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: University of California - Merced
• 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
• 起止时间: 2021-09-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2117877&HistoricalAwards=false
• 关键词: MRI; Acquisition; Hovermap; Rapid; Data

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.

在过去的十年里，随着激光雷达成像技术的出现，测绘领域发生了一场革命。安装在无人机（uav）上的激光雷达扫描仪提供了一种快速数据捕获方法，可以创建人为和自然景观的详细区域图像，从而生成地面的高分辨率浮雕模型。虽然这种方法从根本上改变了陆地环境的成像，但这些系统通常需要全球定位系统的制导系统来飞行和导航。由于这种限制，被描述为gps拒绝的环境，包括地下空间，如洞穴、岩石掩体、矿山或建筑物内部，激光雷达/无人机技术的使用有限。目前用于创建内部空间3D图像的仪器，如全站仪或扫描仪，在恶劣的环境中通常是不切实际的，不能在狭窄或难以到达的地方使用。然而，这类遗址往往面临破坏和文化遗产流失的威胁。随着新技术的发展，现在有可能记录和创建这些遗址的三维重建，因为它们现在存在，不仅为研究提供了更大的能力，而且确保它们将以数字方式保存下来，以备将来使用。这个MRI项目是由加州大学默塞德分校（UCM）和加州大学圣地亚哥分校的高通研究所发起的。UCM是一所西班牙裔服务机构（HSI），也是全国为数不多的授予博士学位的HSI之一。此次收购的Hovermap系统充分利用了UCM在环境监测、自然资源管理、精准农业和学生培训等领域创新部署无人机技术方面所发挥的领导作用。gps拒绝环境的模型用于学科和多学科合作实验室研究项目。教育机会包括学生在实地和课堂上的培训，以及学生的研究和实习机会。这些项目涉及对受到威胁的考古遗址进行数字化保护，以及对国内和国际上的遗产遗址进行管理。该合同支持Emescent Hovermap系统的采购，该系统是一种手持和基于无人机的光探测和测距Velodyne激光雷达，具有专有的SLAM（同步定位和测绘）和处理系统。Hovermap专为采矿业设计，是一个强大的工具，可以快速捕获和可视化复杂的拓扑结构。这项新技术允许多次按需调查和实时机会数据收集，为快速捕获复杂的地下/室内环境（如洞穴、岩石掩体或建筑物内部以及陆地景观和地面建筑）建立能力，为依赖于精确空间数据捕获和成像的研究提供就业表示。该系统允许在狭窄或受限的空间行走时，手持设备进行渐进式激光雷达扫描，并根据地形和环境的需要，即插即用地过渡到基于无人机的扫描。该系统具有专有的软件，可以将每个模态的多个图像拼接在一起，创建具有彩色的高分辨率3D图像。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

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

• 发表时间: 2023
• 期刊: ISPRS annals of the photogrammetry remote sensing and spatial information sciences
• 作者: Lozano Bravo, H.;Lo, E.;Moyes, H.;Montgomery, S;Kuester, F.
• 通讯作者: Kuester, F.