Yuanfan
Papers
1
Total Citations
3
H-Index
1
About
Yuanfan’s research focuses on precision robotics and automated manufacturing, with a particular emphasis on improving accuracy in aircraft assembly processes. Their most cited work introduces an auto-normalization algorithm for robotic drilling systems, addressing a critical challenge in aerospace manufacturing: achieving precise alignment between the drill spindle and the surface normal vector of aircraft components. Yuanfan developed a novel approach using four laser displacement sensors mounted on a multi-functional end effector to measure deviations in real time. By solving for the robot’s target orientation through an inverse algorithm, they enabled simultaneous correction of pitch and yaw rotations around the tool center point, ensuring the spindle axis aligns with the surface normal. Experimental validation using a laser tracker demonstrated that residual deviations were reduced to less than 0.5°, a significant improvement for high-stakes assembly tasks. Although this foundational paper has accumulated 3 citations, its impact lies in advancing robotic precision for safety-critical industries. Yuanfan’s work exemplifies the integration of sensor feedback and control algorithms to enhance automation reliability, offering practical solutions for complex manufacturing environments.
Research Focus
Key Achievements
Top Papers
- 1