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Hybrid Metric-topological Mapping for Large Scale Monocular SLAM

  • Eduardo Fernández-MoralEmail author
  • Vicente Arévalo
  • Javier González-Jiménez
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 325)

Abstract

Simultaneous Localization and Mapping (SLAM) is a central problem for autonomous mobile robotics. Monocular SLAM is one of the ways to tackle the problem, where the only input information are the images from a moving camera. Current approaches for this problem have achieved a good balance between accuracy and density of the map, however, they are not suited for large scale. In this paper, we present a dynamic mapping strategy where the metric map is divided into regions with highly connected observations, resulting in a topological structure which permits the efficient augmentation and optimization of the map. For that, a graph representation where the nodes represent keyframes, and their connections are a measure of their overlapping, is continuously rearranged. The experiments show that this hybrid metric-topological approach outperforms the efficiency and scalability of previous approaches.

Keywords

Monocular SLAM Metric-topological mapping Map partitioning 

Notes

Acknowledgments

This work has been supported by the project “TAROTH: New developments toward a robot at home”, funded by the Spanish Government and the “European Regional Development Fund ERD” under contract DPI2011-25483.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Eduardo Fernández-Moral
    • 1
    Email author
  • Vicente Arévalo
    • 1
  • Javier González-Jiménez
    • 1
  1. 1.MAPIR Group, Universidad de Málaga, E.T.S. Ingeniería de Informática-Telecomunicación, Campus de TeatinosMálagaSpain

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