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Knowledge Engineering Tools and Techniques for AI Planning pp 231–248Cite as

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

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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