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Visual SLAM Based on Phase Correlation and Particle Filters

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Mendel 2015 (ICSC-MENDEL 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 378))

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Abstract

This paper deals with design of visual SLAM method, which is based on phase correlation and particle filters. This method can be used for localization of autonomous mobile robots inside of buildings. The method contains two parts. The first one is mapping of environment, where the mobile robot operates. For this purpose was used phase correlation and images stitching method. The second one is localization problem, which was solved by particle filters, where a particles weights re-sampling was realized by phase correlation image processing method as well. Localization uses the map, which was created by phase correlation and stitching method.

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Acknowledgments

This research was supported by grant of BUT IGA No. FSI-S-14-2533: “Applied Computer Science and Control”.

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Authors and Affiliations

  1. Faculty of Mechanical Engineering: Institute of Automation and Computer Science, Brno University of Technology, Technická 2896/2616 69, Brno, Czech Republic

    Michal Růžička & Petr Mašek

Authors
  1. Michal Růžička
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  2. Petr Mašek
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Corresponding author

Correspondence to Michal Růžička .

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Editors and Affiliations

  1. Faculty of Mechanical Engineering, Department of Applied Computer Science, Brno University of Technology, Brno, Czech Republic

    Radek Matoušek

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Růžička, M., Mašek, P. (2015). Visual SLAM Based on Phase Correlation and Particle Filters. In: Matoušek, R. (eds) Mendel 2015. ICSC-MENDEL 2016. Advances in Intelligent Systems and Computing, vol 378. Springer, Cham. https://doi.org/10.1007/978-3-319-19824-8_29

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  • DOI: https://doi.org/10.1007/978-3-319-19824-8_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19823-1

  • Online ISBN: 978-3-319-19824-8

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