Kewen Tang
Papers
1
Total Citations
3
H-Index
1
About
Kewen Tang is a robotics researcher whose work centers on machine vision and intelligent manipulation systems. His key research areas include real-time object recognition, corner detection algorithms, and their integration into robotic control frameworks. Tang’s most notable contribution is a corner detection-based strategy for workpiece recognition, which provides critical visual cues for robot manipulation tasks. This approach addresses a fundamental challenge in robotics: enabling machines to accurately identify and interact with objects in dynamic environments. His 2017 paper, "Corner detection based real-time workpiece recognition for robot manipulation," has accumulated 3 citations, reflecting its targeted impact within the robotics and computer vision communities. While the citation count is modest, the work is significant for its practical application in industrial automation, where reliable workpiece identification is essential for tasks like assembly and sorting. Tang’s research bridges the gap between low-level image processing and high-level robotic decision-making, offering a computationally efficient solution that enhances robot autonomy. His contributions are particularly valuable for researchers and engineers developing vision-guided robotic systems for manufacturing and logistics.
Research Focus
Key Achievements
Top Papers
- 1