We develop two algorithms to register a range scan to a previous scan so as to compute relative robot positions in an unknown environment. The first algorithm is used on matching tangent lines defined on two scans and minimizing a distance function. The second algorithm iteratively establishes correspondences between points in the two scans and then solves the point-to-point least-squares problem to compute the relative pose. Our methods avoid the use of localized features. They work in curved environments and can handle partial occlusions.<>


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    Titel :

    Robot pose estimation in unknown environments by matching 2D range scans


    Beteiligte:
    Feng Lu (Autor:in) / Milios (Autor:in)


    Erscheinungsdatum :

    01.01.1994


    Format / Umfang :

    369243 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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