Abstract
Following obstacle free paths towards the ball and avoiding opponents while dribbling are key skills to win soccer games. These tasks are challenging as the robot’s environment in soccer games is highly dynamic. Thus, exact plans will likely become invalid in the future and continuous replanning is necessary. The robots of the RoboCup Standard Platform League are equipped with limited computational resources, but have to perform many parallel tasks with real-time requirements. Consequently, path planning algorithms have to be fast.
In this paper, we compare two approaches to reduce the planning time by using a local-multiresolution representation or a log-polar representation of the environment. Both approaches combine a detailed representation of the vicinity of the robot with a reasonably short planning time. We extend the multiresolution approach to the time dimension and we predict the opponents movement by projecting the planning robot’s intentions.
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References
Behnke, S.: Local Multiresolution Path Planning. In: Polani, D., Browning, B., Bonarini, A., Yoshida, K. (eds.) RoboCup 2003. LNCS (LNAI), vol. 3020, pp. 332–343. Springer, Heidelberg (2004)
Behnke, S., StĂ¼ckler, J.: Hierarchical Reactive Control for Humanoid Soccer Robots. International Journal of Humanoid Robots (IJHR) 5(3), 375–396 (2008)
Borenstein, J., Koren, Y.: The Vector Field Histogram-Fast Obstacle Avoidance for Mobile Robots. IEEE Trans. on Robotics and Automation 7(3), 278–288 (1991)
Kaelbling, L., Lozano-PĂ©rez, T.: Hierarchical Task and Motion Planning in the Now. MIT-CSAIL-TR-2010-026 (2010)
Lagoudakis, M., Maida, A.: Neural maps for mobile robot navigation. In: IJCNN 1999 (1999)
Longega, L., Panzieri, S., Pascucci, F., Ulivi, G.: Indoor robot navigation using log-polar local maps. In: Prep. of 7th Int. IFAC Symp. on Robot Control, pp. 229–234 (2003)
RoboCup Technical Commitee: RoboCup Standard Platform League Rule Book (2010)
Röfer, T., Laue, T., MĂ¼ller, J., Burchardt, A., Damrose, E., Fabisch, A., Feldpausch, F., Gillmann, K., Graf, C., de Haas, T.J., Härtl, A., Honsel, D., Kastner, P., Kastner, T., Markowsky, B., Mester, M., Peter, J., Riemann, O.J.L., Ring, M., Sauerland, W., Schreck, A., Sieverdingbeck, I., Wenk, F., Worch, J.H.: B-Human Team Report and Code Release (2010), http://www.b-human.de/file_download/33/bhuman10_coderelease.pdf
Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice-Hall (2009)
Sermanet, P., Hadsell, R., Scoffier, M., Muller, U., LeCun, Y.: Mapping and planning under uncertainty in mobile robots with long-range perception. In: Proc. of IROS (2008)
Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics (Intelligent Robotics and Autonomous Agents). MIT Press (2001)
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Nieuwenhuisen, M., Steffens, R., Behnke, S. (2012). Local Multiresolution Path Planning in Soccer Games Based on Projected Intentions. In: Röfer, T., Mayer, N.M., Savage, J., Saranlı, U. (eds) RoboCup 2011: Robot Soccer World Cup XV. RoboCup 2011. Lecture Notes in Computer Science(), vol 7416. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32060-6_42
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DOI: https://doi.org/10.1007/978-3-642-32060-6_42
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