Papers
4
Total Citations
31
H-Index
3
About
Shaowen Fu is a researcher whose work sits at the intersection of robotics, dynamics, and advanced control systems, with a particular focus on robotic bionic eyes. Fu’s most significant contribution lies in pioneering hybrid image stabilization techniques that combine mechanical motion compensation with electronic correction, addressing the critical challenge of image blurring and shaking caused by unwanted robot motion. This work is essential for precise environmental sensing in mobile robotics. Fu’s research has introduced multi-loop stabilization control structures, utilizing acceleration closed loops to improve platform accuracy, and has developed reliable pose measurement methods for robotic bionic eyes using MEMS gyroscopes combined with adaptive Kalman filters to reduce sensor noise. Notably, Fu has also engaged with foundational robotics mechanics, as evidenced by a commentary on the Newton-Euler formulation for Stewart platform dynamics. With over 30 citations across key publications, Fu’s work is establishing a foundation for more stable and perceptive robotic vision systems, making a tangible impact on the field of robotic sensing and control.
Research Focus
Key Achievements
Top Papers
- 1
- 2Hybrid Image Stabilization of Robotic Bionic Eyes4 citations · 2018
- 3Multi-loop stabilization control of a robotic bionic eyes3 citations · 2017
- 4