© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. ; In this paper, a quick and efficient method is presented for grasping unknown objects in clutter. The grasping method relies on real-time superquadric (SQ) representation of partial view objects and incomplete object modelling, well suited for unknown symmetric objects in cluttered scenarios which is followed by optimized antipodal grasping. The incomplete object models are processed through a mirroring algorithm that assumes symmetry to first create an approximate complete model and then fit for SQ representation. The grasping algorithm is designed for maximum force balance and stability, taking advantage of the quick retrieval of dimension and surface curvature information from the SQ parameters. The pose of the SQs with respect to the direction of gravity is calculated and used together with the parameters of the SQs and specification of the gripper, to select the best direction of approach and contact points. The SQ fitting method has been tested on custom datasets containing objects in isolation as well as in clutter. The grasping algorithm is evaluated on a PR2 robot and real time results are presented. Initial results indicate that though the method is based on simplistic shape information, it outperforms other learning based grasping algorithms that also work in clutter in terms of time-efficiency and accuracy. ; Peer Reviewed ; Postprint (author's final draft)


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Grasping unknown objects in clutter by superquadric representation



    Erscheinungsdatum :

    2018-01-01



    Medientyp :

    Sonstige


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




    Superquadric representation of automotive parts applying part decomposition

    Zhang, Y. / Koschan, A. / Abidi, M. A. | British Library Online Contents | 2004


    Task Understanding for Grasping Unknown Objects

    Kaneko, M. | British Library Online Contents | 1993


    Grasping Unknown Objects Using Convolutional Neural Networks

    Krishna Prasad, Pranav / Stähle, Benjamin / Chernov, Igor et al. | BASE | 2020

    Freier Zugriff

    Grasping Unknown Objects Using Convolutional Neural Networks

    Krishna Prasad, Pranav (M.Sc.) | BASE | 2020

    Freier Zugriff

    Framework for Autonomous Underwater Grasping of Unknown Objects

    Peñalver Monfort, Antonio | BASE | 2019

    Freier Zugriff