Abstract
This paper presents an approach to perform data association in a monocular visual SLAM context. The proposed approach is designed to avoid the detection of false associations by means of RANSAC, and is well suited to help in localizing a robot in underwater environments. Experimental results embed the data association in a trajectory-based SLAM in order to evaluate its benefits when localizing an underwater robot. Qualitative and quantitative results are shown evaluating the effects of dead reckoning noise and the frequency of the SLAM updates.
This work is partially supported by the Spanish Ministry of Research and Innovation DPI2011-27977-C03-03 (TRITON Project), Govern Balear (Ref. 71/211) and FEDER funds.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bar-Shalom, Y., Rong Li, X., Kirubarajan, T.: Estimation with applications to tracking and navigation: theory algorithms and software. John Wiley and Sons, Inc. (2001)
Bay, H., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (SURF). Computer Vision and Image Understanding 110, 346–359 (2008)
Bonin, F., Burguera, A., Oliver, G.: Imaging systems for advanced underwater vehicles. Journal of Maritime Research 8(1), 65–86 (2011)
Burguera, A., González, Y., Oliver, G.: The UspIC: Performing scan matching localization using an imaging sonar. Sensors 12, 7855–7885 (2012)
Burguera, A., Oliver, G., González, Y.: Scan-based slam with trajectory correction in underwater environment. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010), Taipei, Taiwan (2010)
Davison, A.J., Reid, I.D., Molton, N.D., Stasse, O.: MonoSLAM: Real-time single camera SLAM. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(6) (June 2007)
Elibol, A., Gracias, N., Garcia, R.: Augmented State Extended Kalman Filter combined framework for topology estimation in large-area underwater mapping. Journal of Field Robotics 27, 656–674 (2010)
Estrada, C., Neira, J., Tardós, J.D.: Hierarchical SLAM: real-time accurate mapping of large environments. IEEE Transactions on Robotics 21(4), 588–596 (2005)
Eustice, R.M., Pizarro, O., Singh, H.: Visually augmented navigation for autonomous underwater vehicles. IEEE Journal of Oceanic Engineering 33(2), 103–122 (2008)
Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM 24(6), 381–395 (1981)
Geiger, A., Ziegler, J., Stiller, C.: Stereoscan: Dense 3d reconstruction in real-time. In: IEEE Intelligent Vehicles Symposium, Baden-Baden, Germany (June 2011)
Huang, A.S., Bachrach, A., Henry, P., Krainin, M., Maturana, D., Fox, D., Roy, N.: Visual odometry and mapping for autonomous flight using an rgb-d camera. In: Proceedings of the International Symposium on Robotics Research (ISRR), Flagstaff, Arizona, USA (August 2011)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)
Rauvi, Trident: UWSim: The underwater simulator. Web (accessed April 22, 2013)
Ribas, D., Ridao, P., Neira, J.: Underwater SLAM for Structured Environments Using an Imaging Sonar. Springer Tracts in Advanced Robotics, vol. 65. Springer (2010)
Smith, R., Cheeseman, P., Self, M.: A stochastic map for uncertain spatial relationships. In: Proceedings of International Symposium on Robotic Research, pp. 467–474. MIT Press (1987)
Vedaldi, A., Fulkerson, B.: VLFeat: An open and portable library of computer vision algorithms (2008), http://www.vlfeat.org
WillowGarage. Ros.org. Web (accessed April 22, 2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Burguera, A., González, Y., Oliver, G. (2014). RANSAC Based Data Association for Underwater Visual SLAM. In: Armada, M., Sanfeliu, A., Ferre, M. (eds) ROBOT2013: First Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 252. Springer, Cham. https://doi.org/10.1007/978-3-319-03413-3_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-03413-3_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03412-6
Online ISBN: 978-3-319-03413-3
eBook Packages: EngineeringEngineering (R0)