Research on an improved RGB-D camera SLAM odometer algorithm

Hongxia Cui; Hu Xue; Hanqing Hu

doi:10.1117/12.2674619

23 May 2023 Research on an improved RGB-D camera SLAM odometer algorithm

Hongxia Cui, Hu Xue, Hanqing Hu

Proceedings Volume 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022); 126041N (2023) https://doi.org/10.1117/12.2674619
Event: 2nd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 2022, Guangzhou, China

Abstract

With the rapid development of sensors and computer vision, simultaneous localization and mapping plays an important role in the field of intelligent robots. However, traditional odometer from ORB-SLAM2 methods based on a RGB-D camera still face the problem of low accuracy and tracking failure in complex environments with obvious irregular motion, which lead to lower stability and reliability. Aiming at solving the above problems, an odometer method is proposed by introducing three-view information to improve the localization precision of current frame. The method establishes a framework for RGB-D odometer. The co-view relationships were developed between three frames based on feature matching method. Thus, the BA optimization model is constructed based on the tracked relationship among three frames. In this way, the problems of accumulated errors can be decreased by constraints of three-view information. Experiments on the public TUM data set show that the trajectories from the proposed method is more accurate and robust than those of tradition ORB-SLAM2.

Citation Download Citation

Hongxia Cui, Hu Xue, and Hanqing Hu "Research on an improved RGB-D camera SLAM odometer algorithm", Proc. SPIE 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 126041N (23 May 2023); https://doi.org/10.1117/12.2674619

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