Abstract
In this paper, we propose a localization system that can combine data supplied by different sensors, even if they are not synchronized, or if they do not provide data at all times. Particularly, we have used the following sensors: a 2D laser range finder, a Wi-Fi positioning system (designed by us), and a magnetic compass. Real world experiments have shown that our algorithm is accurate, robust, and fast, and that it can take advantage of the strengths of each sensor, and minimise its weaknesses.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Alvarez-Santos, V., Canedo-Rodriguez, A., Iglesias, R., Pardo, X.M., Regueiro, C.V.: Route learning and reproduction in a tour-guide robot. In: Ferrández, J.M., Álvarez, J.R., de la Paz, F., Javier Toledo, F. (eds.) IWINAC 2013, Part II. LNCS, vol. 7931, pp. 112–121. Springer, Heidelberg (2013)
Thrun, S., Beetz, M., Bennewitz, M., Burgard, W., Cremers, A.B., Dellaert, F., Fox, D., Haehnel, D., Rosenberg, C., Roy, N., et al.: Probabilistic algorithms and the interactive museum tour-guide robot minerva. International Journal of Robotics Research 19(11), 972–999 (2000)
Tardós, J.D., Neira, J., Newman, P.M., Leonard, J.J.: Robust mapping and localization in indoor environments using sonar data. The International Journal of Robotics Research 21(4), 311–330 (2002)
Gamallo, C., Regueiro, C., Quintía, P., Mucientes, M.: Omnivision-based kld-monte carlo localization. Robotics and Autonomous Systems 58(3), 295–305 (2010)
Canedo-Rodriguez, A., Santos-Saavedra, D., Alvarez-Santos, V., Regueiro, C.V., Iglesias, R., Pardo, X.M.: Analysis of different localization systems suitable for a fast and easy deployment of robots in diverse environments. In: Workshop of Physical Agents, pp. 39–46 (2012)
Gutmann, J.-S., Fox, D.: An experimental comparison of localization methods continued. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 1, pp. 454–459. IEEE (2002)
Thrun, S., Burgard, W., Fox, D., et al.: Probabilistic robotics, vol. 1. MIT Press, Cambridge (2005)
Pollard, D.: A user’s guide to measure theoretic probability, vol. 8. Cambridge University Press (2001)
Chang, C.-C., Lin, C.-J.: Libsvm: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology 2(3), 27 (2011)
Grisetti, G., Stachniss, C., Burgard, W.: Improved techniques for grid mapping with rao-blackwellized particle filters. IEEE Transactions on Robotics 23(1), 34–46 (2007)
Canedo-Rodriguez, A., Iglesias, R., Regueiro, C.V., Alvarez-Santos, V., Pardo, X.M.: Self-organized multi-camera network for a fast and easy deployment of ubiquitous robots in unknown environments. Sensors 13(1), 426–454 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Canedo-Rodriguez, A. et al. (2013). Robust Multi-sensor System for Mobile Robot Localization. In: Ferrández Vicente, J.M., Álvarez Sánchez, J.R., de la Paz López, F., Toledo Moreo, F.J. (eds) Natural and Artificial Computation in Engineering and Medical Applications. IWINAC 2013. Lecture Notes in Computer Science, vol 7931. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38622-0_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-38622-0_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38621-3
Online ISBN: 978-3-642-38622-0
eBook Packages: Computer ScienceComputer Science (R0)