A Stereo SLAM System With Dense Mapping

The development of simultaneous localization and mapping (SLAM) technology plays an important role in robot navigation and autonomous vehicle innovation. The ORB-SLAM2 is a unified SLAM solution for monocular, binocular, and RGBD cameras which constructs a sparse feature point map for real-time posi...

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Autores principales:	Ben Zhang, Denglin Zhu
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Dense mapping mobile robot point cloud SLAM stereo matching Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/8ccc2f9c9b244aa283d355194f9f7d0d
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id	oai:doaj.org-article:8ccc2f9c9b244aa283d355194f9f7d0d
record_format	dspace
spelling	oai:doaj.org-article:8ccc2f9c9b244aa283d355194f9f7d0d2021-11-18T00:01:05ZA Stereo SLAM System With Dense Mapping2169-353610.1109/ACCESS.2021.3126837https://doaj.org/article/8ccc2f9c9b244aa283d355194f9f7d0d2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9611171/https://doaj.org/toc/2169-3536The development of simultaneous localization and mapping (SLAM) technology plays an important role in robot navigation and autonomous vehicle innovation. The ORB-SLAM2 is a unified SLAM solution for monocular, binocular, and RGBD cameras which constructs a sparse feature point map for real-time positioning. However, a sparse map based approach cannot effectively meet the requirements of robot navigation, environment reconstruction, and other tasks. In this paper, a dense mapping thread is added to the existing ORB-SLAM2 system. The depth map and color image obtained by the stereo matching of a binocular camera are used to generate a three-dimensional point cloud for keyframes; then, the point cloud is fused by tracking and optimizing the motion track of a feature frame to obtain a real-time point cloud map. Through the experiments conducted on the KITTI dataset and the real environment under the ROS, it is proved that the proposed system constructs a clear three-dimensional point cloud map while constructing an accurate trajectory.Ben ZhangDenglin ZhuIEEEarticleDense mappingmobile robotpoint cloudSLAMstereo matchingElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 151888-151896 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Dense mapping mobile robot point cloud SLAM stereo matching Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Dense mapping mobile robot point cloud SLAM stereo matching Electrical engineering. Electronics. Nuclear engineering TK1-9971 Ben Zhang Denglin Zhu A Stereo SLAM System With Dense Mapping
description	The development of simultaneous localization and mapping (SLAM) technology plays an important role in robot navigation and autonomous vehicle innovation. The ORB-SLAM2 is a unified SLAM solution for monocular, binocular, and RGBD cameras which constructs a sparse feature point map for real-time positioning. However, a sparse map based approach cannot effectively meet the requirements of robot navigation, environment reconstruction, and other tasks. In this paper, a dense mapping thread is added to the existing ORB-SLAM2 system. The depth map and color image obtained by the stereo matching of a binocular camera are used to generate a three-dimensional point cloud for keyframes; then, the point cloud is fused by tracking and optimizing the motion track of a feature frame to obtain a real-time point cloud map. Through the experiments conducted on the KITTI dataset and the real environment under the ROS, it is proved that the proposed system constructs a clear three-dimensional point cloud map while constructing an accurate trajectory.
format	article
author	Ben Zhang Denglin Zhu
author_facet	Ben Zhang Denglin Zhu
author_sort	Ben Zhang
title	A Stereo SLAM System With Dense Mapping
title_short	A Stereo SLAM System With Dense Mapping
title_full	A Stereo SLAM System With Dense Mapping
title_fullStr	A Stereo SLAM System With Dense Mapping
title_full_unstemmed	A Stereo SLAM System With Dense Mapping
title_sort	stereo slam system with dense mapping
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/8ccc2f9c9b244aa283d355194f9f7d0d
work_keys_str_mv	AT benzhang astereoslamsystemwithdensemapping AT denglinzhu astereoslamsystemwithdensemapping AT benzhang stereoslamsystemwithdensemapping AT denglinzhu stereoslamsystemwithdensemapping
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A Stereo SLAM System With Dense Mapping

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