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Vision-Based Hybrid Map Building for Mobile Robot Navigation

  • Ferit Üzer
  • Hemanth Korrapati
  • Eric Royer
  • Youcef Mezouar
  • Sukhan Lee
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (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.

Keywords

Topological map Metric map Topometric mapping SLAM Robot navigation Autonomous robots Vision Loop closure 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ferit Üzer
    • 1
    • 2
  • Hemanth Korrapati
    • 1
  • Eric Royer
    • 1
  • Youcef Mezouar
    • 1
  • Sukhan Lee
    • 2
  1. 1.Institut PascalUniversité Blaise PascalAubièreFrance
  2. 2.Intelligent Systems Research InstituteSchool of Information and Communication Engineering and the Interaction Science Department of Sungkyunkwan UniversitySeoulSouth Korea

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