This paper presents a method to forecast terrain trafficability from visual appearance. During training, the system identifies a set of image chips (or exemplars) that span the range of terrain appearance and measures terrain trafficability characteristics as the vehicle traverses the terrain. Each chip is assigned a vector tag representing the measured vehicle-terrain interaction properties. After training, the system uses the exemplars to segment images into regions, based on visual similarity to terrain patches observed during training, and assigns the appropriate vehicle-terrain interaction tag to them. The system will therefore allow the online forecasting of vehicle performance on upcoming terrain.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen


    Exportieren, teilen und zitieren



    Titel :

    Image Understanding for Robot Navigation


    Beteiligte:
    R. E. Karlsen (Autor:in) / G. Witus (Autor:in)

    Erscheinungsdatum :

    2006


    Format / Umfang :

    9 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch




    SMART NAVIGATION ROBOT

    CHEN YONG PING | Europäisches Patentamt | 2019

    Freier Zugriff

    Image mosaicing for visual feedback in ground robot navigation

    Esquivel-Hernandez, Sofia / Juarez-Salazar, Rigoberto / Gudino-Lau, Jorge | SPIE | 2021


    Autonomous Navigation Robot Based on Real-Time Image Processing

    Rai, Bijay / Pradhan, Pratik / Pradhan, Roshan | Springer Verlag | 2017


    ROBOT NAVIGATION METHOD, CHIP AND ROBOT

    SUN YONGQIANG | Europäisches Patentamt | 2024

    Freier Zugriff

    Self-Balancing Robot Navigation

    Maghfiroh, Hari / Probo Santoso, Henry | BASE | 2021

    Freier Zugriff