文章基本信息

标题：A PRECISE POSITION AND ATTITUDE DETERMINATION SYSTEM FOR LIGHTWEIGHT UNMANNED AERIAL VEHICLES
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作者：C. Eling ; L. Klingbeil ; M. Wieland 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2013
卷号：XL-1/W2
页码：113-118
DOI：10.5194/isprsarchives-XL-1-W2-113-2013
出版社：Copernicus Publications
摘要：In many unmanned aerial vehicle (UAV) applications a direct georeferencing is required. The reason can be that the UAV flies autonomous and must be navigated precisely, or that the UAV performs a remote sensing operation, where the position of the camera has to be known at the moment of the recording. In our application, a project called Mapping on Demand , we are motivated by both of these reasons. The goal of this project is to develop a lightweight autonomously flying UAV that is able to identify and measure inaccessible three-dimensional objects by use of visual information. Due to payload and space limitations, precise position and attitude determination of micro- and mini-sized UAVs is very challenging. The limitations do not only affect the onboard computing capacity, but they are also noticeable when choosing the georeferencing sensors. In this article, we will present a new developed onboard direct georeferencing system which is real-time capable, applicable for lightweight UAVs and provides very precise results (position accuracy σ < 5 cm and attitude accuracy σ < 0.5 deg). In this system GPS, inertial sensors, magnetic field sensors, a barometer as well as stereo video cameras are used as georeferencing sensors. We will describe the hardware development and will go into details of the implemented software. In this context especially the RTK-GPS software and the concept of the attitude determination by use of inertial sensors, magnetic field sensors as well as an onboard GPS baseline will be highlighted. Finally, results of first field tests as well as an outlook on further developments will conclude this contribution
关键词：Unmanned Aerial Vehicle; Direct Georeferencing; RTK-GPS; IMU; Extended Kalman Filtering; Real Time Operating System