A Ground-Based Vision System for UAV Pose Estimation
We present a vision system based on a single frame of standard RGB digital camera to estimate the pose of an unmanned aerial vehicle (UAV). The envisaged application is of ground-based automatic landing, where the vision system is located on the ship’s deck and is used to estimate the UAV pose (3D position and orientation) during the landing process. Using a vision system located on the ship makes it possible to use an UAV with less processing power, decreasing its size and weight. The proposed method uses a 3D model based pose estimation approach that requires the 3D CAD model of the UAV. Pose is estimated in a particle filtering framework. The implemented particle filter is inspired in the evolution strategies present in the genetic algorithms avoiding sample impoverishment. Results show position and angular errors are compatible with automatic landing system requirements, even without temporal filtering. The algorithm is suitable for real time implementation in standard workstations with graphical processing units.
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