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Learning and Composing Primitive Skills for Dual-Arm Manipulation

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Towards Autonomous Robotic Systems (TAROS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11649))

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Abstract

In an attempt to confer robots with complex manipulation capabilities, dual-arm anthropomorphic systems have become an important research topic in the robotics community. Most approaches in the literature rely upon a great understanding of the dynamics underlying the system’s behaviour and yet offer limited autonomous generalisation capabilities. To address these limitations, this work proposes a modelisation for dual-arm manipulators based on dynamic movement primitives laying in two orthogonal spaces. The modularity and learning capabilities of this model are leveraged to formulate a novel end-to-end learning-based framework which (i) learns a library of primitive skills from human demonstrations, and (ii) composes such knowledge simultaneously and sequentially to confront novel scenarios. The feasibility of the proposal is evaluated by teaching the iCub humanoid the basic skills to succeed on simulated dual-arm pick-and-place tasks. The results suggest the learning and generalisation capabilities of the proposed framework extend to autonomously conduct undemonstrated dual-arm manipulation tasks.

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Acknowledgments

This work has been partially supported by ORCA Hub EPSRC (EP/R026173/1) and consortium partners.

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Authors and Affiliations

  1. Institute of Perception, Action and Behaviour, University of Edinburgh, Edinburgh, UK

    Èric Pairet, Paola Ardón & Michael Mistry

  2. Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK

    Èric Pairet, Paola Ardón & Yvan Petillot

Authors
  1. Èric Pairet
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  2. Paola Ardón
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  3. Michael Mistry
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  4. Yvan Petillot
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Corresponding author

Correspondence to Èric Pairet .

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Editors and Affiliations

  1. Queen Mary University of London, London, UK

    Kaspar Althoefer

  2. Queen Mary University of London, London, UK

    Jelizaveta Konstantinova

  3. Queen Mary University of London, London, UK

    Ketao Zhang

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Pairet, È., Ardón, P., Mistry, M., Petillot, Y. (2019). Learning and Composing Primitive Skills for Dual-Arm Manipulation. In: Althoefer, K., Konstantinova, J., Zhang, K. (eds) Towards Autonomous Robotic Systems. TAROS 2019. Lecture Notes in Computer Science(), vol 11649. Springer, Cham. https://doi.org/10.1007/978-3-030-23807-0_6

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  • DOI: https://doi.org/10.1007/978-3-030-23807-0_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-23806-3

  • Online ISBN: 978-3-030-23807-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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