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Weighted data fusion for UAV-borne 3D mapping with camera and line laser scanner

机译:加权数据融合,可通过摄像机和直线激光扫描仪在无人机上进行3D映射

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摘要

Unmanned aerial vehicles (UAVs) equipped with adequate sensors have nowadays become a powerful tool for capturing spatial information. In this article, we introduce a concept for weighted data fusion in order to enable an improved UAV-borne 3D mapping with a camera and a lightweight line laser scanner. For this purpose, we carry out geometric camera calibration as well as lever-arm and bore-sight calibration and subsequently present a new methodology for incorporating camera images and laser scanner data into an adjustment process. This adjustment is based on the concept of variance components in order to obtain a reasonable weight ratio for data fusion and accurately estimate the poses of the sensors. We demonstrate the feasibility of the proposed approach and show that the consideration of range measurements clearly improves the pose estimation.
机译:如今,配备有足够传感器的无人机已经成为捕获空间信息的强大工具。在本文中,我们介绍了加权数据融合的概念,以便能够使用相机和轻型线型激光扫描仪来改进基于无人机的3D映射。为此,我们进行了几何相机校准以及杠杆和视轴校准,随后提出了一种新方法,将相机图像和激光扫描仪数据整合到调整过程中。该调整基于方差分量的概念,以便获得合理的权重比以进行数据融合并准确估算传感器的姿态。我们证明了提出的方法的可行性,并表明考虑范围测量明显改善了姿态估计。

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