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Comparison of ROS-Based Monocular Visual SLAM Methods: DSO, LDSO, ORB-SLAM2 and DynaSLAM

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dc.contributor.author Mingachev E.
dc.contributor.author Lavrenov R.
dc.contributor.author Tsoy T.
dc.contributor.author Matsuno F.
dc.contributor.author Svinin M.
dc.contributor.author Suthakorn J.
dc.contributor.author Magid E.
dc.date.accessioned 2021-02-25T06:51:02Z
dc.date.available 2021-02-25T06:51:02Z
dc.date.issued 2020
dc.identifier.issn 0302-9743
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/161079
dc.description.abstract © 2020, Springer Nature Switzerland AG. Stable and robust path planning of a ground mobile robot requires a combination of accuracy and low latency in its state estimation. Yet, state estimation algorithms should provide these under computational and power constraints of a robot embedded hardware. The presented study offers a comparative analysis of four cutting edge publicly available within robot operating system (ROS) monocular simultaneous localization and mapping methods: DSO, LDSO, ORB-SLAM2, and DynaSLAM. The analysis considers pose estimation accuracy (alignment, absolute trajectory, and relative pose root mean square error) and trajectory precision of the four methods at TUM-Mono and EuRoC datasets.
dc.relation.ispartofseries Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.subject Benchmark testing
dc.subject Monocular SLAM
dc.subject Path planning
dc.subject Robot sensing systems
dc.subject Simultaneous localization and mapping
dc.subject State estimation
dc.subject Visual odometry
dc.subject Visual SLAM
dc.title Comparison of ROS-Based Monocular Visual SLAM Methods: DSO, LDSO, ORB-SLAM2 and DynaSLAM
dc.type Conference Paper
dc.relation.ispartofseries-volume 12336 LNAI
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 222
dc.source.id SCOPUS03029743-2020-12336-SID85092904826


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  • Публикации сотрудников КФУ Scopus [24551]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

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