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Vision-Based Hybrid Map Building for Mobile Robot Navigation

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Book cover Intelligent Autonomous Systems 13

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 302))

Abstract

A hybrid mapping framework is presented in this work. The goal is to obtain better computational efficiency than pure metrical mapping techniques and better accuracy as well as usability for robot guidance and navigation compared to the topological mapping. Image sequences acquired in an environment by manually driving a robot are used to build a hierarchical map representation by using an image sequence partitioning (ISP) technique that uses local image features. The hierarchical map built can be understood as a topological map with nodes corresponding to certain regions in the environment. Each node in turn is made up of a set of images acquired in that region. These maps are further augmented with metrical information at those nodes which correspond to image subsequences acquired while the robot is turning as a part of its trajectory. Metrical information becomes invaluable during autonomous robot navigation through these places. Hence, we call the resulting maps hybrid since they primarily contain topological information and metrical information at places that are important for navigation. Experimental results obtained on a sequence acquired in an outdoor environment are provided to demonstrate our approach.

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Notes

  1. 1.

    The IP datasets website is: http://ipds.univ-bpclermont.fr/.

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Authors and Affiliations

  1. Institut Pascal, Université Blaise Pascal, 24 Avenue des Landais, 63140, Aubière, France

    Ferit Üzer, Hemanth Korrapati, Eric Royer & Youcef Mezouar

  2. Intelligent Systems Research Institute, School of Information and Communication Engineering and the Interaction Science Department of Sungkyunkwan University, Seoul, South Korea

    Ferit Üzer & Sukhan Lee

Authors
  1. Ferit Üzer
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  2. Hemanth Korrapati
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  3. Eric Royer
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  4. Youcef Mezouar
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  5. Sukhan Lee
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Corresponding author

Correspondence to Ferit Üzer .

Editor information

Editors and Affiliations

  1. Information Engineering, University of Padua, Padua, Italy

    Emanuele Menegatti

  2. Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

    Nathan Michael

  3. Fachbereich Informatik, Technische Universität Kaiserslautern Arbeitsgruppe Robotersysteme, Kaiserslautern, Germany

    Karsten Berns

  4. Integrated Information Technology, Aoyama Gakuin University, Tokyo, Japan

    Hiroaki Yamaguchi

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Üzer, F., Korrapati, H., Royer, E., Mezouar, Y., Lee, S. (2016). Vision-Based Hybrid Map Building for Mobile Robot Navigation. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_11

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  • DOI: https://doi.org/10.1007/978-3-319-08338-4_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08337-7

  • Online ISBN: 978-3-319-08338-4

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