Real–Time Hierarchical GPS Aided Visual SLAM on Urban Environments

  • David Schleicher
  • Luis M. Bergasa
  • Manuel Ocaña
  • Rafael Barea
  • Elena López
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5717)


In this paper we present a new real-time hierarchical (topological/metric) Visual SLAM system focusing on the localization of a vehicle in large-scale outdoor urban environments. It is exclusively based on the visual information provided by both a low-cost wide-angle stereo camera and a low-cost GPS. Our approach divides the whole map into local sub-maps identified by the so-called fingerprint (reference poses). At the sub-map level (Low Level SLAM), 3D sequential mapping of natural landmarks and the vehicle location/orientation are obtained using a top-down Bayesian method to model the dynamic behavior. A higher topological level (High Level SLAM) based on references poses has been added to reduce the global accumulated drift, keeping real-time constraints. Using this hierarchical strategy, we keep local consistency of the metric sub-maps, by mean of the EKF, and global consistency by using the topological map and the MultiLevel Relaxation (MLR) algorithm. GPS measurements are integrated at both levels, improving global estimation. Some experimental results for different large-scale urban environments are presented, showing an almost constant processing time.


SLAM Intelligent Vehicles Computer Vision Real-Time 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • David Schleicher
    • 1
  • Luis M. Bergasa
    • 1
  • Manuel Ocaña
    • 1
  • Rafael Barea
    • 1
  • Elena López
    • 1
  1. 1.Department of ElectronicsUniversity of AlcalaMadridSpain

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