Lin-Lin Chen
Papers
1
Total Citations
3
H-Index
1
About
Lin-Lin Chen is a researcher specializing in robotics, sensor fusion, and intelligent automation systems. Their most notable contribution lies in advancing hand-eye calibration technology for intelligent picking robots, a critical area for improving precision in automated manufacturing and logistics. In their 2021 study, Chen developed a novel approach using multiple photoelectric sensors for information fusion, which constrains the movement of robot end-effectors and cameras to construct accurate hand-eye equations. This work directly addresses the challenge of pose estimation in robotic manipulation, enhancing the reliability of vision-guided systems. While their most-cited paper has garnered 3 citations, reflecting its specialized and emerging nature, Chen’s research demonstrates a focused effort to integrate sensor data for real-world robotic applications. Their work contributes to the broader field of intelligent robotics, particularly in tasks requiring high precision, such as picking and assembly. Chen’s methodology—combining mathematical modeling of hand-eye calibration with practical sensor fusion—offers a foundation for future innovations in autonomous systems, making their research valuable for students and engineers exploring sensor-driven robotics.
Research Focus
Key Achievements
Top Papers
- 1