Automated acquisition of anisotropic friction

Keno Dressel, Kenny Erleben, Paul Kry, Sheldon Andrews

    1 Citationer (Scopus)

    Abstract

    Automated acquisition of friction data is an interesting approach to more successfully bridge the reality gap in simulation than conventional mathematical models. To advance this area of research, we present a novel inexpensive computer vision platform as a solution for collecting and processing friction data, and we make available the open source software and data sets collected with our vision robotic approach. This paper is focused on gathering data on anisotropic static friction behavior as this is ideal for inexpensive vision approach we propose. The data set and experimental setup provide a solid foundation for a wider robotics simulation community to conduct their own experiments.

    OriginalsprogEngelsk
    TitelProceedings - 2019 16th Conference on Computer and Robot Vision, CRV 2019
    Antal sider7
    ForlagIEEE
    Publikationsdatomaj 2019
    Sider159-165
    Artikelnummer8781610
    ISBN (Elektronisk)9781728118383
    DOI
    StatusUdgivet - maj 2019
    Begivenhed16th Conference on Computer and Robot Vision, CRV 2019 - Kingston, Canada
    Varighed: 29 maj 201931 maj 2019

    Konference

    Konference16th Conference on Computer and Robot Vision, CRV 2019
    Land/OmrådeCanada
    ByKingston
    Periode29/05/201931/05/2019
    SponsorCanadian Image Processing and Pattern Recognition Society / Association Canadienne de Traitement d�Images et de Reconnaissance des Formes (CIPPRS/ACTIRF)

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