Fangzhou Lin
Papers
1
Total Citations
18
H-Index
1
About
Fangzhou Lin is a leading researcher at the intersection of robotics, building information modeling (BIM), and automated infrastructure inspection. His work focuses on developing intelligent systems that bridge the gap between physical construction sites and digital twins, with a particular emphasis on leveraging quadruped robots for real-world data capture. Lin’s most notable contribution is his 2024 paper, “Automated reality capture for indoor inspection using BIM and a multi-sensor quadruped robot,” which has already garnered 18 citations for its pioneering integration of legged locomotion with multi-sensor payloads—such as LiDAR and cameras—to autonomously generate as-built BIM models. This work addresses critical challenges in construction quality control and facility management by enabling robots to navigate complex indoor environments without human intervention. By combining robust robotic hardware with advanced perception algorithms, Lin has demonstrated a scalable solution for reducing manual inspection costs and improving data accuracy. His research is widely recognized for its practical impact, offering a blueprint for future autonomous inspection systems in the architecture, engineering, and construction (AEC) industry.
Research Focus
Key Achievements
Top Papers
- 1