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

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的方法，可以创建人类和自然景观的详细区域图像，以生成地面的高分辨率地形模型。 虽然这种方法从根本上改变了地面环境的成像，但这些系统通常需要全球定位系统导航系统来飞行和导航。 被描述为GPS拒绝的环境，包括地下空间，如洞穴，岩石掩体，矿井或建筑物内部，由于这种限制，LiDAR/UAV技术的使用受到限制。目前用于创建内部空间的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，并且不能在狭窄或难以到达的地方使用。然而，这些类型的遗址往往受到破坏和文化遗产损失的威胁。 随着新技术的发展，现在可以记录和创建这些遗址的3D重建，不仅可以提高研究能力，而且可以确保它们在未来得到数字化保存。该MRI项目由加州大学默塞德分校（UCM）和位于圣地亚哥的加州大学高通研究所发起。UCM是一个西班牙裔服务机构（HSI）和为数不多的博士之一。在全国范围内授予HSIs。收购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拒绝环境的模型被制作用于学科和多学科的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。这些项目致力于对受到威胁的考古遗址进行数字化保护，并对国家和国际遗产遗址进行管理。该奖项支持Emescent Hovermap系统的收购，这是一种手持式和基于无人机的光探测和测距Velodyne LiDAR，具有专有的SLAM（同时定位和映射）和处理系统。Hovermap专为采矿业设计，是一款强大的工具，可快速捕获和可视化复杂拓扑。这种新技术允许进行多个按需调查和即时机会性数据收集，从而建立快速捕获复杂地下/室内环境（如洞穴，岩石掩体或建筑内部以及陆地景观和表面建筑）的能力，为依赖于准确空间数据捕获和成像的研究提供表示。该系统允许渐进式激光雷达扫描，同时手持该装置穿过狭窄或受限的空间，并根据地形和环境要求，即插即用过渡到基于无人机的扫描。该系统具有适当的软件，将从每个模态拼接多个图像，创建一个高分辨率的彩色3D图像。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.