Mobile robots currently cannot detect and read arbitrary signs. This is a major hindrance to mobile robot usability, since they cannot be tasked using directions that are intuitive to humans. It also limits their ability to report their position relative to intuitive landmarks. Other researchers have demonstrated some success on traffic sign recognition, but using template based methods limits the set of recognizable signs. There is a clear need for a sign detection and recognition system that can process a much wider variety of signs: traffic signs, street signs, store-name signs, building directories, room signs, etc. We are developing a system for Sign Understanding in Support of Autonomous Navigation (SUSAN), that detects signs from various cues common to most signs: vivid colors, compact shape, and text. We have demonstrated the feasibility of our approach on a variety of signs in both indoor and outdoor locations.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Sign detection for autonomous navigation


    Beteiligte:

    Kongress:

    Unmanned Ground Vehicle Technology V ; 2003 ; Orlando,Florida,United States


    Erschienen in:

    Proc. SPIE ; 5083 ; 219


    Erscheinungsdatum :

    30.09.2003





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Traffic Sign and Obstacle Detection for Autonomous Vehicle Navigation using Edge Computing

    Vijayalakshmi, M. / Bharathwaj, M. / Dharshini, D. Anjelin Deva | IEEE | 2025


    Traffic Sign Detection for Navigation of Autonomous Car Prototype using Convolutional Neural Network

    Ikhlayel, Mohammed / Iswara, Adre Johan / Kurniawan, Arief et al. | IEEE | 2020


    Intelligent autonomous navigation underwater detection robot

    CHEN WENSHU / ZHAO YUHANG | Europäisches Patentamt | 2021

    Freier Zugriff