Papers
5
Total Citations
113
H-Index
5
About
Chang Yong is a leading researcher in field robotics, specializing in autonomous inspection systems for critical infrastructure. His work centers on developing wall-climbing robots that integrate deep learning and 3D metric measurement to detect and quantify concrete defects such as cracks and spalling. His most-cited paper, "Automated wall‐climbing robot for concrete construction inspection" (2022, 59 citations), introduces a robot that enhances construction quality control and infrastructure sustainability. A related study, "Deep Neural Network based Visual Inspection with 3D Metric Measurement of Concrete Defects using Wall-climbing Robot" (2019, 24 citations), demonstrates a system that combines RGB-D data with neural networks for precise defect assessment. Beyond concrete inspection, Yong has contributed to power line maintenance with an insulator cleaning robot (2015, 10 citations) and to healthcare robotics with a foot massage robot based on Chinese massage therapy (2016, 9 citations). His early work on kinematic modeling of wheeled mobile robots (2010, 11 citations) laid foundational principles for his later innovations. With a portfolio spanning construction, energy, and biomedical applications, Yong’s research significantly advances robotic solutions for real-world challenges, making him a key figure in applied robotics.
Research Focus
Key Achievements
Top Papers
- 1Automated wall‐climbing robot for concrete construction inspection59 citations · 2022
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- 3Method of Kinematic Modeling of Wheeled Mobile Robot11 citations · 2010
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