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Development of a UAV-based system for the semi-automatic estimation of the volume of earthworks

机译:开发基于UV的系统,用于半自动估计土方数量

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One of the challenges faced by surveyors in acquisition of accurate spatial data for mining applications is the risk involved in acquiring data in rugged terrains and difficult or inaccessible areas. With the advent of modern technology, accurate geospatial data can now be safely obtained for proper mining documentation periodically. The use of Unmanned Aerial Vehicles (UAVs) for data acquisition in mine surveying has been a viable means of obtaining reliable geospatial data rapidly and efficiently. The main goal of this study is to develop a semi-automatic UAV-based system for the acquisition of spatial data required for the estimation of the volume of earthworks. A DJI Phantom 4 quadcopter was used for the acquisition of image data of the project site, while the images were processed into a Digital Elevation Model (DEM) using Pix4Dmapper v2.0.1, which was then imported into the MATLAB-based system developed for the automatic estimation of the volume of earthworks. The volume obtained from the automated system was thus compared with the volume obtained directly from the Pix4Dmapper software, having specified a contour interval of 1 and an allowable error rate of ±3% as the standard error. While ±1.02% error was observed in the volume estimated using the Pix4Dmapper, the developed automated system yielded an estimated precision of ±0.81% in its volume estimation, which proves to be more robust for automatic volume estimation in terms of accuracy and precision.
机译:测量师面临的挑战之一,以获取用于采矿应用的准确空间数据是获取崎岖地形和困难或无法访问的地区的数据所涉及的风险。随着现代技术的出现,现在可以定期为适当的采矿文档安全地获得准确的地理空间数据。在矿山测量中使用无人驾驶飞行器(无人机)用于数据采集的数据采集是快速有效地获得可靠的地理空间数据的可行方法。本研究的主要目标是开发基于半自动的UV基系统,用于获取估计土方数量所需的空间数据。 DJI Phantom 4 Quadcopter用于获取项目站点的图像数据,而使用Pix4dmapper v2.0.1将图像处理到数字高度模型(DEM)中,然后将其导入为基于Matlab的系统开发自动估计土方数量。因此,与直接从PIX4DMapper软件获得的体积相比,从自动化系统获得的体积,其指定了1的轮廓间隔和作为标准误差的±3%的允许误差率。在使用PIX4DMAPPER估计的音量中观察到±1.02%误差,而开发的自动化系统在其体积估计中估计精度为±0.81%,这被证明在准确性和精度方面的自动体积估计更加稳健。

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