Avoiding obstacles is one of the main tasks in robotic navigation. In this paper, robot navigation using monocular vision is presented. Therefore, an accuracy in the segmentation of obstacles is necessary to avoid collisions by estimating the Time-to-Contact. Our proposal in this research process is based on using YOLO so that through a training process, the robot identifies which regions of the image are potentially obstacles. The experimentation was performed in a real environment, with low daylight and without controlling lighting parameters. The first results of this approach are satisfactory although this project will continue with the learning of other obstacles.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Towards Learning Obstacles to Avoid Collisions in Autonomous Robot Navigation




    Erscheinungsdatum :

    01.11.2019


    Format / Umfang :

    1083929 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    An Analytical Approach to Avoid Obstacles in Mobile Robot Navigation

    Brandao, Alexandre Santos / Sarcinelli Filho, Mário / Carelli Albarracin, Ricardo Oscar | BASE

    Freier Zugriff

    Redundant Robot Can Avoid Obstacles

    Homayoun, Seraji / Colbaugh, Richard / Glass, Kristin | NTRS | 1991


    Experimental study on autonomous mobile robot acquiring optimal action to avoid moving obstacles

    Aoki, T. / Oka, T. / Hayakawa, S. et al. | British Library Online Contents | 1997


    DETERMINING DRIVING PATHS FOR AUTONOMOUS DRIVING THAT AVOID MOVING OBSTACLES

    XU KECHENG / MIAO JINGHAO | Europäisches Patentamt | 2019

    Freier Zugriff

    Robot Avoids Collisions With Obstacles

    Cheung, Edward / Rosinski, Doug / Wegerif, Dan | NTRS | 1993