In this paper, we proposed a vision based global localization approach for intelligent vehicles. A single camera is used to determine vehicle's lateral and longitudinal offsets with respect to the road. Since the number of horizontal landmarks on the road is limited, an Extended Kalman Filter is used to fuse the results of odometry and vision, which also improves the system's reliability in case that landmarks disappear from camera's field of view. If locations of the landmarks are known a priori, the global pose of the vehicle can be estimated by the proposed methods. The algorithm is composed of two steps. landmarks detection using Randomized Hough Transform and data fusion with odometry. Experimental results with real data prove the high accuracy and low computation.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Vision Based Global Localization for Intelligent Vehicles


    Beteiligte:
    Xia, T.K. (Autor:in) / Yang, M. (Autor:in) / Yang, R.Q. (Autor:in)


    Erscheinungsdatum :

    01.01.2006


    Format / Umfang :

    3861896 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Vision Based Global Localization for Intelligent Vehicles

    Xia, T. K. / Yang, M. / Yang, R. Q. | British Library Conference Proceedings | 2006


    Vision based method for the localization of intelligent vehicles in loose constraint area

    Liu, Xiaonan / Xiong, Guangming / Gong, Jianwei et al. | IEEE | 2016


    Vision-based perception for intelligent vehicles

    Broggi, Alberto | IEEE | 2015

    Freier Zugriff

    Ground Texture Matching Based Global Localization for Intelligent Vehicles in Urban Environment

    Fang, H. / Yang, M. / Yang, R. et al. | British Library Conference Proceedings | 2007