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

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.