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Man–Machine Interactions 4 pp 161–168Cite as

Incorporating Static Environment Elements into the EKF-Based Visual SLAM

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 391))

Abstract

The paper presents a visual simultaneous localization and mapping (SLAM) system extended to work with additional, static elements of the environment. Additional measurements have been introduced by incorporating the static surveillance cameras and artificial markers placed in the environment. This reduced the influence of the inherent scale ambiguity of the monocular systems and the tracking drift on the trajectory tracking. Consequently, the root mean square of the absolute trajectory error was reduced by \(23\,\%\) when compared to the well-established MonoSLAM system.

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References

  1. Baczyk, R., Kasiński, A.: Visual simultaneous localisation and map-building supported by structured landmarks. Int. J. Appl. Math. Comput. Sci. 20(2), 281–293 (2010)

    Article  MATH  Google Scholar 

  2. Civera, J., Davison, A.J., Montiel, J.: Inverse depth parametrization for monocular SLAM. IEEE Trans. Robot. 24(5), 932–945 (2008)

    Article  Google Scholar 

  3. Davison, A.J., Reid, I.D., Molton, N.D., Stasse, O.: MonoSLAM: real-time single camera SLAM. IEEE Trans. Pattern Anal. Mach. Intell. 29(6), 1052–1067 (2007)

    Article  Google Scholar 

  4. Klein, G., Murray, D.: Parallel tracking and mapping for small AR workspaces. In: ISMAR 2007, pp. 225–234, Nara, Japan (2007)

    Google Scholar 

  5. Konolige, K., Agrawal, M.: FrameSLAM: from bundle adjustment to real-time visual mapping. IEEE Trans. Robot. 24(5), 1066–1077 (2008)

    Article  Google Scholar 

  6. Kummerle, R., Grisetti, G., Strasdat, H., Konolige, K., Burgard, W.: g2o: a general framework for graph optimization. In: ICRA 2011, pp. 3607–3613, Shanghai, China (2011)

    Google Scholar 

  7. Montemerlo, M., Thrun, S., Koller, D., Wegbreit, B., et al.: FastSLAM: a factored solution to the simultaneous localization and mapping problem. In: AAAI 2002, Edmonton, Canada (2002)

    Google Scholar 

  8. Schmidt, A., Fularz, M., Kraft, M., Kasiński, A., Nowicki, M.: An indoor RGB-D dataset for the evaluation of robot navigation algorithms. In: Blanc-Talon, J., Kasinski, A., Philips, W., Popescu, D., Scheunders, P. (eds.) Advanced Concepts for Intelligent Vision Systems, LNCS, vol. 8192, pp. 321–329. Springer, Switzerland (2013)

    Chapter  Google Scholar 

  9. Schmidt, A., Kasiński, A.: The visual SLAM system for a hexapod robot. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds.) Computer Vision and Graphics, LNCS, vol. 6375, pp. 260–267. Springer, Berlin Heidelberg, Germany (2010)

    Chapter  Google Scholar 

  10. Schmidt, A., Kasiński, A., Kraft, M., Fularz, M., Domagała, Z.: Calibration of the multi-camera registration system for visual navigation benchmarking. Int. J. Adv. Rob. Syst. 11, 83 (2014)

    Google Scholar 

  11. Sturm, J., Magnenat, S., Engelhard, N., Pomerleau, F., Colas, F., Burgard, W., Cremers, D., Siegwart, R.: Towards a benchmark for RGB-D slam evaluation. In: RGB-D Workshop on Advanced Reasoning with Depth Cameras at Robotics: RSS 2011, Los Angeles, USA (2011)

    Google Scholar 

  12. Suzuki, S., et al.: Topological structural analysis of digitized binary images by border following. Comput. Vis. Graph. Image. Process. 30(1), 32–46 (1985)

    Article  MATH  Google Scholar 

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Acknowledgments

This research was supported by the Polish National Science Centre grant funded according to the decision DEC-2011/01/N/ST7/05940.

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Authors and Affiliations

  1. Poznan University of Technology, Poznan, Poland

    Adam Schmidt

Authors
  1. Adam Schmidt
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Correspondence to Adam Schmidt .

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Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Aleksandra Gruca

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Agnieszka Brachman

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Tadeusz Czachórski

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Schmidt, A. (2016). Incorporating Static Environment Elements into the EKF-Based Visual SLAM. In: Gruca, A., Brachman, A., Kozielski, S., Czachórski, T. (eds) Man–Machine Interactions 4. Advances in Intelligent Systems and Computing, vol 391. Springer, Cham. https://doi.org/10.1007/978-3-319-23437-3_13

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  • DOI: https://doi.org/10.1007/978-3-319-23437-3_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23436-6

  • Online ISBN: 978-3-319-23437-3

  • eBook Packages: EngineeringEngineering (R0)

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