Abstract
Abstract. Many unmanned aerial vehicles (UAV) that are used for aerial mapping are equipped with consumer-grade digital cameras, which use CMOS (Complementary metal–oxide–semiconductor) image sensors. Majority of these sensors capture images using an electronic rolling shutter, which can cause distortions on the image if either the camera or the captured objects are moving. This phenomenon is usually ignored in aerial mapping with UAVs in practice. However, there is a lack of published research papers that would prove the effect can be neglected. In this paper, we present the design of the system for monitoring UAV camera orientation. Furthermore, the calibration process to get correct and reliable readings is described. The initial analysis of the data is focused on assessing the accuracy that can be achieved using the proposed system. The main component of our system is a MEMS (Microelectromechanical system) gyroscope. It was selected for its low weight and size, low price and high sampling rates which are all very beneficial characteristics for a system, mounted on a UAV. In a paper, a working prototype is presented that uses the selected MEMS gyroscope connected to a single-board computer. The presented initial analysis of collected data shows, that the system would be capable to indirectly detect the image distortions, caused by camera orientation changes during exposure, in the range of typical ground sample distance (GSD).
Highlights
unmanned aerial vehicles (UAV) are becoming a widely used tool for spatial data acquisition
A big majority of UAVs are equipped with consumer-grade cameras that use CMOS image sensor technology
CMOS image sensors are better than CCD image sensors in many aspects that are important for mass marketing, but not in the one, that is very important in photogrammetry – constant and stable image geometry
Summary
UAVs are becoming a widely used tool for spatial data acquisition. The UAVs are nowadays technically advanced and affordable platforms for spatial data acquisition. The software combined with UAV as a platform, and a camera, provide a comprehensive package for efficient spatial data acquisition. Despite all this progress, a very important component of this package from the photogrammetric point of view was not considered – until recently, there has been no evident development of small and light metric cameras. A big majority of UAVs are equipped with consumer-grade cameras that use CMOS image sensor technology. Because UAV is far from being a stable platform in the air, research is needed to develop systems and methodologies for estimation, reduction, and correction of the errors, caused by the instability
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