arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2106.03797cs.CVcs.AIcs.HC

Drone-based AI and 3D Reconstruction for Digital Twin Augmentation

University of Sydney(悉尼大学);Aviation Virtual Pte Ltd(Aviation Virtual私人有限公司);Singapore Institute of Technology(新加坡理工大学);University of Glasgow(格拉斯哥大学)

Alex To, Maican Liu, Muhammad Hazeeq Bin Muhammad Hairul, Joseph G. Davis, Jeannie S. A. Lee, Henrik Hesse, Hoang D. Nguyen

英文摘要:

Digital Twin is an emerging technology at the forefront of Industry 4.0, with the ultimate goal of combining the physical space and the virtual space. To date, the Digital Twin concept has been applied in many engineering fields, providing useful insights in the areas of engineering design, manufacturing, automation, and construction industry. While the nexus of various technologies opens up new opportunities with Digital Twin, the technology requires a framework to integrate the different technologies, such as the Building Information Model used in the Building and Construction industry. In this work, an Information Fusion framework is proposed to seamlessly fuse heterogeneous components in a Digital Twin framework from the variety of technologies involved. This study aims to augment Digital Twin in buildings with the use of AI and 3D reconstruction empowered by unmanned aviation vehicles. We proposed a drone-based Digital Twin augmentation framework with reusable and customisable components. A proof of concept is also developed, and extensive evaluation is conducted for 3D reconstruction and applications of AI for defect detection.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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