课题基金 / 基金详情

MRI: Acquisition of Hovermap Rapid Data Capture and 3D Imaging of GPS-Denied Spaces

MRI: Acquisition of Hovermap Rapid Data Capture and 3D Imaging of GPS-Denied Spaces
MRI:获取 Hovermap 快速数据捕获和 GPS 遮挡空间的 3D 成像
批准号:
2117877
负责人:
Holley Moyes
金额:
$10.17万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-09-01 至 2023-05-31

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中文摘要
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英文摘要
Over the past decade there has been a revolution in survey and mapping with the advent of LiDAR imaging technology. LiDAR scanners mounted on Unmanned Aerial Vehicles (UAVs) offer a method of rapid data capture that creates detailed regional images of anthropogenic and natural landscapes to generate high-resolution relief models of ground surfaces. While this method has radically changed the imaging of terrestrial environments, these systems often require Global Positioning System guidance systems to fly and navigate. Contexts described as GPS-denied, which include subterranean spaces such as caves, rockshelters, mines, or building interiors, have seen limited use of LiDAR/UAV technologies due to this limitation. The instruments currently used to create 3D images of interior spaces such as total stations or scanners are often impractical in rugged environments and cannot be employed in tight or hard to reach places. Yet, these types of sites are often under threat of destruction and cultural heritage loss. With the development of new technologies, it is now possible to record and create 3D reconstructions of these sites as they exist today, not only enabling greater capacities for research, but ensuring that they will be digitally preserved for the future. This MRI project is initiated by the University of California, Merced (UCM) and the Qualcomm Institute at the University of California, San Diego. UCM is a Hispanic Serving Institution (HSI) and one of few Ph.D.-granting HSIs nationwide. The acquisition of a Hovermap system leverages the leadership role played by UCM in innovative deployments of UAV technology in environmental monitoring, natural resource management, precision agriculture, and student training . Models of GPS-denied environments are produced for use in disciplinary and multidisciplinary collaborative laboratory research projects. Opportunities for education include student training in the field and classroom as well as student research and internship opportunities. Projects engage the digital preservation of archaeological sites under threat as well as management of heritage sites both nationally and internationally. This award supports the acquisition of the Emescent Hovermap system, a hand-held and UAV-based Light Detection and Ranging Velodyne LiDAR with a proprietary SLAM (simultaneous localization and mapping) and processing system. Designed for the mining industry, the Hovermap is a robust tool that enables rapid capture and visualization of complex topologies. This new technology allows for multiple on-demand surveys and on-the-fly opportunistic data collection that builds capacity for the rapid capture of complex subterranean/indoor contexts such as caves, rockshelters, or building interiors as well as terrestrial landscapes and surface architecture, producing representations for employment in research that depends on accurate spatial data capture and imaging. The system allows for progressive LiDAR scanning while walking through constricted or confined spaces with the unit in hand, with plug-and-play transition to drone-based scanning as terrain and environments require. The system has propriety software that will stitch multiple images from each modality creating a high resolution 3D image with colorization.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(1)
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科研奖励(0)
会议论文
Rapid scanning of large caves and cave floor basemap generation from a 3D point cloud: a case study of Las Cuevas, Belize
从 3D 点云快速扫描大型洞穴并生成洞穴底图:伯利兹拉斯奎瓦斯的案例研究
DOI: --
发表时间: 2023
期刊: ISPRS annals of the photogrammetry remote sensing and spatial information sciences
影响因子: --
作者: [Lozano Bravo, H., Lo, E., Moyes, H., Montgomery, S, Kuester, F.]
通讯作者: Kuester, F.
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