In this paper we present our research work on self-Iocalization of the vehicle (ego-state) aided by visual features and maps. This approach requires only last received GPS location, Odometry estimates as the vehicle moves, a database of visual features around the last received GPS estimate and Standard Definition (SD) Map. Towards this goal, we extract Oriented and Rotated Brief (ORB) Descriptors from the Images collected during a drive and use Bag of Words (BoW) approach for creating a vocabulary of visual words. We also use Inverted File Index method for fast querying of the image descriptor that is seen currently by the ego vehicle against a database of all the descriptors collected for finding the possible locations of the robot. The locations for the corresponding matches are then used to update the measurement model. This approach has helped us to localize within 3 seconds with average position and orientation error of 0.8 m and 0.38 degree respectively for all the sequences.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Improved localization using visual features and maps for Autonomous Cars


    Beteiligte:


    Erscheinungsdatum :

    01.06.2018


    Format / Umfang :

    2590818 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    IMPROVED LOCALIZATION USING VISUAL FEATURES AND MAPS FOR AUTONOMOUS CARS

    Rangan, Sathya Narayanan Kasturi / Yalla, Veera Ganesh / Bacchet, Davide et al. | British Library Conference Proceedings | 2018


    Lane Localization for Autonomous Model Cars

    Maischak, Lukas | DataCite | 2014


    Visual Localization for Autonomous Driving using Pre-built Point Cloud Maps

    Yabuuchi, Kento / Wong, David Robert / Ishita, Takeshi et al. | IEEE | 2021


    Re-localization for Self-Driving Cars using Semantic Maps

    Kenye, Lhilo / Palugulla, Rishitha / Arora, Mehul et al. | IEEE | 2020


    Traffic Light Recognition Using Deep Learning and Prior Maps for Autonomous Cars

    Possatti, Lucas C. / Guidolini, Rânik / Cardoso, Vinicius B. et al. | ArXiv | 2019

    Freier Zugriff