Xiao Jie Duan
Papers
1
Total Citations
8
H-Index
1
About
Xiao Jie Duan is a robotics researcher whose work centers on vision-guided manipulation and autonomous grasping, with a particular focus on bridging the gap between perception and action in complex, unstructured environments. Her major contribution lies in developing a closed-loop, vision-based hand–eye coordination policy that enables robotic systems to achieve both high task success rates and precise manipulation. Demonstrated through the challenging domain of Tangram puzzles—where objects vary in shape, orientation, and placement—her system showcases how real-time visual feedback can robustly guide grasping without requiring exhaustive pre-programming. This work, published in 2021 and garnering 8 citations, represents a foundational step toward more adaptive and intelligent robotic assistants. Duan’s research is particularly notable for its practical emphasis: rather than relying on idealized simulations, she tackles the messy realities of physical interaction, making her contributions directly applicable to manufacturing, logistics, and service robotics. Her approach—integrating computer vision, control theory, and robotic kinematics—offers a compelling blueprint for future systems that must operate reliably amid uncertainty.
Research Focus
Key Achievements
Top Papers
- 1