Skip to main content

Recognition and Representation of Robot Skills in Real Time: A Theoretical Analysis

  • Conference paper
  • 6277 Accesses

Part of the Lecture Notes in Computer Science book series (LNAI,volume 8239)

Abstract

Sharing reusable knowledge among robots has the potential to sustainably develop robot skills. The bottlenecks to sharing robot skills across a network are how to recognise and represent reusable robot skills in real-time and how to define reusable robot skills in a way that facilitates the recognition and representation challenge. In this paper, we first analyse the considerations to categorise reusable robot skills that manipulate objects derived from R.C. Schank’s script representation of human basic motion, and define three types of reusable robot skills on the basis of the analysis. Then, we propose a method with potential to identify robot skills in real-time. We present a theoretical process of skills recognition during task performance. Finally, we characterise reusable robot skill based on new definitions and explain how the new proposed representation of robot skill is potentially advantageous over current state-of-the-art work.

Keywords

  • Human-Robot Interaction
  • Robot-Robot Interaction
  • Social networking
  • Internet of Things
  • Robots

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-02675-6_13
  • Chapter length: 11 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   84.99
Price excludes VAT (USA)
  • ISBN: 978-3-319-02675-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   109.99
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Castro-González, Á., Malfaz, M., Salichs, M.A.: Learning the Selection of Actions for an Autonomous Social Robot by Reinforcement Learning Based on Motivations. International Journal of Social Robotics 3(4), 427–441 (2011)

    CrossRef  Google Scholar 

  2. Weng, J., McClelland, J., Pentland, A., Sporns, O., Stockman, I., Sur, M., Thelen, E.: Autonomous Mental Development by Robots and Animals. Science 291, 599–600 (2001)

    CrossRef  Google Scholar 

  3. Tenorth, M., Perzylo, A., Lafrenz, R., Beetz, M.: The RoboEarth Language: Representing and Exchanging Knowledge about Action, Objects and Environments. In: ICRA, pp. 1284–1289 (2012)

    Google Scholar 

  4. Cohen, P.R., Chang, Y.-H., Morrison, C.T.: Learning and Transferring Action Schemas. In: IJCAI, pp. 720–725 (2007)

    Google Scholar 

  5. Konidaris, G.D., Kuindersma, S.R., Grupen, R.A., Barto, A.G.: Robot Learning from Demonstration by Constructing Skill Trees. International Journal of Robotics Research 31(3), 360–375 (2012)

    CrossRef  Google Scholar 

  6. Mugan, J., Kuipers, B.: Autonomous Learning of High-Level States and Actions in Continuous Environments. IEEE Transactions on Autonomous Mental Development 4(1), 70–86 (2012)

    CrossRef  Google Scholar 

  7. Zhang, Y.L., Weng, J.Y.: Task Transfer by a Developmental Robot. IEEE Transactions on Evolutionary Computation 11(2), 226–248 (2007)

    CrossRef  Google Scholar 

  8. Piaget, J.: The Construction of Reality in the Child, New York (1954)

    Google Scholar 

  9. Schank, R., Abelson, R.P.: Scripts, Plans, Goals and Understanding: An Inquiry into Human Knowledge Structures. Erlbaum (1977)

    Google Scholar 

  10. Wiering, M., Otterlo, M.V.: Transfer in Reinforcement Learning Reinforcement Learning State-of-the-Art., ch. 5. Springer, Berlin (2012)

    Google Scholar 

  11. Konidaris, G.D., Kuindersma, S.R., Grupen, R.A., Barto, A.G.: Autonomous Skill Acquisition on a Mobile Manipulator. In: AAAI, pp. 1468–1473 (2011)

    Google Scholar 

  12. Sutton, R.S., Precup, D., Singh, S.: Between MDPs and semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning. Artificial Intelligence 112(1-2), 181–211 (1999)

    MathSciNet  CrossRef  MATH  Google Scholar 

  13. Nicolescu, M.N., Matari, M.J.: A Hierarchical Architecture for Behavior-Based Robots. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multi-agent Systems: Part 1. ACM, Bologna (2002)

    Google Scholar 

  14. Allen, J.F.: Maintaining Knowledge about Temporal Intervals. Communications of the ACM 26(11), 832–843 (1983)

    CrossRef  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wang, W., Johnston, B., Williams, MA. (2013). Recognition and Representation of Robot Skills in Real Time: A Theoretical Analysis. In: Herrmann, G., Pearson, M.J., Lenz, A., Bremner, P., Spiers, A., Leonards, U. (eds) Social Robotics. ICSR 2013. Lecture Notes in Computer Science(), vol 8239. Springer, Cham. https://doi.org/10.1007/978-3-319-02675-6_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-02675-6_13

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02674-9

  • Online ISBN: 978-3-319-02675-6

  • eBook Packages: Computer ScienceComputer Science (R0)