Caihong Su
Papers
1
Total Citations
3
H-Index
1
About
Caihong Su is a leading researcher in the field of robotic manipulation, with a particular focus on the intersection of computer vision and tactile sensing. Her work centers on enabling robots to interact with deformable objects—such as fabrics, food items, or soft tissues—by developing novel sensor fusion techniques. In her most-cited paper, "Vision-Tactile Fusion Based Detection of Deformation and Slippage of Deformable Objects During Grasping" (2023), Su introduced a groundbreaking framework that integrates visual data with tactile feedback to detect subtle deformations and slippage in real time. This contribution is critical for advancing robotic dexterity in unstructured environments, from automated manufacturing to surgical assistance. Though early in her career, her work has already garnered attention, with 3 citations to this key paper, signaling its growing impact. Su’s achievements include pioneering methods that bridge the gap between high-level visual perception and low-level tactile sensing, offering a pathway toward more adaptive and safe robotic grasping. Her research is essential reading for students and engineers seeking to understand the future of human-robot interaction and soft object handling.
Research Focus
Key Achievements
Top Papers
- 1