Cheng Yuan
Papers
2
Total Citations
88
H-Index
2
About
Dr. Cheng Yuan is a leading researcher at the intersection of robotics, computer vision, and structural health monitoring. His primary contributions lie in developing intelligent inspection systems that leverage deep learning and stereo vision to automate the assessment of critical infrastructure. Dr. Yuan’s most impactful work, “A novel intelligent inspection robot with deep stereo vision for three-dimensional concrete damage detection and quantification” (2021), has garnered 86 citations, establishing a new paradigm for moving beyond traditional 2D damage analysis. By enabling robots to perceive and quantify cracks in three dimensions, his research significantly enhances the efficiency, accuracy, and safety of routine maintenance for reinforced concrete structures. This work addresses a critical need in civil engineering, where manual inspection is often dangerous and time-consuming. Dr. Yuan’s broader expertise in object recognition, demonstrated through his work on platforms like the iCub robot, further underscores his commitment to advancing autonomous systems capable of interacting with and understanding their physical environment. His pioneering fusion of robotics and deep vision is paving the way for smarter, more resilient infrastructure management.
Research Focus
Key Achievements
Top Papers
- 1
- 2Object Recognition on iCub Robot2 citations · 2017