Event-Oriented Incremental Component Construction

Chapter

Abstract

Understanding the prerequisites of an effective and intuitive human-robot teaching situation requires an experimental approach to human-robot interaction that includes cross-platform variation as well as fast inter- and intra-component change. Although re-use has been significantly increased over the last years, the complexity faced in robotic systems is still leading to frequent lock-in rather than change. Today, most approaches address the complexity in a robot’s software system by decomposition into components, coupled through middleware. However, the integration of core algorithms, utility libraries and middleware into a component is itself becoming more complex and, due to the embedded external references, can create lock-in.

To reduce both lock-in and complexity, we have developed a component construction framework based on modelling the various building blocks as directed, typed graphs. These graphs may be (re-)assembled efficiently into components. The approach has been tested on diverse applications, from device drivers to robot behavior generation and we report the experience gained. Furthermore, we propose a decomposition strategy for converting legacy components into such graphs on a coarse level. The strategy is based on principles from event-based systems to optimize the re-usability of the resulting sub-graphs.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Barrett, D.J., Clarke, L.A., Tarr, P.L., Wise, A.E.: A framework for event-based software integration. ACM Trans. Softw. Eng. Methodol 5(4), 378–421 (1996)CrossRefGoogle Scholar
  2. 2.
    Bäuml, B., Hirzinger, G.: When hard realtime matters: Software for complex mechatronic systems. Robotics and Autonomous Systems 56(1), 5–13 (2008)CrossRefGoogle Scholar
  3. 3.
    Boehm, B.W.: Software engineering economics. IEEE Transactions on Software Engineering SE-10(1), 4–21 (1984)CrossRefGoogle Scholar
  4. 4.
    Hackel, M., Schwope, S., Fritsch, J., Wrede, B., Sagerer, G.: A humanoid robot platform suitable for studying embodied interaction. In: Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 56–61. IEEE (2005)Google Scholar
  5. 5.
    Johnston, W.M., Hanna, J.R.P., Millar, R.J.: Advances in dataflow programming languages. ACM Comput. Surv. 36(1), 1–34 (2004)CrossRefGoogle Scholar
  6. 6.
    Kahn, G., MacQueen, D.: Coroutines and networks of parallel processes. In: Gilchrist, B. (ed.) Information Processing 1977: Proceedings of IFIP Congress, pp. 993–998. North-Holland Publishing Co., Amsterdam (1977)Google Scholar
  7. 7.
    Lee, E.A., Messerschmitt, D.G.: Synchronous data flow. Proceedings of the IEEE 75(9) (1987)Google Scholar
  8. 8.
    Lütkebohle, I.: Coordination and composition patterns in the “curious robot” scenario. PhD thesis, Bielefeld University (2010)Google Scholar
  9. 9.
    Lütkebohle, I., Peltason, J., Schillingmann, L., Elbrechter, C., Wrede, B., Wachsmuth, S., Haschke, R.: The Curious Robot - Structuring Interactive Robot Learning. In: International Conference on Robotics and Automation, Robotics and Automation Society, IEEE (2009)Google Scholar
  10. 10.
    Lütkebohle, I., Schäfer, J., Wrede, S.: Facilitating re-use by design: A filtering, transformation, and selection architecture for robotic software systems. In: Software Development and Integration in Robotics (2009)Google Scholar
  11. 11.
    Lütkebohle, I., Hegel, F., Schulz, S., Hackel, M., Wrede, B., Wachsmuth, S., Sagerer, G.: The Bielefeld Anthropomorphic Robot Head “Flobi”. In: 2010 IEEE International Conference on Robotics and Automation, IEEE (2010)Google Scholar
  12. 12.
    Schmidt, D.C.: Guest editor’s introduction: Model-driven engineering. Computer 39(02), 25–31 (2006)CrossRefGoogle Scholar
  13. 13.
    Shaw, M., Garlan, D.: Software Architecture: Perspectives on an Emerging Discipline. Prentice-Hall (1996)Google Scholar
  14. 14.
    UML2.0, Unified Modeling Language: Superstructure version 2.0. Object Management Group (OMG), Inc. (2005)Google Scholar
  15. 15.
    VISCA, Command list – Intelligent Communication Color Video Camera EVI-D30/D31. Sony Corporation, v1.21, english edn. (1999)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Cognitive Interaction Technology Excellence ClusterBielefeld UniversityBielefeldGermany

Personalised recommendations