Distance measure with computer vision and neural networks for underwater applications

Luis M. Aristizabal, Carlos A. Zuluaga

    Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

    3 Citas (Scopus)

    Resumen

    This document describes a distance measurement system for underwater applications with computer vision and an Artificial Neural Network (ANN). The developed system is installed in the observation class remotely operated vehicle (ROV) Visor3, to be used in experimental testing. An integrated camera with two laser pointers are used to obtain input data to a Multi-Layer Perceptron (MLP) ANN, trained with a resilient backpropagation algorithm (RPROP). The solution described in this paper is an alternative to other methods found in the literature. Experimental results are presented.

    Idioma originalInglés
    Título de la publicación alojada2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings
    EditoresHenry Carrillo Lindado
    EditorialInstitute of Electrical and Electronics Engineers Inc.
    ISBN (versión digital)9781509037872
    DOI
    EstadoPublicada - 9 ene. 2017
    Evento1st IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Bogota D.C., Colombia
    Duración: 29 sept. 201630 sept. 2016

    Serie de la publicación

    Nombre2016 IEEE Colombian Conference on Robotics and Automation, CCRA 2016 - Conference Proceedings

    Conferencia

    Conferencia1st IEEE Colombian Conference on Robotics and Automation, CCRA 2016
    País/TerritorioColombia
    CiudadBogota D.C.
    Período29/09/1630/09/16

    Nota bibliográfica

    Publisher Copyright:
    © 2016 IEEE.

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