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Unmanned aerial vehicle based visualization of deep excavations using game engines
Date
2016
Author
Teke, Türker
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In the last two decades, the advancements in monitoring tools and growing use of information technologies lead to better visualization of construction sites. The challenge in this field is to develop an extensively capable tool for safety check, progress monitoring and quality control. In this sense, Geotechnical Engineers need a comprehensive understanding of field conditions, which includes topography, soil conditions, effect of nearby structures, etc. In this study, game engines are proposed as visualization tools to interact with the site on a virtual environment formed by the images taken by Unmanned Aerial Vehicles (UAVs). Deep excavations are chosen as test cases where catastrophic failures can be prevented by taking measures according to monitoring activities. In addition, reaching to deep levels in the excavations for quality assurance is always a challenge at the construction site. To overcome such challenges, UAVs with various sensors are used to capture images of the site. In this study, as photographs inherently lack geometric information and does not provide a full imagery, Structure From Motion and Multi View Stereo algorithms are proposed to create a highly dense and colored point cloud. As the cloud may not be interactive enough for inspection, it is further processed through meshing, then imported as a scene into a virtual world via game engines to provide an interactive environment for the engineers. The developed product is successfully tested on two deep excavation sites located in Ankara, Turkey. Promising results show that the game produces sufficient details of construction and topography, which provides engineers a way to investigate the excavation. The study has immense future possibilities such that the developed tool can be employed in educating the engineers, and can be integrated with the current software tools to make them more capable.
Subject Keywords
Excavation.
,
Computer vision.
,
Construction industry.
URI
http://etd.lib.metu.edu.tr/upload/12620488/index.pdf
https://hdl.handle.net/11511/25924
Collections
Graduate School of Natural and Applied Sciences, Thesis
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T. Teke, “Unmanned aerial vehicle based visualization of deep excavations using game engines,” M.S. - Master of Science, Middle East Technical University, 2016.