Abstract
Abstract. UAVs have become an indispensable tool for a variety of mapping applications. Not only in the area of surveying, infrastructure planning and environmental monitoring tasks but also in time-critical applications, such as emergency and disaster response. Although UAVs enable rapid data acquisition per se, data processing usually relies on offline workflows. This contribution presents an accurate real-time data processing solution for UAV mapping applications as well as an extensive experimental and comparative study to the commercial offline solution Pix4D on the absolute accuracy of orthomosaics and digital surface models. We show that our procedure achieves an absolute horizontal and vertical accuracy of about 1 m without the use of ground control. The code will be made publicly available.
Highlights
In recent years, unmanned aerial vehicles (UAV) have become an important asset for rapid information retrieval for a wide array of applications, such as infrastructure inspection, environmental monitoring or disaster response (Ejaz et al, 2019; Erdelj et al, 2017; Kerle et al, 2019).UAVs provide high agility, flexibility and fast data capture, whereas respective data processing chains, i.e. image orientation, 3D reconstruction and ortho-generation, are usually performed in post-processing
This paper extends our previous work on this topic (Fanta-Jende et al, 2020; Kern et al, 2020) by integrating and comparing various state-of-the-art SLAM implementations (ORB-SLAM3 (Campos et al, 2020), OV2SLAM (Ferrera et al, 2021) and (Sumikura et al, 2019)) and their impact on the quality and accuracy of generated data products, i.e. orthomosaics and surface models
The aim of this study is to ascertain the absolute accuracy of the data products, i.e. orthomosaics in the horizontal dimension and digital surface models in the vertical dimension, generated by the proposed OpenREALM framework using different SLAM pipelines
Summary
In recent years, unmanned aerial vehicles (UAV) have become an important asset for rapid information retrieval for a wide array of applications, such as infrastructure inspection, environmental monitoring or disaster response (Ejaz et al, 2019; Erdelj et al, 2017; Kerle et al, 2019). UAVs provide high agility, flexibility and fast data capture, whereas respective data processing chains, i.e. image orientation, 3D reconstruction and ortho-generation, are usually performed in post-processing. This traditional pipeline is suited for scenarios which require high-accuracy and excellent reconstruction quality. This paper extends our previous work on this topic (Fanta-Jende et al, 2020; Kern et al, 2020) by integrating and comparing various state-of-the-art SLAM implementations (ORB-SLAM3 (Campos et al, 2020), OV2SLAM (Ferrera et al, 2021) and (Sumikura et al, 2019)) and their impact on the quality and accuracy of generated data products, i.e. orthomosaics and surface models
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