In random bin picking, grasps on a workpiece are often defined manually, which requires extensive time and expert knowledge. In this paper, we propose a method that generates and prioritizes grasps for vacuum and magnetic grippers by analyzing the CAD model of a workpiece and gripper geometry. Using projections of these models, heatmaps such as the overlap of gripper and workpiece, the center of gravity, and the surface smoothness are generated. To get a combined heatmap, which estimates the probability for a successful grip, all individual heatmaps are fused by means of a weighted sum. Grid-based sampling generates prioritized grasps and suggests the most suitable gripper automatically. This approach increases the autonomy of bin picking significantly.


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    Titel :

    Automatic Grasp Generation for Vacuum Grippers for Random Bin Picking


    Weitere Titelangaben:

    ARENA2036


    Beteiligte:
    Weißgraeber, Philipp (Herausgeber:in) / Heieck, Frieder (Herausgeber:in) / Ackermann, Clemens (Herausgeber:in) / Khalid, Muhammad Usman (Autor:in) / Spenrath, Felix (Autor:in) / Mönnig, Manuel (Autor:in) / Moosmann, Marius (Autor:in) / Bormann, Richard (Autor:in) / Kunz, Holger (Autor:in) / Huber, Marco F. (Autor:in)


    Erscheinungsdatum :

    2021-06-02


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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