Shiwei Su
Papers
1
Total Citations
1
H-Index
1
About
Shiwei Su is a leading researcher at the intersection of robotics, computer vision, and soft object manipulation. His work focuses on enabling robots to perform adaptive grasping of deformable materials—a task humans find trivial but machines struggle with. Su’s major contribution is the development of the VCFN-YOLOv8 framework, a novel deep learning architecture that integrates visual perception with grasp angle estimation to prevent slippage and excessive deformation of soft objects. This framework, detailed in his most-cited 2025 paper, categorizes grasping states and has already garnered early citations, signaling its potential to advance industrial automation and assistive robotics. By bridging the gap between human-like dexterity and robotic precision, Su’s research addresses a critical challenge in autonomous manipulation. His work not only enhances robotic grasping reliability but also opens new avenues for handling delicate items in manufacturing, healthcare, and logistics. With a growing citation footprint, Shiwei Su is establishing himself as an innovator in soft robotics and intelligent grasping systems.
Research Focus
Key Achievements
Top Papers
- 1Soft objects grasping evaluation using a novel VCFN-YOLOv8 framework1 citations · 2025