Tech United Eindhoven Middle Size League Winner 2016

  • Ferry Schoenmakers
  • Koen Meessen
  • Yanick Douven
  • Harrie van de Loo
  • Dennis Bruijnen
  • Wouter Aangenent
  • Bob van Ninhuijs
  • Matthias Briegel
  • Patrick van Brakel
  • Jordy Senden
  • Robin Soetens
  • Wouter Kuijpers
  • Joris Reijrink
  • Camiel Beeren
  • Marjon van ’t Klooster
  • Lotte de Koning
  • René van de Molengraft
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9776)

Abstract

The Tech United Eindhoven Mid-size league (MSL) team won the 2016 Championship in Leipzig. This paper describes the main progress we made in 2016 which enabled this success. Recent progress in software includes improved perception methods using combined omnivision of different robots and integrating the Kinect v2 camera onto the robots. To improve the efficiency of shots at the opponents’ goal, the obstacle detection is improved. During the tournament new defensive strategies were developed as an answer to the advanced attacking strategies that were seen during the round robins. Several statistics of matches during the tournament show the overall performance of Tech United at RoboCup 2016.

Keywords

RoboCup soccer Middle-size league Cooperative sensing Multi-network extension Kinect 

References

  1. 1.
    Ahmad, A., Xavier, J., Santos-Victor, J., Lima, P.: 3D to 2D bijection for spherical objects under equidistant fisheye projection. Comput. Vis. Image Underst. 125, 172–183 (2014)CrossRefGoogle Scholar
  2. 2.
    Martinez, C.L., et al.: Tech United Eindhoven, Winner RoboCup 2014 MSL. In: Bianchi, R.A.C., Akin, H.L., Ramamoorthy, S., Sugiura, K. (eds.) RoboCup 2014. LNCS, vol. 8992, pp. 60–69. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-18615-3_5CrossRefGoogle Scholar
  3. 3.
    Microsoft. Kinect v2 technical specifications. https://dev.windows.com/en-us/kinect/hardware
  4. 4.
    Tech United Eindhoven MSL. Tech United Eindhoven Team Description 2014 (2014)Google Scholar
  5. 5.
    Neves, A.J.R., Pinho, A.J., Martins, D.A., Cunha, B.: An efficient omnidirectional vision system for soccer robots: from calibration to object detection. Mechatronics 21(2), 399–410 (2011)CrossRefGoogle Scholar
  6. 6.
    NVIDIA: Jetson tk1 technical specifications. http://www.nvidia.com/object/jetson-tk1-embedded-dev-kit.html
  7. 7.
    Almeida, L., Santos, F., Facchinetti, T., Pedreiras, P., Silva, V., Lopes, L.S.: Coordinating distributed autonomous agents with a real-time database: the CAMBADA project. In: Aykanat, C., Dayar, T., Körpeoğlu, İ. (eds.) ISCIS 2004. LNCS, vol. 3280, pp. 876–886. Springer, Heidelberg (2004).  https://doi.org/10.1007/978-3-540-30182-0_88CrossRefGoogle Scholar
  8. 8.
    Kuijpers, W., Neves, A.J.R., van de Molengraft, R.: Cooperative sensing for 3D ball positioning in the RoboCup middle size league. In: Robocup 2016: Robot World Cup XX, Accepted for Publication (2016)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Ferry Schoenmakers
    • 1
  • Koen Meessen
    • 1
  • Yanick Douven
    • 1
  • Harrie van de Loo
    • 1
  • Dennis Bruijnen
    • 1
  • Wouter Aangenent
    • 1
  • Bob van Ninhuijs
    • 1
  • Matthias Briegel
    • 1
  • Patrick van Brakel
    • 1
  • Jordy Senden
    • 1
  • Robin Soetens
    • 1
  • Wouter Kuijpers
    • 1
  • Joris Reijrink
    • 1
  • Camiel Beeren
    • 1
  • Marjon van ’t Klooster
    • 1
  • Lotte de Koning
    • 1
  • René van de Molengraft
    • 1
  1. 1.Eindhoven University of TechnologyEindhovenThe Netherlands

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