The aim of this paper is to contribute with an object-based learning and selection methods to improve localization and mapping techniques. The methods use 3D-LiDAR data which is suitable for autonomous driving systems operating in urban environments. The objects of interest to be served as landmarks are pole-like objects which are naturally present in the environment. To detect and recognize pole-like objects in 3D-LiDAR data, a semi-supervised iterative label propagation method has been developed. Additionally, a selection method is proposed for selection the best poles to be used in the localization loop. The LiDAR localization and mapping system is validated using data from the KITTI database. Reported results show that by considering the occurrence of pole-like objects over time leads to an improvement on both the learning model and the localization.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Improving Localization by Learning Pole-Like Landmarks Using a Semi-supervised Approach


    Weitere Titelangaben:

    Advs in Intelligent Syst., Computing


    Beteiligte:
    Silva, Manuel F. (Herausgeber:in) / Luís Lima, José (Herausgeber:in) / Reis, Luís Paulo (Herausgeber:in) / Sanfeliu, Alberto (Herausgeber:in) / Tardioli, Danilo (Herausgeber:in) / Barros, Tiago (Autor:in) / Garrote, Luís (Autor:in) / Pereira, Ricardo (Autor:in) / Premebida, Cristiano (Autor:in) / Nunes, Urbano J. (Autor:in)

    Kongress:

    Iberian Robotics conference ; 2019 ; Porto, Portugal November 20, 2019 - November 22, 2019



    Erscheinungsdatum :

    20.11.2019


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Improving Localization by Learning Pole-Like Landmarks Using a Semi-supervised Approach

    Barros, Tiago / Garrote, Luís / Pereira, Ricardo et al. | TIBKAT | 2020


    Improving vehicle localization using semantic and pole-like landmarks

    Sefati, M. / Daum, M. / Sondermann, B. et al. | IEEE | 2017


    Improving Vehicle Localization Using Semantic and Pole-Like Landmarks (I)

    Sefati, Mohsen / Daum, Magnus / Sondermann, Björn et al. | British Library Conference Proceedings | 2017


    Improving vehicle localization using pole-like landmarks extracted from 3-D lidar scans

    Lee, Sheng-Wei / Lin, Peng-Wei / Fu, Yuan-Ting et al. | IEEE | 2020


    IMPROVING VEHICLE LOCALIZATION USING POLE-LIKE LANDMARKS EXTRACTED FROM 3-D LIDAR SCANS

    Lee, Sheng-Wei / Lin, Peng-Wei / Fu, Yuan-Ting et al. | British Library Conference Proceedings | 2020