ORB-SLAM2 algorithm based on improved key frame selection

To address the difficulties caused by the low accuracy and poor robustness of simultaneous localization and mapping (SLAM), an ORB-SLAM2 algorithm is proposed based on key frame selection. First, the relative pose between frames is calculated based on ORB-SLAM2. Second, to determine whether a new key frame should be created, rotation and translation values are added to the original algorithm, functioning as the judgement basis. Then, an inferior key frame removal algorithm is designed to solve the problem of inferior key frame generation which results from incorrect shooting caused by the relative movement between the robot and the camera installed in the self-developed mobile robot. Finally, experiments are carried out based on the RGB-D dataset and the developed mobile robot, verifying the outstanding performance of the proposed algorithm. The results show that the improved key frame selection algorithm can accurately and timely choose the key frame, and reduce tracking failures. In the most optimal case, the positioning error is about 51.9% of that of the original, while the linear error is about 82.1% of that of the original, which effectively eliminates the influence caused by relative motion between the camera and the robot. This research shows that the improved algorithm could effectively promote positioning accuracy and reduce tracking failures. © 2023 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.