Journal of the Brazilian Computer Society

, Volume 17, Issue 1, pp 69–82

On the construction of a RoboCup small size league team

  • José Angelo GurzoniJr.
  • Murilo Fernandes Martins
  • Flavio Tonidandel
  • Reinaldo A. C. Bianchi
Open Access
Original Paper

Abstract

The Robot Soccer domain has become an important artificial intelligence test bench and a widely studied research area. It is a domain with real, dynamic, and uncertain environment, where teams of robots cooperate and face adversarial competition. To build a RoboCup Small Size League (SSL) team able to compete in the world championship requires multidisciplinary research in fields like robotic hardware development, machine learning, multi-robot systems, computer vision, control theory, and mechanics, among others.

This paper intends to provide insights about the aspects involved on the development of the RoboFEI RoboCup SSL robot soccer team and to present the contributions produced over its course. Among these contributions, a computer vision system employing an artificial neural network (ANN) to recognize colors, a heuristic algorithm to recognize partially detected objects, an implementation of the known rapidly-exploring random trees (RRT) path planning algorithm with additional rules, enabling the angle of approach of the robot to be controlled, and a layered strategy software system.

Experimental results on real robots demonstrate the high performance of the vision system and the efficiency of the RRT algorithm implementation. Some strategy functions are also experimented, with empirical results showing their effectiveness.

Keywords

Robotic soccer Computer vision Neural networks RRT path planning Omnidirectional control 

References

  1. 1.
    Arkin RC (1987) Motor schema based navigation for a mobile robot: An approach to programming by behavior. In: Proceedings of the IEEE international conference on robotics and automation (ICRA), March, vol 4, pp 264–271Google Scholar
  2. 2.
    Atramentov A, LaValle SM (2002) Efficient nearest neighbor searching for motion planning. In: IEEE international conference on robotics and automation (ICRA), pp 632–637Google Scholar
  3. 3.
    Balch T (2000) Teambots 2.0 documentation. www.teambots.org
  4. 4.
    Balch T, Ram A (1998) Integrating robotic technologies with JavaBots. In: Working notes of the AAAI 1998 spring symposium, Stanford, CA.Google Scholar
  5. 5.
    Bowling M, Browning B, Veloso M (2004) Plays as effective multiagent plans enabling opponent-adaptive play selection. In: Proceedings of international conference on automated planning and scheduling (ICAPS’04), pp 376–383Google Scholar
  6. 6.
    Browning B, Tryzelaar E (2003) Ubersim: A realistic simulation engine for robot soccer. In: Proceedings of autonomous agents and multi-agent systems (AAMAS), AustraliaGoogle Scholar
  7. 7.
    Browning B, Bruce J, Bowling M, Veloso M (2005) Stp: Skills, tactics and plays for multi-robot control in adversarial environments. IEEE J Control Syst Eng 219:33–52Google Scholar
  8. 8.
    Bruce J, Veloso M (2002) Real-time randomized path planning for robot navigation. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS)Google Scholar
  9. 9.
    Bruce J, Veloso M (2003) Fast and accurate vision-based pattern detection and identification. In: Proceedings of the IEEE international conference on robotics and automation (ICRA), Taiwan, May, pp 1277–1282Google Scholar
  10. 10.
    Bruce J, Balch T, Veloso M (2000) Fast and inexpensive color image segmentation for interactive robots. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS), October, vol 3, pp 2061–2066Google Scholar
  11. 11.
    Bruce J, Zickler S, Licitra M, Veloso M (2008) Cmdragons: Dynamic passing and strategy on a champion robot soccer team. In: Proceedings of the IEEE international conference on robotics and automation (ICRA), Pasadena, CA, pp 4074–4079Google Scholar
  12. 12.
    Cheng P, LaValle SM (2002) Resolution complete rapidly-exploring random trees. In: IEEE international conference on robotics and automation (ICRA), pp 267–272Google Scholar
  13. 13.
    Foley JD, van Dam A, Feiner SK, Hughes JF (1995) Computer graphics: Principles and practice in C, 2nd edn. Addison-Wesley, ReadingGoogle Scholar
  14. 14.
    Gurzoni JA Jr., Martins MF, Tonidandel F, Bianchi RAC (2009) A neural approach to real time colour recognition in the robot soccer domain. In: Proceedings of SBAI’09, The X Brazilian symposium of artificial intelligenceGoogle Scholar
  15. 15.
    Huntsberger TL, Trebi-ollennu A, Aghazarian H, Schenker PS, Pirjanian P (2004) Distributed control of multi-robot systems engaged in tightly coupled tasks. Auton Robots 17:79–92CrossRefGoogle Scholar
  16. 16.
    Iocchi L, Matsubara H, Weitzenfeld A, Zhou C (eds) (2009) RoboCup 2008: Robot soccer world cup XII [papers from the 12th annual RoboCup international symposium, Suzhou, China, July 15–18, 2008]. Lecture notes in computer science, vol 5399. Springer, BerlinGoogle Scholar
  17. 17.
    Kitano H, Asada M, Kuniyoshi Y, Noda I, Osawa E (1997) Robocup: The robot world cup initiative. In: AGENTS ’97: Proceedings of the first international conference on autonomous agents. ACM, New York, pp 340–347CrossRefGoogle Scholar
  18. 18.
    Kitano H, Asada M, Kuniyoshi Y, Noda I, Osawa E (1997) Robocup: A challenge problem for AI. AI Mag 18(1):73–85Google Scholar
  19. 19.
    Kitano H, Tambe M, Stone P, Veloso MM, Coradeschi S, Osawa E, Matsubara H, Noda I, Asada M (1997) The robocup synthetic agent challenge 97. In: International joint conference on artificial intelligence (IJCAI), pp 24–30Google Scholar
  20. 20.
    Kramer J, Scheutz M (2007) Development environments for autonomous mobile robots: A survey. Auton Robots 22(2):101–132CrossRefGoogle Scholar
  21. 21.
    Latombe JC (1991) Robot motion planning. Kluwer Academic, DordrechtCrossRefGoogle Scholar
  22. 22.
    Laue T (2009) B-Smart (Bremen Small Multi-Agent Robot Team) team description for robocup 2009. In: Proceedings of the international RoboCup symposium 2009 (RoboCup 2009), June 30–July 3Google Scholar
  23. 23.
    Laue T, Spiess K, Rofer T (2006) Simrobot—a general physical robot simulator and its application in robocup. In: Bredenfeld A, Jacoff A, Noda I, Takahashi Y (eds) RoboCup 2005: Robot soccer world cup IX. Springer, Berlin, pp 173–183CrossRefGoogle Scholar
  24. 24.
    LaValle SM (1998) Rapidly-exploring random trees: A new tool for path planning. Technical report, Iowa State University, OctoberGoogle Scholar
  25. 25.
    LaValle SM, Branicky MS (2003) On the relationship between classical grid search and probabilistic roadmaps. In: Algorithmic foundations of robotics V, vol 7. Springer, Berlin, pp 59–76CrossRefGoogle Scholar
  26. 26.
    Martins MF, Tonidandel F, Bianchi RAC (2007) Towards model-based vision systems for robot soccer teams. In: Lima P (ed) Robotic soccer, Chap. 5. I-Tech Education and Publishing, pp 95–108Google Scholar
  27. 27.
    Mataric MJ (2001) Learning in behavior-based multi-robot systems: Policies, models, and other agents. In: Cognitive systems research, April, pp 81–93Google Scholar
  28. 28.
    Mills JK, Ing JGL (1996) Dynamic modeling and control of a multi-robot system for assembly of flexible payloads with applications to automotive body assembly. J Robot Syst 13(12):817–836CrossRefGoogle Scholar
  29. 29.
    Mitchell TM (1997) Machine learning (ISE Editions). McGraw-Hill Education, New YorkGoogle Scholar
  30. 30.
    Nouyan S, Gross R, Dorigo M, Bonani M, Mondada F (2005) Group transport along a robot chain in a self-organised robot colony. In: Proceedings of the 9th int conf on intelligent autonomous systems. IOS Press, Amsterdam, pp 433–442Google Scholar
  31. 31.
    RoboCup Federation (2010) Laws of the Small Size League 2010Google Scholar
  32. 32.
    Rojas R, Förster AG (2006) Holonomic control of a robot with an omnidirectional drive. Künstl Intell 20(2):12–17Google Scholar
  33. 33.
    Simões AS, Reali Costa AH (2000) Using neural color classification in robotic soccer domain. In: International joint conference IBERAMIA’00 Ibero-American conference on artificial intelligence and SBIA’00 Brazilian symposium on artificial intelligence, pp 208–213Google Scholar
  34. 34.
    Sridharan M, Stone P (2007) Color learning on a mobile robot: Towards full autonomy under changing illumination. In: Veloso MM (ed) International joint conference on artificial intelligence (IJCAI), pp 2212–2217Google Scholar
  35. 35.
    Srisabye J, Wasuntapichaikul P, Onman C, Sukvichai K, Damyot S, Munintarawong T, Phuangjaisri P, Tipsuwan Y (2009) Skuba 2009 extended team description. In: Proceedings of the international RoboCup symposium 2009 (RoboCup 2009), June 30–July 3.Google Scholar
  36. 36.
    Stone P, Veloso M (1999) Task decomposition, dynamic role assignment, and low-bandwidth communication for real-time strategic teamwork. Artif Intell 110(2):241–273CrossRefGoogle Scholar
  37. 37.
    Sun D, Mills JK (2002) Adaptive synchronized control for coordination of multirobot assembly tasks. IEEE Trans Robot Autom 18:498–510CrossRefGoogle Scholar
  38. 38.
    Tambe M (1998) Implementing agent teams in dynamic multiagent environments. Appl Artif Intell 12(2–3):189–210CrossRefGoogle Scholar
  39. 39.
    Tao W, Jin H, Zhang Y (2007) Color image segmentation based on mean shift and normalized cuts. IEEE Trans Syst Man Cybern, Part B, Cybern 37(5):1382–1389CrossRefGoogle Scholar
  40. 40.
    Visser U, Ribeiro F, Ohashi T, Dellaert F (eds) (2008) RoboCup 2007: Robot soccer world cup XI, July 9–10, 2007, Atlanta, GA, USA. Lecture notes in computer science, vol 5001. Springer, BerlinGoogle Scholar

Copyright information

© The Brazilian Computer Society 2011

Authors and Affiliations

  • José Angelo GurzoniJr.
    • 1
  • Murilo Fernandes Martins
    • 2
  • Flavio Tonidandel
    • 1
  • Reinaldo A. C. Bianchi
    • 1
  1. 1.Department of Electrical Engineering and Computer ScienceCentro Universitario da FEISao Bernardo do CampoBrazil
  2. 2.Department of Electrical and Electronic EngineeringImperial College LondonLondonUK

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