Zhong Gen Su
Papers
2
Total Citations
8
H-Index
2
About
Zhong Gen Su is a leading researcher in intelligent robotics, specializing in autonomous manipulation, robotic grasping, and computer vision for industrial automation. His work addresses critical challenges in logistics and manufacturing by developing systems that enable robots to handle complex, unstructured environments. Su’s major contributions include the creation of a hybrid robotic gripper and vision-based grasp planning system for autonomous bin-picking, which significantly reduces manual labor in logistics by efficiently grasping cluttered packages of varying materials and shapes. This work, published in 2025, has already garnered 6 citations for its practical impact. He also pioneered AffPose, an innovative RGB-based framework that simultaneously performs pose estimation and affordance detection for robotic tool manipulation. This breakthrough allows robots to semantically understand tool functions and precisely localize them, overcoming the limitations of conventional RGB-D methods. With 2 citations since its 2025 publication, AffPose represents a significant step toward human-like tool use in robotics. Su’s research is highly influential, offering scalable solutions that bridge the gap between perception and action in real-world robotic applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2