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Vision-Based Semantic-Map Building and Localization

  • Conference paper
Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4251))

Abstract

A semantic-map building method is proposed to localize a robot in the semantic-map. Our semantic-map is organized by using SIFT feature-based object representation. In addition to semantic map, a vision-based relative localization is employed as a process model of extended Kalman filters, where optical flows and Levenberg-Marquardt least square minimization are incorporated to predict relative robot locations. Thus, robust SLAM performances can be obtained even under poor conditions in which localization cannot be achieved by classical odometry-based SLAM.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Hanyang University, 17 Haengdang-dong, Sungdong-gu, Seoul, 133-791, Korea

    Seungdo Jeong

  2. School of Information and Communications, Hanyang University,  

    Jounghoon Lim, Hong Il Suh & Byung-Uk Choi

Authors
  1. Seungdo Jeong
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  2. Jounghoon Lim
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  3. Hong Il Suh
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  4. Byung-Uk Choi
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Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK

    Bogdan Gabrys

  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes, 5095, SA, Australia

    Lakhmi C. Jain

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© 2006 Springer-Verlag Berlin Heidelberg

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Jeong, S., Lim, J., Suh, H.I., Choi, BU. (2006). Vision-Based Semantic-Map Building and Localization. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11892960_68

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  • DOI: https://doi.org/10.1007/11892960_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46535-5

  • Online ISBN: 978-3-540-46536-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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