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Enhanced Monte Carlo Localization with Visual Place Recognition for Robust Robot Localization

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Abstract

This paper proposes extending Monte Carlo Localization methods with visual place recognition information in order to build a robust robot localization system. This system is aimed to work in crowded and non-planar scenarios, where 2D laser rangefinders may not always be enough to match the robot position within the map. Thus, visual place recognition will be used in order to obtain robot position clues that can be used to detect when the robot is lost and also to reset its positions to the right one. The paper presents experimental results based on datasets gathered with a real robot in challenging scenarios.

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Authors and Affiliations

  1. University Pablo de Olavide, Seville, Spain

    Javier Pérez & Luis Merino

  2. University of Seville, Seville, Spain

    Fernando Caballero

Authors
  1. Javier Pérez
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  2. Fernando Caballero
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  3. Luis Merino
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Corresponding author

Correspondence to Javier Pérez.

Additional information

This paper is an extension of work presented at ICARSC 2014 [14] and is partially supported by the FP7 FROG Project (Contract 288235) funded by the European Commission and the PAIS-MultiRobot Project (TIC-7390) funded by Regional Government of Andalucía

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Pérez, J., Caballero, F. & Merino, L. Enhanced Monte Carlo Localization with Visual Place Recognition for Robust Robot Localization. J Intell Robot Syst 80, 641–656 (2015). https://doi.org/10.1007/s10846-015-0198-y

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  • DOI: https://doi.org/10.1007/s10846-015-0198-y

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