Abstract
Localization is an important issue for UAV (Unmanned Aerial Vehicle) applications. This paper proposes a localization algorithm based on the combination of direct method and feature-based method. The visual odometer uses the photometric error to directly match and track the camera’s pose to improve the real-time performance. Then the ORB (Oriented FAST and Rotated Brief) features are extended from key frames, and local and global optimization can be achieved through key frames to improve map consistency by Bundle Adjustment. A depth filter is also introduced to optimize the map points by accumulating depth information of multiple frames. Then the localization accuracy can be improved by building a more accurate map. The proposed algorithm can achieve faster pose estimation and higher real-time performance while ensuring localization accuracy in indoor environments.
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