Yu-Lun Hsu
Papers
1
Total Citations
3
H-Index
1
About
Yu-Lun Hsu is a robotics researcher whose work centers on mobile robot localization and sensor integration, with a particular focus on optical flow sensing. His major contribution lies in developing calibration methods and computational algorithms that integrate data from multiple optical flow sensors to improve robot positioning accuracy. By using multiple optical flow sensors as an alternative to traditional wheel encoders, Hsu’s approach effectively reduces measurement uncertainties, enabling more reliable localization in environments where wheel slippage or uneven terrain can compromise performance. His 2008 paper, "Calibration and Data Integration of Multiple Optical Flow Sensors for Mobile Robot Localization," has accumulated 3 citations, reflecting its foundational role in sensor fusion for mobile robotics. While his citation count is modest, the work addresses a critical challenge in autonomous navigation—achieving robust odometry without relying solely on wheel-based sensors. Hsu’s research is particularly valuable for students and engineers working on low-cost, vision-based localization systems for robots operating in unstructured or indoor environments. His contributions underscore the importance of sensor redundancy and calibration in advancing practical mobile robotics.
Research Focus
Key Achievements
Top Papers
- 1