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A Landmark Vector Approach Using Gray-Colored Information

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From Animals to Animats 14 (SAB 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9825))

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Abstract

Homing navigation is an important aspect in navigation behaviours of animals. There has been many types of navigation but we focus on the vision-based landmark navigation to return home. Visual navigation is involved with image matching process over snapshot images. Landmark vector methods simplify the environmental information into a set of landmark vectors, and then compare the landmark vectors obtained from each snapshot. In this paper, we encode landmark vectors using the gray-colored values as the length of vectors. Then we apply the landmark arrangement method to those landmark vectors. Using the gray-colored information, we can estimate the homing direction at a given position. We show that the suggested method is effective in homing navigation.

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Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2014R1A2A1A11053839).

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Authors and Affiliations

  1. Biological Cybernetics Lab, School of Electrical and Electronic Engineering, Yonsei University, Shinchon, Seoul, 120-749, South Korea

    Changmin Lee & DaeEun Kim

Authors
  1. Changmin Lee
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  2. DaeEun Kim
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Corresponding author

Correspondence to Changmin Lee .

Editor information

Editors and Affiliations

  1. Aberystwyth University, Aberystwyth, United Kingdom

    Elio Tuci

  2. Aberystwyth University, Aberystwyth, United Kingdom

    Alexandros Giagkos

  3. Aberystwyth University, Aberystwyth, United Kingdom

    Myra Wilson

  4. University of Southern Denmark, Odense, Denmark

    John Hallam

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Lee, C., Kim, D. (2016). A Landmark Vector Approach Using Gray-Colored Information. In: Tuci, E., Giagkos, A., Wilson, M., Hallam, J. (eds) From Animals to Animats 14. SAB 2016. Lecture Notes in Computer Science(), vol 9825. Springer, Cham. https://doi.org/10.1007/978-3-319-43488-9_13

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  • DOI: https://doi.org/10.1007/978-3-319-43488-9_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43487-2

  • Online ISBN: 978-3-319-43488-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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