Advertisement

Toward Data Driven Development in RoboCup

  • Heinrich MellmannEmail author
  • Benjamin Schlotter
  • Philipp Strobel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11531)

Abstract

Conducting games in RoboCup incurs high cost in terms of effort, time, and money. The scientific outcome, however, is quite limited and often not very conclusive. Especially, analyzing and drawing conclusions about the performance of complex processes like decision making of an individual robot or the behavior on the team level poses a considerable challenge. Collecting more data during the competition games will help to analyze the performance of algorithms, identify errors and areas for improvement, and make more significant statements regarding the performance of the robots. In this work we investigate the possibilities for collection of the large scale RoboCup data and its analysis. We present a system for automatic recording of synchronized videos of RoboCup games and an application for exploration and annotation of large sets of RoboCup-related data. We also present data sets collected during the competitions in 2018 and an algorithm for visual detection and tracking of robots in the RoboCup videos. A first empirical evaluation shows promising results and demonstrates how such data can be integrated and used to validate robot’s behavior.

Keywords

Data driven development Robot detection Visual robot tracking Camera localization 

Notes

Acknowledgements

This work was supported by the RCF grants in 2017 and 2018.

References

  1. 1.
    B-Human: GameController 2018 - RoboCup Edition (2018). https://spl.robocup.org/downloads/. Accessed 22 Apr 2019
  2. 2.
    Berlin United: Tools for Data Driven Research and Development in RoboCup (2019). http://www.robocup.tools. Accessed 22 Apr 2019
  3. 3.
    Hofmann, M., Moos, A., Rensen, F., Schwarz, I., Urbann, O.: Playing robot soccer outdoor. In: The 11th Workshop on Humanoid Soccer Robots at 16th IEEE-RAS International Conference on Humanoid Robots (2016). http://d-fence.sytes.net/research/files/Playing%20Soccer%20Outdoors%20with%20Humanoid%20Robots.pdf
  4. 4.
    Huang, Z., Wang, J.: DC-SPP-YOLO: dense connection and spatial pyramid pooling based YOLO for object detection. CoRR (2019). arXiv:1903.08589
  5. 5.
    Le, H.M., Carr, P., Yue, Y., Lucey, P.: Data-driven ghosting using deep imitation learning (2017)Google Scholar
  6. 6.
    Mellmann, H., Schlotter, B.: Advances on simulation based selection of actions for a humanoid soccer-robot. In: Proceedings of the 12th Workshop on Humanoid Soccer Robots, 17th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Madrid, Spain (2017)Google Scholar
  7. 7.
    Mellmann, H., Schlotter, B., Blum, C.: Simulation based selection of actions for a humanoid soccer-robot. In: Behnke, S., Sheh, R., Sarıel, S., Lee, D.D. (eds.) RoboCup 2016. LNCS (LNAI), vol. 9776, pp. 193–205. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-68792-6_16CrossRefGoogle Scholar
  8. 8.
    Röfer, T., Laue, T., Hasselbring, A., Richter-Klug, J., Röhrig, E.: B-Human 2017 – team tactics and robot skills in the standard platform league. In: Akiyama, H., Obst, O., Sammut, C., Tonidandel, F. (eds.) RoboCup 2017. LNCS (LNAI), vol. 11175, pp. 461–472. Springer, Cham (2018).  https://doi.org/10.1007/978-3-030-00308-1_38CrossRefGoogle Scholar
  9. 9.
    Zhu, D., Veloso, M.: Virtually adapted reality and algorithm visualization for autonomous robots. In: Behnke, S., Sheh, R., Sarıel, S., Lee, D.D. (eds.) RoboCup 2016. LNCS (LNAI), vol. 9776, pp. 452–464. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-68792-6_38CrossRefGoogle Scholar
  10. 10.
    Zhu, D., Veloso, M.: Event-based automated refereeing for robot soccer. Auton. Robots 41(7), 1463–1485 (2017).  https://doi.org/10.1007/s10514-016-9607-8CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Heinrich Mellmann
    • 1
    Email author
  • Benjamin Schlotter
    • 1
  • Philipp Strobel
    • 1
  1. 1.Adaptive Systems GroupHumboldt-Universität zu BerlinBerlinGermany

Personalised recommendations