High-precision geo-referencing of UAS data with robotic total stations
Keywords: Trajectory, Mapping, UAV, Sensor fusion
Abstract. Robotic Total Stations (RTS) allow the measurement of 3D positions of kinematic targets with high accuracy. They find wide applications for geo-referencing multisensor systems, but little focus has been put on the geo-referencing of Unmanned Aerial Systems (UAS) with RTS.
In this study, we geo-reference an Unmanned Laser Scanning (ULS) point cloud using an RTS and an Inertial Measurement Unit (IMU) without using GNSS positions. We thoroughly investigate the UAS trajectory measured by an RTS, using photogrammetric reference positions and a redundant trajectory from a second RTS. In addition, we evaluate the generated ULS point cloud against a reference point cloud acquired by Terrestrial Laser Scanning (TLS).
For our field test, we find that the UAS trajectory shows an average 3D difference of less than 13 mm compared to our reference data sets. The generated point cloud has an average absolute 3D normal distance of 9 mm to our TLS reference.