness" (2019, 15 citations), Fan developed a novel model that simultaneously accounts for geometric and non-geometric parameters—such as joint stiffness—to improve robot positioning accuracy. This contribution addresses a key limitation in industrial robotics, where both parameter types significantly affect performance. Fan has also contributed to the advancement of intelligent welding systems, as demonstrated in her work on "Software Realization of Gantry Welding Robot Control System with PC+ Soft NC Mode" (2018), which explores flexible, standardized numerical control architectures for automated welding. Her research bridges the gap between theoretical parameter identification and practical industrial applications, supporting the development of more precise and adaptable robotic systems for modern manufacturing environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2