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Automatic Grasp Generation and Improvement for Industrial Bin-Picking

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Gearing Up and Accelerating Cross‐fertilization between Academic and Industrial Robotics Research in Europe:

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 94))

Abstract

This paper presents work on automatic grasp generation and grasp learning for reducing the manual setup time and increase grasp success rates within bin-picking applications. We propose an approach that is able to generate good grasps automatically using a dynamic grasp simulator, a newly developed robust grasp quality measure and post-processing methods. In addition we present an offline learning approach that is able to adjust grasp priorities based on prior performance. We show, on two real world platforms, that one can replace manual grasp selection by our automatic grasp selection process and achieve comparable results and that our learning approach can improve system performance significantly. Automatic bin-picking is an important industrial process that can lead to significant savings and potentially keep production in countries with high labour cost rather than outsourcing it. The presented work allows to minimize cycle time as well as setup cost, which are essential factors in automatic bin-picking. It therefore leads to a wider applicability of bin-picking in industry.

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Author information

Authors and Affiliations

  1. Cognitive and Applied Robotics Group, The Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, Campusvej 55, 5230, Odense, Denmark

    Dirk Kraft & Jimmy Alison Jørgensen

  2. Scape Technologies A/S, Kochsgade 31C, 5000, Odense C, Denmark

    Lars-Peter Ellekilde

Authors
  1. Dirk Kraft
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  2. Lars-Peter Ellekilde
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  3. Jimmy Alison Jørgensen
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Corresponding author

Correspondence to Dirk Kraft .

Editor information

Editors and Affiliations

  1. Department of Informatics VI, Technical University of Munich, Garching, Germany

    Florian Röhrbein

  2. Feup Campus, Inesc Porto, Porto, Portugal

    Germano Veiga

  3. Department of Information Engineering, Second University of Naples, Aversa, Italy

    Ciro Natale

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Kraft, D., Ellekilde, LP., Jørgensen, J.A. (2014). Automatic Grasp Generation and Improvement for Industrial Bin-Picking. In: Röhrbein, F., Veiga, G., Natale, C. (eds) Gearing Up and Accelerating Cross‐fertilization between Academic and Industrial Robotics Research in Europe:. Springer Tracts in Advanced Robotics, vol 94. Springer, Cham. https://doi.org/10.1007/978-3-319-03838-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-03838-4_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03837-7

  • Online ISBN: 978-3-319-03838-4

  • eBook Packages: EngineeringEngineering (R0)

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