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Design of Timeline-Based Planning Systems for Safe Human-Robot Collaboration

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Knowledge Engineering Tools and Techniques for AI Planning

Abstract

During the last decade, industrial collaborative robots have entered assembly cells supporting human workers in repetitive and physical demanding operations. Such human-robot collaboration (HRC) scenarios entail many open issues. The deployment of highly flexible and adaptive plan-based controllers is capable of preserving productivity while enforcing human safety is then a crucial requirement. The deployment of plan-based solutions entails knowledge engineers and roboticists interactions in order to design well-suited models of robotic cells considering both operational and safety requirements. So, the ability of supporting knowledge engineering for integrating high level and low level control (also from non-specialist users) can facilitate deployment of effective and safe solutions in different industrial settings. In this chapter, we will provide an overview of some recent results concerning the development of a task planning and execution technology and its integration with a state of the art Knowledge Engineering environment to deploy safe and effective solutions in realistic manufacturing HRC scenarios. We will briefly present and discuss a HRC use case to demonstrate the effectiveness of such integration discussing its advantages.

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Notes

  1. 1.

    https://github.com/pstlab/PLATINUm.

  2. 2.

    https://github.com/ugilio/keen. The reader interested in knowing how to use KEEN can find a detailed description at https://ugilio.github.io/keen/userguide.

  3. 3.

    http://www.fourbythree.eu.

  4. 4.

    http://www.ros.org/.

  5. 5.

    https://sharework-project.eu/.

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Acknowledgements

Amedeo Cesta, Andrea Orlandini, and Alessandro Umbrico wish to acknowledge the support by the European Commission and the ShareWork project (H2020—Factories of the Future—G.A. nr. 820807).

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Authors and Affiliations

  1. Institute of Cognitive Science and Technology, CNR – National Research Council of Italy, Rome, Italy

    Andrea Orlandini, Alessandro Umbrico & Amedeo Cesta

  2. Department of Engineering, University “Roma TRE”, Rome (RM), Italy

    Marta Cialdea Mayer

Authors
  1. Andrea Orlandini
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  2. Marta Cialdea Mayer
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  3. Alessandro Umbrico
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  4. Amedeo Cesta
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Corresponding author

Correspondence to Andrea Orlandini .

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Editors and Affiliations

  1. Department of Computer Science, University of Huddersfield, Huddersfield, UK

    Mauro Vallati

  2. Department of Computer Science, University of Huddersfield, Huddersfield, UK

    Diane Kitchin

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Orlandini, A., Cialdea Mayer, M., Umbrico, A., Cesta, A. (2020). Design of Timeline-Based Planning Systems for Safe Human-Robot Collaboration. In: Vallati, M., Kitchin, D. (eds) Knowledge Engineering Tools and Techniques for AI Planning. Springer, Cham. https://doi.org/10.1007/978-3-030-38561-3_12

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  • DOI: https://doi.org/10.1007/978-3-030-38561-3_12

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  • Online ISBN: 978-3-030-38561-3

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