We present BulletArm, a novel benchmark and learning-environment for robotic manipulation. BulletArm is designed around two key principles: reproducibility and extensibility. We aim to encourage more direct comparisons between robotic learning methods by providing a set of standardized benchmark tasks in simulation alongside a collection of baseline algorithms. The framework consists of 31 different manipulation tasks of varying difficulty, ranging from simple reaching and picking tasks to more realistic tasks such as bin packing and pallet stacking. In addition to the provided tasks, BulletArm has been built to facilitate easy expansion and provides a suite of tools to assist users when adding new tasks to the framework. Moreover, we introduce a set of five benchmarks and evaluate them using a series of state-of-the-art baseline algorithms. By including these algorithms as part of our framework, we hope to encourage users to benchmark their work on any new tasks against these baselines.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    BulletArm: An Open-Source Robotic Manipulation Benchmark and Learning Framework


    Weitere Titelangaben:

    Springer Proceedings in Advanced Robotics


    Beteiligte:
    Billard, Aude (Herausgeber:in) / Asfour, Tamim (Herausgeber:in) / Khatib, Oussama (Herausgeber:in) / Wang, Dian (Autor:in) / Kohler, Colin (Autor:in) / Zhu, Xupeng (Autor:in) / Jia, Mingxi (Autor:in) / Platt, Robert (Autor:in)

    Kongress:

    The International Symposium of Robotics Research ; 2022 ; Geneva, Switzerland September 25, 2022 - September 30, 2022


    Erschienen in:

    Robotics Research ; Kapitel : 23 ; 335-350


    Erscheinungsdatum :

    08.03.2023


    Format / Umfang :

    16 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    EEMBC stellt Open-Source-Benchmark CoreMark vor

    British Library Online Contents | 2009


    Learning physical intuition for robotic manipulation

    Groth, OM | BASE | 2022

    Freier Zugriff

    Modular robotic manipulation

    BRUEMMER DAVID J | Europäisches Patentamt | 2019

    Freier Zugriff

    Combining learning and structure for robotic manipulation

    Kloss, Alina / Eberhard Karls Universität Tübingen | TIBKAT | 2020

    Freier Zugriff