Advertisement

Lightweight Management – Taming the RoboCup Development Process

  • Tijn van der Zant
  • Paul G. Plöger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4020)

Abstract

RoboCup projects can face a lack of progress and continuity. The teams change continuously and knowledge gets lost. The approach used in previous years is no longer valid due to rule changes and specialists leaving the team leave black boxes that no-one understands. This article presents the application of a recent software development technique called eXtreme Programming to the realm of RoboCup. Many common problems typical for teams of students seem to be solvable with this technique. It also gradually spreads out in professional software production companies. Students mastering it are of high use for their further career after having left the university. The strategy is being tested on a real RoboCup Mid-Size and an Aibo league project and produces very promising results. The approach makes it possible to modularize scientific knowledge into software that can be re-used. Both the scientist/expert, who has the knowledge, and the software development team benefit from this approach without much overhead on the project.

Keywords

Stable Branch Implementation Decision Pair Programming Software Development Team eXtreme Program 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
  2. 2.
  3. 3.
  4. 4.
    Special report: Software goes extremeGoogle Scholar
  5. 5.
    Bredenfeld, A., Christaller, T., Jaeger, H., Kobialka, H.-U., Schöll, P.: Robot behavior design using dual dynamics. Technical report, GMD Report (2000)Google Scholar
  6. 6.
    Bredenfeld, A., Becanovic, V., Christaller, Th., Godler, I., Indiveri, G., Ishii, K., Ji, J., Kobialka, H.-U., Mayer, N., Miyamoto, H., Nassiraei, A.F.F., Plöger, P.-G., Schöll, P., Shimizu, M.: Ais-musashi team description paperGoogle Scholar
  7. 7.
    Beck, K.: Extreme Programming Explained. Addision Wessley, Reading (2000)Google Scholar
  8. 8.
    Coradeschi, S., Malec, J.: How to make a challenging AI course enjoyable using the roboCup soccer simulation system. In: Asada, M., Kitano, H. (eds.) RoboCup 1998. LNCS, vol. 1604, pp. 120–124. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  9. 9.
    Fowler, M.: Refactoring: Improving the Design of Existing Code. Addision Wessley, Reading (1999)Google Scholar
  10. 10.
    Mandl, R., Sick, B.: Messen, Steuern und Regeln mit ICONNECT. Vieweg (2003)Google Scholar
  11. 11.
    McCurdy, H.E.: Faster, Better, Cheaper: Low-Cost Innovation in the U.S. Space Program. Johns Hopkins Univ. Press (2001)Google Scholar
  12. 12.
    Stone, P.: Robocup as an introduction to cs researchGoogle Scholar
  13. 13.
    Stone, P.: Multiagent competitions and research: Lessons from robocup and tac (2002)Google Scholar
  14. 14.
    Werger, B.: Ayllu: Distributed port-arbitrated behavior-based control (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Tijn van der Zant
    • 1
  • Paul G. Plöger
    • 1
  1. 1.FhG Institute of Autonomous Intelligent SystemsSt. AugustinGermany

Personalised recommendations