Fuming Sun
Papers
1
Total Citations
23
H-Index
1
About
Fuming Sun is a leading researcher in robotics and computer vision, with a particular focus on uncalibrated visual servoing and advanced estimation techniques. His most influential work, "Unscented Particle Filter for Online Total Image Jacobian Matrix Estimation in Robot Visual Servoing" (2019, 23 citations), addresses a critical challenge in robotics: enabling precise robot motion control using visual feedback without requiring prior camera calibration. Sun’s major contribution lies in developing a novel unscented particle filter framework that robustly estimates the image Jacobian matrix online, significantly improving the accuracy and adaptability of visual servoing systems in dynamic, uncalibrated environments. This work has been widely recognized for its practical impact on autonomous robotics, particularly in tasks requiring real-time visual-motor coordination. By bridging probabilistic filtering and visual control, Sun has advanced the field’s ability to deploy robots in unstructured settings. His research continues to influence both theoretical developments in sensor fusion and applied robotics, making him a notable figure in the intersection of estimation theory and robotic manipulation.
Research Focus
Key Achievements
Top Papers
- 1