Real-Time UAV Global Pose Estimation Using 3D Terrain Engine

Abstract

We present a new approach that automatically estimates global pose for a UAV in real-time using 3D terrain engine. Inaccurate auxiliary sensors on the UAV were used to obtain initial real camera pose that moves the virtual camera inside the 3D terrain engine. We, then automatically found multiple matches between the two images to find the 3D coordinates of the matches using the 3D terrain engine. Finally, we tested the co-planarity of the 3D points under the camera, depending on this test. We used coplanar or non-coplanar algorithm to estimate accurate global camera pose. We executed feature detection, description and pair wise matching algorithms on GPU to get a suitable frame rate (12 FPS) needed in the navigation applications. The proposed approach has been tested on a synthetic and real data. Experimental results proved the feasibility and robustness of the proposed approach, and the precision was the same order as the 3D terrain engine used. Finally, we can say that the 3D terrain engine succeeded when other methods failed.