Guoyong Yang

University of Chinese Academy of Sciences, Shenyang Institute of Automation

Papers

Total Citations

143

H-Index

About

Guoyong Yang is a pioneering researcher at the intersection of robotics, computer vision, and civil infrastructure inspection. His work focuses on developing autonomous robotic systems capable of assessing the structural health of concrete infrastructure — a critical challenge as aging buildings and bridges demand more sophisticated, scalable monitoring solutions. Yang's most significant contribution is the development of wall-climbing robots equipped with advanced sensing and AI capabilities for concrete inspection. His 2022 paper introducing an automated wall-climbing robot for construction inspection has already garnered 59 citations, reflecting strong community interest in replacing dangerous, labor-intensive manual surveys with intelligent robotic alternatives. Earlier work established the foundational systems, including a robotic platform for building spalling and crack databases (34 citations) and a wall-climbing robot integrating both visual and ground-penetrating radar (GPR) inspection capabilities (26 citations). A hallmark of Yang's research is his integration of deep neural networks with 3D metric measurement, enabling robots to not only detect surface defects like cracks and spalling but precisely quantify them — a leap toward actionable, data-driven structural health monitoring. With over 140 cumulative citations across his key works, Yang's research is shaping the future of smart infrastructure inspection and construction robotics.