Real Time Monocular Visual Odometry using ORB Features for Indoor Environment
Navigation is a key process in many intelligent systems. The most common way to do navigation is using Global Positioning System (GPS). However, in indoor environment, GPS is inaccurate due to multi-path problem. To solve this problem, a dead reckoning system may be implemented. Visual odometry is one of the dead reckoning methods which can help solving this problem. Among many types of visual odometry algorithm, feature-based monocular visual odometry algorithm is proposed in this research. The feature detector used in this work is ORB. The features are used for triangulation and the obtained 3D structure will be used as the basic information for poses determination. Pose determination is done by solving the PnP problem. The algorithm is validated by performing six basic motion tests while the algorithm is running. The result of the tests shows that the visual odometry algorithm can determine the position and orientation with good accuracy.
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