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Visual Localization Based on Quadtrees

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Robot 2015: Second Iberian Robotics Conference

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 418))

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Abstract

Autonomous mobile robots moving through their environment to perform the tasks for which they were programmed. The robot proper operation largely depends on the quality of the self localization information used when globally navigating in its environment. This paper describes a method of maintaining a self-location probability distribution of a set of states, which represents the robot position. The novel feature of this approach is to represent the state space as a Quadtree that dynamically evolves to use the minimum set of statements without loss of accuracy. We demonstrate the benefits of this approach in localizing a robot in the RoboCup SPL environment using the information provided by its camera.

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Author information

Authors and Affiliations

  1. Robotics Group, Rey Juan Carlos University, C/ Tulipán s/n, 28933, Móstoles, Madrid, Spain

    Francisco Martín

Authors
  1. Francisco Martín
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Correspondence to Francisco Martín .

Editor information

Editors and Affiliations

  1. Info Syst Dept;Campus de Azurém, University of Minho, Guimarães, Portugal

    Luís Paulo Reis

  2. Electrical and Computer Engineering Dept, University of Porto, Porto, Portugal

    António Paulo Moreira

  3. Instituto Superior Tecnico - Torre Norte, University of Lisboa, Lisboa, Portugal

    Pedro U. Lima

  4. Engineering Dept., E. Ada Byron, Univ of Zaragoza, Computer & Systems, Zaragoza, Spain

    Luis Montano

  5. Automatic Control and Systems Eng. Dept., University of Malaga, Superior Technical, Málaga, Spain

    Victor Muñoz-Martinez

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© 2016 Springer International Publishing Switzerland

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Martín, F. (2016). Visual Localization Based on Quadtrees. In: Reis, L., Moreira, A., Lima, P., Montano, L., Muñoz-Martinez, V. (eds) Robot 2015: Second Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 418. Springer, Cham. https://doi.org/10.1007/978-3-319-27149-1_46

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  • DOI: https://doi.org/10.1007/978-3-319-27149-1_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27148-4

  • Online ISBN: 978-3-319-27149-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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