Visual topological SLAM and global localization

  • Authors:

  • Adrien Angeli;Stéphane Doncieux;Jean-Arcady Meyer;David Filliat

  • Affiliations:

  • Université Pierre et Marie Curie-Paris 6, FRE, ISIR, Paris, France;Université Pierre et Marie Curie-Paris 6, FRE, ISIR, Paris, France;Université Pierre et Marie Curie-Paris 6, FRE, ISIR, Paris, France;UEI, ENSTA, Paris, France

  • Venue:
  • ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
  • Year:
  • 2009

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Abstract

Visual localization and mapping for mobile robots has been achieved with a large variety of methods. Among them, topological navigation using vision has the advantage of offering a scalable representation, and of relying on a common and affordable sensor. In previous work, we developed such an incremental and real-time topological mapping and localization solution, without using any metrical information, and by relying on a Bayesian visual loop-closure detection algorithm. In this paper, we propose an extension of this work by integrating metrical information from robot odometry in the topological map, so as to obtain a globally consistent environment model. Also, we demonstrate the performance of our system on the global localization task, where the robot has to determine its position in a map acquired beforehand.