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Collaborative Research: Correlating Geospatial Data Lineage and Positional Accuracy for Excavation Damage Prevention

Collaborative Research: Correlating Geospatial Data Lineage and Positional Accuracy for Excavation Damage Prevention
合作研究:关联地理空间数据谱系和位置精度以预防开挖损坏
批准号:
1265895
负责人:
Hubo Cai
金额:
$15.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-06-01 至 2016-05-31

项目摘要

项目成果

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中文摘要
翻译
本研究的目的是探索与记录的地下公用事业位置数据相关的不确定性建模和量化的方法。位置不确定性是与地下公用设施测绘方法相关的误差,将被建模为三维几何形状,与这些形状包含公用设施的概率相对应。位置的不确定性依赖于位置的准确性,这将从数据沿袭(用于收集数据的格式和过程)中估计出来。与本研究相关的前提是,位置不确定性源于不准确的位置信息,而不准确的位置信息又是数据谱系的函数。公用事业数据及其量化的不确定性将与挖掘作业相结合,并通过使用视频可视增强现实将几何形状和属性信息与操作员对工作环境的看法相结合,传达给操作员。现场试验将与行业合作伙伴一起进行,以验证所提出的地理空间不确定性模型,并评估其提高挖掘安全的效益。如果成功,研究结果将导致施工作业的改进,例如,在存在埋藏公用设施的情况下进行挖掘,在存在隐藏障碍物的情况下进行钻孔,以及在没有准确先验环境知识的情况下进行机器人施工。该项目将通过促进地下公用事业工程作为一个专业领域来影响教育。通过与普渡大学和密歇根大学的女性科学与工程以及少数族裔工程项目办公室的积极合作,一个多元化的未被充分代表的学生群体将参与该项目。总之,该项目的社会效益预计将是提高挖掘和其他施工作业的安全性,以及在新兴的工程专业中对当前和未来的工程师进行多学科教育和培训。
英文摘要
The objective of this research is to explore methods that model and quantify the uncertainty associated with recorded underground utility location data. Locational uncertainty is the error associated with the methods of mapping underground utilities, and will be modeled as three-dimensional geometric shapes that correspond to the probability that these shapes contain the utilities. Locational uncertainty is dependent on locational accuracy, which will be estimated from data lineage - the format and process used to collect data. The premise associated with this research is that locational uncertainty results from inaccurate locational information that, in turn, is a function of data lineage. The utility data and its quantified uncertainty will be integrated with excavation operations, and communicated to operators by blending the geometry and attribute information with operators' views of the work environment using video-see-through augmented reality. Field experiments will be conducted with industry partners to validate the proposed geospatial uncertainty model and evaluate its benefits of improving excavation safety.If successful, the research results will lead to improvements in construction operations such as, excavation in the presence of buried utilities, drilling in the presence of hidden obstructions, and robotic construction in the absence of exact prior knowledge of the environment. The project will impact education by promoting subsurface utility engineering as an area of specialization. A diverse group of under-represented students will participate in the project through active collaboration with the Women in Science and Engineering, and the Minority Engineering Program offices at Purdue and the University of Michigan. In summary, the societal benefits of the project are expected to be the improved safety of excavation and other construction operations, and the multi-disciplinary education and training of current and future engineers in an emerging engineering specialty.
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会议论文
PFI-TT: Development of a Mapping and Visualization System to Inform Excavators of Buried Utility Pipes
  • 批准号:
    2213750
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.0万
  • 财政年份:
    2022
  • 负责人:
    Hubo Cai
  • 依托单位:
Mapping the Underworld of Buried Utilities - A Hybrid Sensing Approach
  • 批准号:
    1462638
  • 项目类别:
    Standard Grant
  • 资助金额:
    $21.65万
  • 财政年份:
    2015
  • 负责人:
    Hubo Cai
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
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