A Precise Positioning Methodology for Autonomous Navigation of a Tethered UAV for Photogrammetry

In the last decade the use of unmanned aerial vehicles for civilian applications has grown exponentially. The emergence of autonomous systems and artificial intelligence has opened new research areas for the development of aerial industrial applications. This paper presents a methodology based on a tethered drone to perform aerial photogrammetry applications through a fully autonomous navigation. The algorithm has been tested using a tethered hexacopter, which has been configured with a specific selection of its components, seeking maximum stability and accuracy in its positioning during flight operations. The autonomous navigation of the aircraft is based on the information generated in real time by a set of on-board calibrated sensors. Aerial photogrammetry hardware has been also implemented on board for the capture of georeferenced images and developing a set of applications for photogrammetry missions. All the control of the autonomous operations is performed from a ground station, in constant connection with the aircraft through the communication protocols of the drone controller. Once each programmed flight mission has been executed, the aerial images have been processed for the generation of different photogrammetric models. The results present enhanced navigation and precise positioning through the applied metrology and the high-accuracy trajectory measurements.