Learning Manipulation by Sequencing Motor Primitives with a Two-Armed Robot

  • Rudolf Lioutikov
  • Oliver Kroemer
  • Guilherme Maeda
  • Jan Peters
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 302)


Learning to perform complex tasks out of a sequence of simple small demonstrations is a key ability for more flexible robots. In this paper, we present a system that allows for the acquisition of such task executions based on dynamical movement primitives (DMPs). DMPs are a successful approach to encode and generalize robot movements. However, current applications involving DMPs mainly explore movements that, although challenging in terms of dexterity and dimensionality, usually comprise a single continuous movement. This article describes the implementation of a novel system that allows sequencing of simple demonstrations, each one encoded by its own DMP, to achieve a bimanual manipulation task that is too complex to be demonstrated with a single teaching action. As the experimental results show, the resulting system can successfully accomplish a sequenced task of grasping, placing and cutting a vegetable using a setup of a bimanual robot.



The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7-ICT-2013-10) under grant agreement 610878 (3rdHand).


  1. 1.
    Kober, J., Mohler, B., Peters, J.: Learning perceptual coupling for motor primitives. In: Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on, IEEE (2008) 834–839Google Scholar
  2. 2.
    Mülling, K., Kober, J., Kroemer, O., Peters, J.: Learning to select and generalize striking movements in robot table tennis. The International Journal of Robotics Research 32(3) (2013) 263–279Google Scholar
  3. 3.
    Schaal, S.: Dynamic movement primitives-a framework for motor control in humans and humanoid robotics. In: Adaptive Motion of Animals and Machines. Springer (2006) 261–280Google Scholar
  4. 4.
    Nakanishi, J., Morimoto, J., Endo, G., Cheng, G., Schaal, S., Kawato, M.: Learning from demonstration and adaptation of biped locomotion. Robotics and Autonomous Systems 47(2) (2004) 79–91Google Scholar
  5. 5.
    Pastor, P., Hoffmann, H., Asfour, T., Schaal, S.: Learning and generalization of motor skills by learning from demonstration. In: Proceedings of the 2009 IEEE International Conference on Robotics and Automation. (2009) 763–768Google Scholar
  6. 6.
    Kober, J., Mulling, K., Kromer, O., Lampert, C., Scholkopf, B., Peters, J.: Movement templates for learning of hitting and batting. In: Proceedings of the 2010 IEEE International Conference on Robotics and Automation, IEEE (2010) 853–858Google Scholar
  7. 7.
    Kulvicius, T., Ning, K., Tamosiunaite, M., Worgotter, F.: Joining movement sequences: Modified dynamic movement primitives for robotics applications exemplified on handwriting. Robotics, IEEE Transactions on 28(1) (2012) 145–157Google Scholar
  8. 8.
    Pastor, P., Kalakrishnan, M., Chitta, S., Theodorou, E., Schaal, S.: Skill learning and task outcome prediction for manipulation. In: Robotics and Automation (ICRA), 2011 IEEE International Conference on, IEEE (2011) 3828–3834Google Scholar
  9. 9.
    Matsubara, T., Hyon, S.H., Morimoto, J.: Learning parametric dynamic movement primitives from multiple demonstrations. Neural Networks 24(5) (2011) 493–500Google Scholar
  10. 10.
    Gams, A., Nemec, B., Zlajpah, L., Wachter, M., Ijspeert, A., Asfour, T., Ude, A.: Modulation of motor primitives using force feedback: Interaction with the environment and bimanual tasks. In: Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on, IEEE (2013) 5629–5635.Google Scholar
  11. 11.
    Ijspeert, A.J., Nakanishi, J., Hoffmann, H., Pastor, P., Schaal, S.: Dynamical movement primitives: learning attractor models for motor behaviors. Neural computation 25(2) (2013) 328–373Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Rudolf Lioutikov
    • 1
  • Oliver Kroemer
    • 1
  • Guilherme Maeda
    • 1
  • Jan Peters
    • 1
  1. 1.Technische Universitaet DarmstadtIntelligent Autonomous Systems Hochschulstr. 10DarmstadtGermany

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