Eldar MingachevRoman LavrenovTatyana TsoyFumitoshi MatsunoMikhail SvininJackrit SuthakornEvgeni MagidRitsumeikan University Biwako-Kusatsu CampusKazan Federal UniversityMahidol UniversityKyoto University2020-11-182020-11-182020-01-01Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol.12336 LNAI, (2020), 222-23316113349030297432-s2.0-85092904826https://repository.li.mahidol.ac.th/handle/20.500.14594/59952© 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.Mahidol UniversityComputer ScienceMathematicsConference PaperSCOPUS10.1007/978-3-030-60337-3_22