The use of autonomous underwater vehicles (AUVs) for visual inspection tasks is a promising robotic field. The images captured by the robots can also aid in their localization/navigation. In this context, this paper proposes an approach to localization and mapping problem of underwater vehicle. Supposing the use of inspection cameras, this proposal is composed of two stages: i) the use of computer vision through the algorithm SIFT to extract the features in underwater image sequences and; ii) the development of topological maps to localization and navigation. The integration of such systems will permit simultaneous localization and mapping of the environment. A set of tests with real robots was accomplished, regarding online and performance issues. The results reveals an accuracy and robust approach to several bottom conditions, illumination and noise, leading to a promissory and original SLAM technique.


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    Titel :

    NLMAP: visual-based self localization and mapping for autonomous underwater vehicles


    Beteiligte:
    Botelho, S. (Autor:in) / Drews, P. jun. (Autor:in) / Leivas, G. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2008


    Format / Umfang :

    6 Seiten, 26 Quellen




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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