@inproceedings{2a0b093931154291b8e9944cdef29b3a,
title = "Robust SLAM Algorithm in Dynamic Environment Using Optical Flow",
abstract = "Visual SLAM(Simultaneous Localization and Mapping) is one of the hottest research areas nowadays. Most of the SLAM methods assume that the scene is stationary. It is difficult to face the factual complex environment. To solve this problem, an improved RGB-D SLAM algorithm combined with Optical Flow and RANSAC (Random Sample Consensus) was proposed in this paper. Optical flow is used to detect moving objects in the scene. RANSAC is used to calculate the homography matrix and optimize matching results. We used a common data set for experimental verification. The results show that this algorithm can effectively detect dynamic objects, improve the accuracy of visual odometry and the robustness of the system.",
keywords = "Dynamic environment, Optical Flow, RANSAC, SLAM",
author = "Yiying Ma and Yingmin Jia",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Singapore Pte Ltd.; Chinese Intelligent Systems Conference, CISC 2019 ; Conference date: 26-10-2019 Through 27-10-2019",
year = "2020",
doi = "10.1007/978-981-32-9682-4\_71",
language = "英语",
isbn = "9789813296817",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "681--689",
editor = "Yingmin Jia and Junping Du and Weicun Zhang",
booktitle = "Proceedings of 2019 Chinese Intelligent Systems Conference - Volume I",
address = "德国",
}