Geintra

Departamento de electronica Universidad de Alcala

Líneas de investigación

Accede a información sobre la estructura de la actividad investigadora de Geintra.

Trabaja con nosotros

Accede a nuestra oferta actual de becas, tesis doctorales, contratos y trabajos fin de carrera.

Contacta con el grupo

Si desea contactar con nosotros, puede usar varios medios.

    Identification and Tracking of Robots in an Intelligent Space using Static Cameras and an XPFCP

    TítuloIdentification and Tracking of Robots in an Intelligent Space using Static Cameras and an XPFCP
    Tipo de publicaciónJournal Article
    Año de publicación2013
    AutoresLosada-Gutiérrez, C, Mazo, M, Palazuelos, SE, Pizarro, D, Marron, M, Velasco, JF
    Idioma de publicaciónEnglish
    Revista académicaRobotics and Autonomous Systems
    Volumen61
    Número2
    Páginas75-86
    Fecha de publicación02/2013
    ISSN0921-8890
    DOI10.1016/j.robot.2012.11.007
    Resumen

    This paper tackles the problem of identification and tracking of multiple
    robots in an intelligent space using an array of cameras placed in fixed positions within the environment. Several types of agents can be found in an
    intelligent space: controlled agents (mobile robots) and uncontrolled ones
    (users and obstacles). The information transferred between the controlled
    agents and the intelligent space is limited to the control commands sent to
    the robots and the measures of the odometers received from the robots. The
    proposed solution allows the localization of mobile agents, even if they are
    not robots; however, we have focused on the controlled agents. The proposal
    does not require prior knowledge or invasive landmarks on board the robots.
    It starts from the segmentation of different agents in motion that allows obtaining the boundaries of all robots and an estimation of all 3D points that
    define those boundaries. Then, the identification of the robots is obtained
    by comparing the components of the linear velocity estimated by the motion segmentation algorithm and received from the odometers. In order to
    track the robots, an eXtended Particle Filter with Classification Process is
    employed. Several experimental tests have been carried out and the obtained
    results validate the proposal.