Skip to main content
SpringerLink
Log in

Action control of soccer robots based on simulated human intelligence

  • Published:
International Journal of Automation and Computing Aims and scope Submit manuscript

Abstract

A multi-modal action control approach is proposed for an autonomous soccer robot when the bottom hardware is unchangeable. Different from existing methods, the proposed control approach defines actions with the principle of “perception-planning-action” inspired by human intelligence. Character extraction is used to divide the perception input into different modes. Different control modes are built by combining different control methods for the linear velocity and angular velocity. Based on production rules, the motion control is realized by connecting different perceptions to the corresponding control mode. Simulation and real experiments are conducted with the middle-sized robot Frontier-I, and the proposed method is compared with a proportional-integral-derivative (PID) control method to display its feasibility and performance. The results show that the multi-modal action control method can make robots react rapidly in a dynamic environment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. K. H. Low. Locomotion and depth control of robotic fish with modular undulating fins. International Journal of Automation and Computing, vol. 3, no. 4, pp. 348–357, 2006.

    Article  MathSciNet  Google Scholar 

  2. A. De Cabrol, T. Garcia, P. Bonnin, M. Chetto. A concept of dynamically reconfigurable real-time vision system for autonomous mobile robotics. International Journal of Automation and Computing, vol. 5, no. 2, pp. 174–184, 2008.

    Article  Google Scholar 

  3. S. Ma, N. Tadokoro, B. Li, K. Inoue. Analysis of creeping locomotion of a snake robot on a slope. In Proceedings of IEEE International Conference on Robotics and Automation, IEEE, Taiwan, pp. 2073–2078, 2003.

    Google Scholar 

  4. M. Friedmann, S. Petters, M. Risler, H. Sakamoto, D. Thomas, O. von Stryk. New autonomous, four-legged and humanoid robots for research and education. In Proceedings of Simulation, Modeling and Programming for Autonomous Robots, Springer, Venice, Italy, vol. 2, pp. 570–579, 2008.

    Google Scholar 

  5. H. Fujii, K. Yoshida. Action control method for mobile robot considering uncertainty of information. In Proceedings of IEEE International Conference on Intelligent Robots and Systems, IEEE, Alberta, Canada, pp. 3915–3920, 2005.

    Google Scholar 

  6. L. Wong. Fault tolerant behavior-based robots. Journal of Undergraduate Research, vol. 4, no. 1, pp. 13–19, 2005.

    Google Scholar 

  7. G. A. Kaminka, I. Frenkel. Flexible teamwork in behavior-based robots. In Proceedings of the 20th National Conference on Artificial Intelligence, American Association for Artificial Intelligence, USA, AAAI-05, pp. 108–113, 2005.

    Google Scholar 

  8. W. Chatlatanagulchai, C. Srinangyam, W. Siwakosit. Trajectory control of a two-link robot manipulator carrying uncertain payload using quantitative feedback theory. Journal of Research in Engineering and Technology, vol. 5, no. 1, pp. 45–71, 2008.

    Google Scholar 

  9. H. K. Gazit. Transforming High Level Tasks to Low Level Controllers, Ph. D. dissertation, University of Pennsylvania, USA, pp. 16–28, 2008.

    Google Scholar 

  10. N. Ohnishi, A. Imiya. Corridor navigation and obstacle avoidance using visual potential for mobile robot. In Proceedings of the 4th Canadian Conference on Computer and Robot Vision, IEEE, pp. 131–138, 2007.

  11. S. Mastellone, D. M. Stipanović, C. R. Graunke, K. A. Intlekofer, M. W. Spong. Formation control and collision avoidance for multi-agent non-holonomic systems: Theory and experiments. International Journal of Robotics Research, vol. 27, no. 1, pp. 107–126, 2008.

    Article  Google Scholar 

  12. R. Nakanishi, J. Bruce, K. Murakami, T. Naruse, M. Veloso. Cooperative 3-robot passing and shooting in the RoboCup small size league. In Proceedings of the RoboCup Symposium 2006, Lecture Notes in Computer Science, Springer, Berlin, Germany, vol. 4434, pp. 418–425, 2009.

    Google Scholar 

  13. G. Shao. Study on the Behavior, Behavior Selection and Evolution of Artificial Life Based on Sensor-motor Intelligent Schema, Ph.D. dissertation, Chongqing University, PRC, 2007. (in Chinese)

    Google Scholar 

  14. M. Sato, A. Kanda, K. Ishii. A switching controller system for a wheeled mobile robot. Journal of Bionic Engineering, vol. 4, no. 4, pp. 281–289, 2007.

    Article  Google Scholar 

  15. M. W. Han, P. Kopacek. Neural networks for the control of soccer robots. Computational Intelligence, Theory and Applications, Berlin, Germany: Springer, vol. 33, pp. 621–628, 2005.

    Chapter  Google Scholar 

  16. J. Jang, C. K. Ahn, S. Han, W. H. Kwon. Rapid control prototyping for robot soccer system using SIM tool. In Proceedings of International Joint Conference on SICE-ICASE, IEEE, Korea, pp. 3035–3039, 2006.

    Chapter  Google Scholar 

  17. N. Ouadah, L. Ourak, F. Boudjema. Car-like mobile robot oriented positioning by fuzzy controllers. International Journal of Advanced Robotic Systems, vol. 5, no. 3, pp. 249–256, 2008.

    Google Scholar 

  18. R. Brooks. A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation, vol. 2, no. 1, pp. 14–23, 1986.

    Google Scholar 

  19. Product Information Guide for Frontier-I Autonomous Mobile Robot. Shanghai Jiao Tong University, pp. 18–30, 2004.

  20. A. Coninx, A. Guillot, B. Girard. Adaptive motivation in a biomimetic action selection mechanism. In Proceedings of Conference on Neurosciences Computation, France, pp. 158–162, 2008.

  21. P. Guerrero, J. Ruiz-del-Solar, G. Díaz. Probabilistic decision making in robot soccer. Lecture Notes in Computer Science, RoboCup 2007: Robot Soccer World Cup XI, Springer, Berlin, Germany, vol. 5001, pp. 29–40, 2008.

    Chapter  Google Scholar 

  22. G. Shao, Y. Wen, F. Yu, Z. Li. Target localization for autonomous soccer robot based on vision perception. In Proceedings of the 3rd International Symposium on Intelligence Computation and Applications, Lecture Notes in Computer Science, Springer, Berlin, Germany, vol. 5370, pp. 831–840, 2008.

    Google Scholar 

  23. R. M. M. Vallim, T. S. P. C. Duque, D. E. Goldberg, A. C. P. L. F. Carvalho. The multi-label OCS with a genetic algorithm for rule discovery: Implementation and first results. In Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, ACM, Montreal, Québec, Canada, pp. 1323–1330, 2009.

    Chapter  Google Scholar 

  24. C. D. Wu, Y. Zhang, M. X. Li, Y. Yue. A rough set GA-based hybrid method for robot path planning. International Journal of Automation and Computing, vol. 3, no. 1, pp. 29–34, 2006.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Engineering, Jimei University, Xiamen, 361021, PRC

    Tie-Jun Li

  2. Institute of Command Automation, Chongqing Communication College, Chongqing, 400035, PRC

    Gui-Qiang Chen

  3. Department of Automation, Xiamen University, Xiamen, 361005, PRC

    Gui-Fang Shao

Authors
  1. Tie-Jun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gui-Qiang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gui-Fang Shao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gui-Fang Shao.

Additional information

This work was supported by National Natural Science Foundation of China (No. 60443004) and Science and Technology Project of CQ Education Committee (No.KJ080621).

Tie-Jun Li received the B. Sc. and M. Sc. degrees in automation from the Chongqing University, PRC in 2000 and 2005, respectively. In 2005, he was a faculty member at Chongqing Jinmei Communication Co., Ltd., PRC. He is currently an engineer at Jimei University, PRC.

His research interests include robotics, communication systems, and electromagnetic compatibility.

Gui-Qiang Chen received the B.Eng. degree in wireless communication from Chongqing Communication College, PRC in 2000. He received the M. Sc. degree in intelligent control and pattern recognition from Chongqing University, PRC. Now he is working with Chongqing Communication College.

His research interests include intelligent control, evolutional computation and pattern recognition.

Gui-Fang Shao received the B. Sc., M. Sc., and Ph.D. degrees from Chongqing University, PRC in 2000, 2003, and 2007, respectively, all in control theory and control engineering. She is currently an associate professor with the Institute of Pattern Recognition and Intelligence System, Xiamen University, PRC.

Her research interests include the pattern recognition, image processing, and robot control.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Li, TJ., Chen, GQ. & Shao, GF. Action control of soccer robots based on simulated human intelligence. Int. J. Autom. Comput. 7, 55–63 (2010). https://doi.org/10.1007/s11633-010-0055-1

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11633-010-0055-1

Keywords

Search

Navigation