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    Improved LiDAR Probabilistic Localization for Autonomous Vehicles Using GNSS

    Improved LiDAR Probabilistic Localization for Autonomous Vehicles Using GNSS

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    This paper proposes a method that improves autonomous vehicles localization using a modification of probabilistic laser localization like Monte Carlo Localization (MCL) algorithm, enhancing the weights of the particles by adding Kalman filtered Global Navigation Satellite System (GNSS) information. GNSS data are used to improve localization accuracy in places with fewer map features and to prevent the kidnapped robot problems. Besides, laser information improves accuracy in places where the map has more features and GNSS higher covariance, allowing the approach to be used in specifically difficult scenarios for GNSS such as urban canyons. The algorithm is tested using KITTI odometry dataset proving that it improves localization compared with classic GNSS + Inertial Navigation System (INS) fusion and Adaptive Monte Carlo Localization (AMCL), it is also tested in the autonomous vehicle platform of the Intelligent Systems Lab (LSI), of the University Carlos III de of Madrid, providing qualitative results. ; Research supported by the Spanish Government through the CICYT projects (TRA2016-78886-C3-1-Rand RTI2018-096036-B-C21), Universidad Carlos III of Madrid through (PEAVAUTO-CM-UC3M) and the Comunidad de Madrid through SEGVAUTO-4.0-CM (P2018/EMT-4362).

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    Titel :

    Improved LiDAR Probabilistic Localization for Autonomous Vehicles Using GNSS

    Beteiligte:
    Miguel Paraiso, Miguel Ángel de (Autor:in) / García Fernández, Fernando (Autor:in) / Armingol Moreno, José María (Autor:in) / Comunidad de Madrid / Ministerio de Economía y Competitividad (España)
    Erscheinungsdatum :

    2020-06-02

    Anmerkungen:

    AR/0000025768

    DOI :

    https://doi.org/10.3390/s20113145

    Medientyp :

    Aufsatz (Zeitschrift)

    Format :

    Elektronische Ressource

    Sprache :

    Englisch

    Schlagwörter :

    Localization , LiDAR , GNSS , Global Positioning System (GPS) , Monte carlo , Particle filter , Autonomous driving , Robótica e Informática Industrial

    Klassifikation :

    DDC:    629

    Lizenzbestimmungen :

    http://creativecommons.org/licenses/by/3.0/es/

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