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Conclusions

  • Adrià ColoméEmail author
  • Carme Torras
Chapter
  • 451 Downloads
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 134)

Abstract

This book has focused on a complete framework for learning motion tasks in mostly unmodelled environments with robotic arms. We devised strategies to compliantly learn such tasks both in the joint space and in the robot’s operational—or Cartesian- space, as well as to obtain coordination schemes for the robot’s DoF for a certain task.

References

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    Jevtic, A., Colomé, A., Alenya, G., Torras, C.: Robot motion adaptation through user intervention and reinforcement learning. Pattern Recognit. Lett. 105, 67–75 (2018)CrossRefGoogle Scholar
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    Rozo, L., Silvério, J., Calinon, S., Caldwell, D.G.: Learning controllers for reactive and proactive behaviors in human-robot collaboration. Front. Robot. AI 3(30), 1–11 (2016)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institut de Robòtica i Informàtica Industrial (UPC-CSIC)BarcelonaSpain

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