Yongpeng Tang
Papers
4
Total Citations
61
H-Index
4
About
Yongpeng Tang is a leading researcher at the intersection of intelligent manufacturing, robotics, and digital twin technology. His work focuses on revolutionizing industrial automation through advanced robotic measurement and grasping systems. Tang’s most significant contribution is the development of a digital twin-based intelligent robotic measurement framework for freeform surface parts, which dramatically improves the efficiency, autonomy, and intelligence of inspection processes—a paper that has garnered 23 citations since 2023. He has also advanced industrial robotic grasping with a robust pixel-wise prediction network for textureless parts, achieving 17 citations for its novel approach to 6D pose estimation. His comprehensive review on key technologies and trends in active robotic 3D measurement (2024, 12 citations) has become a go-to resource for researchers in smart manufacturing. Additionally, Tang’s work on viewpoint planning using visibility cone space exploration (2023, 9 citations) addresses critical challenges in measuring complex geometries. Through these contributions, Tang is shaping the future of autonomous, high-precision robotic systems for Industry 4.0 applications.
Research Focus
Key Achievements
Top Papers
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