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Please use this identifier to cite or link to this item: http://repository.li.mahidol.ac.th/dspace/handle/123456789/59952
Title: Comparison of ROS-Based Monocular Visual SLAM Methods: DSO, LDSO, ORB-SLAM2 and DynaSLAM
Authors: Eldar Mingachev
Roman Lavrenov
Tatyana Tsoy
Fumitoshi Matsuno
Mikhail Svinin
Jackrit Suthakorn
Evgeni Magid
Ritsumeikan University Biwako-Kusatsu Campus
Kazan Federal University
Mahidol University
Kyoto University
Keywords: Computer Science;Mathematics
Issue Date: 1-Jan-2020
Citation: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol.12336 LNAI, (2020), 222-233
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.
URI: http://repository.li.mahidol.ac.th/dspace/handle/123456789/59952
metadata.dc.identifier.url: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85092904826&origin=inward
ISSN: 16113349
03029743
Appears in Collections:Scopus 2020

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