Geintra

Departamento de electronica Universidad de Alcala

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    Localization of Mobile Robots Using Odometry and an External Vision Sensor

    TítuloLocalization of Mobile Robots Using Odometry and an External Vision Sensor
    Tipo de publicaciónJournal Article
    Año de publicación2010
    AutoresPizarro, D, Mazo, M, Santiso, E, Marron, M, Jimenez, D, Cobreces, S, Losada-Gutiérrez, C
    Idioma de publicaciónEnglish
    Revista académicaSensors
    Volumen10
    Número4
    Páginas3655-3680
    Fecha de publicación04/2010
    EditorialMDPI - Open Access Publishing
    ISSN1424-8220
    JCR Impact Factor1.821
    Palabras claveartificial vision, Intelligent spaces, robotics
    Rank in category11/58
    JCR CategoryINSTRUMENTS & INSTRUMENTATION
    DOI10.3390/s100403655
    URLhttp://www.mdpi.com/1424-8220/10/4/3655/
    Resumen

    This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields.

    Resumen

    This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields.

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