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DM-SLAM: Monocular SLAM in Dynamic Environments
Lu, Xiaoyun1,2; Wang, Hu1,2; Tang, Shuming2,3; Huang, Huimin1,2; Li, Chuang1
Contribution Rank1

Many classic visual monocular SLAM (simultaneous localization and mapping) systems have been developed over the past decades, yet most of them fail when dynamic scenarios dominate. DM-SLAM is proposed for handling dynamic objects in environments based on ORB-SLAM2. This article mainly concentrates on two aspects. Firstly, we proposed a distribution and local-based RANSAC (Random Sample Consensus) algorithm (DLRSAC) to extract static features from the dynamic scene based on awareness of the nature difference between motion and static, which is integrated into initialization of DM-SLAM. Secondly, we designed a candidate map points selection mechanism based on neighborhood mutual exclusion to balance the accuracy of tracking camera pose and system robustness in motion scenes. Finally, we conducted experiments in the public dataset and compared DM-SLAM with ORB-SLAM2. The experiments corroborated the superiority of the DM-SLAM.

Keywordstatic features extraction dynamic environments 3D reconstruction monocular SLAM
Indexed BySCI
WOS IDWOS:000549398100001
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Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Corresponding AuthorWang, Hu
Affiliation1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Lu, Xiaoyun,Wang, Hu,Tang, Shuming,et al. DM-SLAM: Monocular SLAM in Dynamic Environments[J]. APPLIED SCIENCES-BASEL,2020,10(12).
APA Lu, Xiaoyun,Wang, Hu,Tang, Shuming,Huang, Huimin,&Li, Chuang.(2020).DM-SLAM: Monocular SLAM in Dynamic Environments.APPLIED SCIENCES-BASEL,10(12).
MLA Lu, Xiaoyun,et al."DM-SLAM: Monocular SLAM in Dynamic Environments".APPLIED SCIENCES-BASEL 10.12(2020).
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