Abstract
This paper will present a cooperative multi-robot localization model with planning support. Models of communication and transmission of pose estimates are constantly explored, however how the robots act on the environment is generally defined by random actions (from the localization task’s point of view). Random actions generate observations that can be useless for improving the estimate. This work describes a proposal for multi-robot localization with planning of actions. The objective is to describe a model where policies define the best action to performed by robots. The proposed model, called Model of Planned Localization - MPL, uses POMDPs to model the problems of location and specific algorithms to generate policies. We compared the MPL to a model that does not make use of planning actions. The results showed that MPL is able to estimate the positions of robots with lower number of steps, being more efficient than model compared.
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.
References
Cassandra, A., Kaelbling, L.P., Kurien, J.: Acting under uncertainty: Discrete bayesian models for mobile-robot navigation. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 2, pp. 963–972 (1996)
Cox, I.J.: Blanche: an experiment in guidance and navigation of an autonomous robot vehicle. IEEE Transaction on Robotics and Automation 7(2), 193–204 (1991)
Fox, D.: Markov Localization: A Probabilistic Framework for Mobile Robot Localization and Navigation. PhD thesis, University of Bonn, Germany, Germany (1998)
Fox, D., Burgard, W., Thrun, S.: Active markov localization for mobile robots. Robotics and Autonomous Systems 25, 195–207 (1998)
Fox, D., et al.: A probabilistic approach to collaborative multi-robot localization. Autonomous Robots 8(3), 325–344 (2000)
Hoffman, J., et al.: Making use of what you don’t see: negative information in markov localization. In: International Conference on Intelligent Robots and Systems, vol. 1, pp. 2947–2952 (2005)
Hoffmann, J., Spranger, M., Gohring, M., Jungel, M.: Exploiting the unexpected: Negative evidence modeling and proprioceptive motion modeling for improved markov localization. In: Bredenfeld, A., Jacoff, A., Noda, I., Takahashi, Y. (eds.) RoboCup 2005. LNCS (LNAI), vol. 4020, pp. 24–35. Springer, Heidelberg (2006)
Nourbakhsh, I., Powers, R., Birchfield, S.: Dervish: An office-navigation robot. AI Magazine 16(2), 53–60 (1995)
Odakura, V.: Localização de Markov para multirrobôs cooperativos. PhD thesis, Escola Politécnica, USP, São Paulo (2006)
Odakura, V., Costa, A.H.R.: Cooperative multi-robot localization: using communication to reduce localization error. In: International Conference on Informatics in Control Automation and Robotics - ICINCO, vol. 3, pp. 88–93 (2005)
Odakura, V., Costa, A.H.R.: Negative information in cooperative multirobot localization. In: Sichman, J.S., Coelho, H., Rezende, S.O. (eds.) IBERAMIA 2006 and SBIA 2006. LNCS (LNAI), vol. 4140, pp. 552–561. Springer, Heidelberg (2006)
Romero, L., Arellano, J.J.: Robust local localization of a mobile robot using a 180 2-d laser range finder. In: Proceedings of the Sixth Mexican International Conference on Computer Science, vol. 1, pp. 248–255. IEEE Computer Society, Los Alamitos (2005)
Romero, L., Lara, C.: Robust local localization of a mobile robot in indoor environments using virtual corners. In: Rueda, L., Mery, D., Kittler, J. (eds.) CIARP 2007. LNCS, vol. 4756, pp. 901–910. Springer, Heidelberg (2007)
Roumeliotis, S., Bekey, G.A.: Distributed multirobot localization. IEEE Transactions on Robotics and Automation 18, 781–795 (2002)
Tardos, J.D., et al.: Robust mapping and localization in indoor environments using sonar. The International Journal of Robotics Research 21(4), 311–330 (2002)
Theocharous, G., Murphy, K., Pack, L.: Representing hierarchical pomdps as dbns for multi-scale robot localization. In: International Conference on Robotics and Automation, vol. 1, pp. 1045–1051 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pinheiro, P., Wainer, J. (2010). Planning for Multi-robot Localization. In: da Rocha Costa, A.C., Vicari, R.M., Tonidandel, F. (eds) Advances in Artificial Intelligence – SBIA 2010. SBIA 2010. Lecture Notes in Computer Science(), vol 6404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16138-4_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-16138-4_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16137-7
Online ISBN: 978-3-642-16138-4
eBook Packages: Computer ScienceComputer Science (R0)