This paper describes the work for the design and development of an autonomous underwater vehicle (AUV). The reference missions are sea bottom surveys and sealines inspections. A vision-based system for the automatic underwater vehicle is presented. The detection of underwater pipeline borders and its symmetry axis is performed. The method adopted for edge detection consists of two steps: 1) a backpropagation neural network is applied to segment the underwater image into different regions; and 2) for each region, the best fit segment and the related parameters are extracted. Since the information on which regions are the right pipeline edges does not depend only on single region characteristics, but also on relations between regions, all the possible regions pairs are analyzed, in order to determine the right one. Satisfactory results are also obtained for pipelines partially covered by sand.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A vision-based system for autonomous underwater vehicle navigation


    Contributors:
    Foresti, G.L. (author) / Gentili, S. (author) / Zampato, M. (author)


    Publication date :

    1998


    Size :

    5 Seiten, 9 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Autonomous Underwater Vehicle Navigation

    P. A. Miller / J. Farrell / Y. Zhao et al. | NTIS | 2008


    Autonomous Underwater Vehicle Navigation

    Leonard, John J. / Bahr, Alexander | Springer Verlag | 2016



    Vision system research for autonomous underwater vehicle

    Yuan, Xiaohai / Qiu, Chenchang / Chen, Rongsheng et al. | Tema Archive | 1997


    Vision-based navigation system for autonomous transportation vehicle

    Morimoto, E. / Suguri, M. / Sakon, Y. et al. | British Library Conference Proceedings | 2001