@inproceedings{1a5046a50ea240bd874f36dc6355b674,
title = "A Novel Monocular SLAM Algorithm for High Real-Time Based on Kalman Filter",
abstract = "Simultaneous Localization and Mapping (SLAM) has been a hot research direction in the field of mobile robots since it was proposed. ORB-SLAM is a typical algorithm in feature point SLAM system. However, because the ORB-SLAM can only provide sparse map construction, it can only be used for positioning. Just using ORB-SLAM to handle the positioning problem make the calculation complexity higher and reduce the real-time performance. Because of the complicated calculation, the ORB-SLAM is not practical to the embedded devices with low computing power. Therefore, we propose a monocular SLAM algorithm with high real-time performance based on Kalman filter. Our proposed algorithm reduces the time consumption of the system by modifying the posture optimization algorithm. Our algorithm provides accurate and efficient positioning for upper-level applications. We use Kalman filter modeling to optimize the pose of the camera. The experimental results show that compared with traditional algorithm, our proposed algorithm can effectively improve the real-time performance and reduces the time consumption of the system.",
keywords = "Kalman filter, ORB, Pose optimization, SLAM",
author = "Wanqing Wu and Lin Ma and Bin Wang",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 17th IEEE International Wireless Communications and Mobile Computing, IWCMC 2021 ; Conference date: 28-06-2021 Through 02-07-2021",
year = "2021",
doi = "10.1109/IWCMC51323.2021.9498904",
language = "英语",
series = "2021 International Wireless Communications and Mobile Computing, IWCMC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1667--1672",
booktitle = "2021 International Wireless Communications and Mobile Computing, IWCMC 2021",
address = "美国",
}