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Vision-Based Self-localization of Autonomous Guided Vehicle Using Landmarks of Colored Pentagons

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Advances in Visual Computing (ISVC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4291))

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Abstract

This paper describes an idea for determining self-organization using visual land marks. The critical geometric dimensions of a pentagon are used here to locate the relative position of the mobile robot with respect to the pattern. This method has the advantages of simplicity and flexibility. This pentagon is also provided with a unique identification, using invariant features and colors that enable the system to find the absolute location of the patterns. This algorithm determines both the correspondence between observed landmarks and a stored sequence, computes the absolute location of the observer using those correspondences, and calculates relative position from a pentagon using its five vertices. The algorithm has been implemented and tested. In several trials it computes location accurate to within 5.4 centimeters in less than 0.3 second.

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References

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Author information

Authors and Affiliations

  1. Research & Development Division for Hyudai Motor Company & Kia Motors Corporation,  

    Y. S. Kim

  2. Department of Electronic Engineering, Seonam University, Namwon, Chonbuk, 590-711, Korea

    J. C. Kim

  3. Department of Electronic Engineering Chonbuk National University, Jeonju, Chonbuk, 560-756, Korea

    E. J. Park & Joonwhoan Lee

Authors
  1. Y. S. Kim
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  2. J. C. Kim
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  3. E. J. Park
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  4. Joonwhoan Lee
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Digital Image Research Center, Kingston University, London, UK

    Paolo Remagnino

  6. Intel, 95052, Santa Clara, CA, USA

    Ara Nefian

  7. University of California, 430, Computer Science Building, 92697-3425, Irvine, CA, USA

    Gopi Meenakshisundaram

  8. Institute for Data Analysis and Visualization, P.O. Box

    Valerio Pascucci

  9. Department of Computer Science and Engineering, Czech Technical University in Prague, Czech

    Jiri Zara

  10. Rockwell Scientific, 1049 Camino Dos Rios, 91360, Thousand Oaks, CA, USA

    Jose Molineros

  11. Computer Graphics Group, Bielefeld University, D-33501, Bielefeld, Germany

    Holger Theisel

  12. Hewlett Packard Labs, Palo Alto, CA, USA

    Tom Malzbender

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Kim, Y.S., Kim, J.C., Park, E.J., Lee, J. (2006). Vision-Based Self-localization of Autonomous Guided Vehicle Using Landmarks of Colored Pentagons. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2006. Lecture Notes in Computer Science, vol 4291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11919476_14

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  • DOI: https://doi.org/10.1007/11919476_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-48628-2

  • Online ISBN: 978-3-540-48631-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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