An embedded visual SLAM algorithm based on Kinect and ORB features

This paper introduces a visual SLAM system based on Kinect sensor and ORB features. The RGB image output by the Kinect sensor is processed and Oriented FAST and Rotated BRIEF (ORB) features are extracted for landmark detection. The depth information output by Kinect is processed and repaired using nearest neighbor repairing algorithm to achieve a complete depth map. Locality-sensitive hashing (LSH) algorithm is used during feature association process to improve the mapping speed. Experiments show that the visual SLAM system based on Kinect and ORB feature is feasible and has an acceptable accuracy, with a good potential for indoor robot navigation tasks in an unknown environment.