Yunfan Gu

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About

Yunfan Gu is a leading researcher in the automation of prefabricated construction, specializing in vision-guided robotic systems for on-site assembly. His work addresses a critical bottleneck in modern building: the labor-intensive, error-prone process of positioning and joining large prefabricated components. Gu’s major contribution lies in developing binocular vision-based guidance algorithms that enable robots to perceive, locate, and automatically assemble these components with high precision, reducing reliance on manual coordination. His most-cited paper, "Automatic assembly of prefabricated components based on vision-guided robot" (2024, 40 citations), demonstrates a practical framework for crane-integrated robotic assembly, while his follow-up work on binocular vision (2025, 5 citations) refines depth perception for complex environments. With a growing citation impact, Gu’s research is pivotal for advancing construction automation, promising safer, faster, and more accurate building processes. His achievements mark a significant step toward fully autonomous construction sites, earning recognition from both robotics and civil engineering communities.