Abstract
The successful mission of an autonomous airborne system like an unmanned aerial vehicle (UAV) strongly depends on its accurate navigation. While GPS is not always available and pose estimation based solely on Inertial Measurement Unit (IMU) drifts, image-based navigation may become a cheap and robust additional pose measurement device. For the actual navigation update a landmark-based approach is used. It is essential that the used landmarks are well chosen. Therefore we introduce an approach for evaluating landmarks in terms of the matching distance, which is the maximum misplacement in the position of the landmark that can be corrected. We validate the evaluations with our 3D reconstruction system working on data captured from a helicopter.
Highlights
Autonomous navigation is of growing interest in science as well as in industry
In the previous sections only highly accurate 3D points are used for evaluation or selection of landmarks
That can be considered as the preparation phase of a mission, where LiDAR or other advanced sensors are used for measuring the structure of the area
Summary
Autonomous navigation is of growing interest in science as well as in industry. The key problem of most existing outdoor systems is the dependency on GPS data. Since GPS is not always available we integrate an image-based approach into the system. Landmarks are used to update the actual position and orientation. It is necessary to select the landmarks carefully. This selection takes place in an offline phase before the mission. The evaluation of these landmarks is the main contribution of this paper. We compute 3D reconstructions from the scene and match them with the selected georeferenced landmarks
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