Abstract
The use of the odometry and SLAM visual methods in autonomous vehicles has been growing. Optical sensors provide valuable information from the scenario that enhance the navigation of autonomous vehicles. Although several visual techniques are already available in the literature, their performance could be significantly affected by the scene captured by the optical sensor. In this context, this paper presents a comparative analysis of three monocular visual odometry methods and three stereo SLAM techniques. The advantages, particularities and performance of each technique are discussed, to provide information that is relevant for the development of new research and novel robotic applications.
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Notes
- 1.
Dataset available on http://www.cvlibs.net/datasets/kitti/eval_odometry.php.
- 2.
Dataset available on http://projects.csail.mit.edu/stata/downloads.php.
- 3.
Dataset available on http://www.robots.ox.ac.uk/NewCollegeData/.
- 4.
KFr represents the number of keyframes used to egomotion estimation.
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Acknowledgements
This work is financed by the ERDF - European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme within project \(\ll \)POCI-01-0145-FEDER-006961\(\gg \), and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) as part of project UID/EEA/50014/2013.
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Gaspar, A.R., Nunes, A., Pinto, A., Matos, A. (2018). Comparative Study of Visual Odometry and SLAM Techniques. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds) ROBOT 2017: Third Iberian Robotics Conference. ROBOT 2017. Advances in Intelligent Systems and Computing, vol 694. Springer, Cham. https://doi.org/10.1007/978-3-319-70836-2_38
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