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|Title:||Comparison of ROS-Based Monocular Visual SLAM Methods: DSO, LDSO, ORB-SLAM2 and DynaSLAM|
Ritsumeikan University Biwako-Kusatsu Campus
Kazan Federal University
|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.|
|Appears in Collections:||Scopus 2020|
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