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Aerial–ground collaborative 3D reconstruction for fast pile volume estimation with unexplored surroundings

机译:空中地面协作三维重建快速桩批量估算与未开发的环境

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Fast and accurate pile volume estimation is a very important basic problem in mining, waste sorting, and waste disposing industry. Nevertheless, for rapid changing or badly conditioned piles like stockpiles or landfills, conventional approaches involving massive measurements may not be applicable. To solve these problems, in this work, by utilizing unmanned aerial vehicles and unmanned ground vehicles equipped with a camera, we propose a collaborative framework to estimate volumes of free-formed piles accurately in short time. Compensating aerial- and ground views enable the reconstruction of piles with steep sides that is hard to be observed by single unmanned aerial vehicle. With the help of red-green-blue image sequences captured by unmanned aerial vehicles, we are able to distinguish piles from the ground in reconstructed point clouds and automatically eliminate concave on the ground while estimating pile volume. In the experiments, we compared our method to state-of-the-art dense reconstruction photogrammetry approaches. The results show that our approach for pile volume estimation has proved its feasibility for industrial use and its availability to free-formed piles on a different scale, providing high-accuracy estimation results in short time.
机译:快速准确的桩批量估计是采矿,废物分类和废物处理行业中非常重要的基本问题。尽管如此,对于快速变化或严重状况桩,如库存或垃圾填埋场,涉及大规模测量的常规方法可能不适用。为了解决这些问题,在这项工作中,通过利用装备的无人驾驶飞行器和装备相机的无人机车辆,我们提出了一种合作框架,在短时间内准确地估算自由成型桩的体积。补偿空中和地面视图使得具有陡峭的侧面的桩的重建能够通过单一无人驾驶飞行器难以观察到的。借助由无人航空车辆捕获的红绿蓝图像序列,我们能够将桩与重建点云的地面区分开,并在估计桩卷时自动消除地面上的凹面。在实验中,我们将我们的方法与最先进的密集重建摄影测量方法进行了比较。结果表明,我们对桩批估计的方法证明了其对工业用途的可行性及其对不同规模的自由成型桩的可用性,提供了高精度估计在短时间内产生的结果。

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