(A) VISION FOR 2050 - The Road Towards Image Understanding for a Human-Robot Soccer Match

Udo Frese, Tim Laue

Abstract

We believe it is possible to create the visual subsystem needed for the RoboCup 2050 challenge – a soccer match between humans and robots – within the next decade. In this position paper, we argue, that the basic techniques are available, but the main challenge will be to achieve the necessary robustness. We propose to address this challenge through the use of probabilistically modeled context, so for instance a visually indistinct circle is accepted as the ball, if it fits well with the ball’s motion model and vice versa. Our vision is accompanied by a sequence of (partially already conducted) experiments for its verification. In these experiments, a human soccer player carries a helmet with a camera and an inertial sensor and the vision system has to extract all information from that data, a humanoid robot would need to take the human’s place.

References

  1. Beetz, M., Gedikli, S., Bandouch, J., Kirchlechner, B., v. Hoyningen-Huene, N., and Perzylo, A. (2007). Visually tracking football games based on tv broadcasts. IJCAI 2007, Proceedings of the 20th International Joint Conference on Artificial Intelligence, Hyderabad, India.
  2. Beetz, M., v. Hoyningen-Huene, N., Bandouch, J., Kirchlechner, B., Gedikli, S., and Maldonado, A. (2006). Camerabased observation of football games for analyzing multiagent activities. In International Conference on Autonomous Agents.
  3. Binnig, G. (2004). Cellenger automated high content analysis of biomedical imagery.
  4. Birbach, O. (2008). Accuracy analysis of camera-inertial sensor based ball trajectory prediction. Master's thesis, Universität Bremen, Mathematik und Informatik.
  5. Burkhard, H.-D., Duhaut, D., Fujita, M., Lima, P., Murphy, R., and Rojas, R. (2002). The Road to RoboCup 2050. IEEE Robotics and Automation Magazine, 9(2):31-38.
  6. Davies, E. R. (2004). Machine Vision. Theory, Algorithms, Practicalities. Morgan Kauffmann.
  7. Frese, U., Bäuml, B., Haidacher, S., Schreiber, G., Schaefer, I., Hähnle, M., and Hirzinger, G. (2001). Off-theshelf vision for a robotic ball catcher. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Maui, pages 1623 - 1629.
  8. Guru, D. and Shekar, B. (2004). A simple and robust line detection algorithm based on small eigenvalue analysis. Pattern Recognition Letters, 25(1):1-13.
  9. Haddadin, S., Laue, T., Frese, U., and Hirzinger, G. (2007). Foul 2050: Thoughts on Physical Interaction in HumanRobot Soccer. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.
  10. Honda Worldwide Site (2007). Honda World Wide - Asimo. http://world.honda.com/ASIMO/.
  11. Kitano, H. and Asada, M. (1998). RoboCup Humanoid Challenge: That's One Small Step for A Robot, One Giant Leap for Mankind. In International Conference on Intelligent Robots and Systems, Victoria, pages 419-424.
  12. Kuffner, J. J., Kagami, S., Nishiwaki, K., Inaba, M., and Inoue, H. (2002). Dynamically-stable Motion Planning for Humanoid Robots. Auton. Robots, 12(1):105-118.
  13. Kurlbaum, J. (2007). Verfolgung von ballflugbahnen mit einem frei beweglichen kamera-inertialsensor. Master's thesis, Universität Bremen, Mathematik und Informatik.
  14. Leibe, B., Cornelis, N., Cornelis, K., and Gool, L. V. (2007). Dynamic 3D Scene Analysis from a Moving Vehicle. In IEEE Conference on Computer Vision and Pattern Recognition.
  15. Lowe, D. (2004). Distinctive image features from scaleinvariant keypoints. International Journal of Computer Vision, 60(2):91 - 110.
  16. Price, K. (2008). The annotated computer vision bibliography. http://www.visionbib.com/.
  17. Ramanan, D. and Forsyth, D. (2003). Finding and tracking people from the bottom up. In IEEE Conference on Computer Vision and Pattern Recognition.
  18. RoboCup Federation (2008). http://www.robocup.org.
  19. Röfer, T. et al. (2005). GermanTeam RoboCup 2005. http://www.germanteam.org/GT2005.pdf.
  20. Stone, P., Sutton, R. S., and Kuhlmann, G. (2005). Reinforcement Learning for RoboCup-Soccer Keepaway. Adaptive Behavior, 13(3):165-188.
  21. Ullman, S. (1995). Sequence seeking and counter streams: A computational model for bidirectional information flow in the visual cortex. Cerebral Cortex, 5(1):1-11.
  22. Xsens Technologies B.V. (2007). Moven, Inertial Motion Capture, Product Leaflet. XSens Technologies.
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Paper Citation


in Harvard Style

Frese U. and Laue T. (2008). (A) VISION FOR 2050 - The Road Towards Image Understanding for a Human-Robot Soccer Match . In Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-8111-31-9, pages 317-322. DOI: 10.5220/0001506803170322


in Bibtex Style

@conference{icinco08,
author={Udo Frese and Tim Laue},
title={(A) VISION FOR 2050 - The Road Towards Image Understanding for a Human-Robot Soccer Match},
booktitle={Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2008},
pages={317-322},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001506803170322},
isbn={978-989-8111-31-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - (A) VISION FOR 2050 - The Road Towards Image Understanding for a Human-Robot Soccer Match
SN - 978-989-8111-31-9
AU - Frese U.
AU - Laue T.
PY - 2008
SP - 317
EP - 322
DO - 10.5220/0001506803170322