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Quality control and progress monitoring from large-scale 3D point clouds

Quality control and progress monitoring from large-scale 3D point clouds
通过大规模 3D 点云进行质量控制和进度监控
批准号:
580274-2022
负责人:
Lalonde, JeanFrançoisJF
金额:
$2.15万
依托单位:
依托单位国家:
加拿大
项目类别:
Alliance Grants
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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中文摘要
翻译
新型3D传感器的出现显然标志着基础设施和建筑业的一场革命,但它们也伴随着一系列问题。总结其中大多数问题的最简单方法之一是强调收集和使用数据之间的重要区别。建筑和基础设施公司面临的主要问题已从数据采集转向数据解释。这种转变的一个例子是竣工与设计的比较。仅仅是对齐这些3D模型(CAD模型和高密度点云)的任务是具有挑战性的,因为在任何真实的3D捕获中都不可避免地会出现不完整、噪声、差异和遮挡。此外,CAD模型和点云之间可能存在结构差异(这是比较它们的点),这使得它们的对准更加复杂。本项目的主要目标是为工程师、建筑师、设计师、检查员、测量员和其他专业人员提供工具,帮助他们完成与开发这些新传感器和技术相关的繁琐和耗时的任务。通过设计能够智能地清理、预处理和解释嵌入在特定专业环境中的原始点云中的3D表示的系统,甚至在潜在的问题发生之前指出潜在的问题,并产生有用的抽象以更好地评估情况,将有可能减少工作负荷并提高监督建筑工地的专业人员的效率。反过来,这将导致成本降低和新的可能性,如更频繁的调查,增加及早发现错误的机会,并降低成本和时间超支的风险。这也可能对工人的安全和保障产生影响。
英文摘要
The advent of new 3D sensors clearly marks a revolution for the infrastructure and construction industry, but they also come with their own set of issues. One of the simplest ways to summarize most of these is by stressing the important distinction between gathering and using data. The main problem faced by construction and infrastructure companies has shifted from data acquisition to data interpretation. One example of such a transition is the as-built vs. as-design comparison. The mere task of aligning these 3D modalities (CAD models and high density point clouds) is challenging because of the incompleteness, noise, discrepancies, and occlusions that inevitably occur in any real-world 3D capture. In addition, there may exist structural differences between the CAD model and the point cloud (that is the point of comparing them), which further complicates their alignment.The main goal of this project is to provide tools to engineers, architects, designers, inspectors, surveyors, and other professionals to assist them in tedious and time-consuming tasks related to the exploitation of those new sensors and techniques. By designing systems able to intelligently clean, pre-process and interpret a 3D representation embedded in a raw point cloud within specific professional contexts, to point out potential problematic situations before they even occur, and to produce helpful abstractions to better assess a situation, it will be possible to reduce the workload and improve the efficiency of the professionals overseeing construction sites. In turn, this will lead to cost reductions and new possibilities such as more frequent surveys, increasing the chances of early error catching and reducing the risk of cost and time overruns. This could also have an impact on the safety and security of workers.
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