Abstract
This article presents a new approach to mobile robot vision based on genetic algorithms. The major contribution of this proposal is the real-time adaptation of genetic algorithms, which are generally used offline. In order to achieve this goal, the execution time must be as short as possible. The scope of this system is the Standard Platform category of the RoboCup soccer competition. The system developed detects and estimates distance and orientation to key elements on a football field, such as the ball and goals. Different experiments have been carried out within an official RoboCup environment.
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Rofer, T., Brunn, R., Dahm, I., Hebbel, M., Hoffmann, J., Jungel, M., Laue, T., Lotzsch, M., Nistico, W., Spranger, M.: GermanTeam 2004. Team Report RoboCup (2004)
Wasik, Z., Saffiotti, A.: Robust color segmentation for the robocup domain. In: Pattern Recognition, Proc. of the Int. Conf. on Pattern Recognition (ICPR), vol. 2, pp. 651–654 (2002)
Jüngel, M., Hoffmann, J., Lötzsch, M.: A real-time auto-adjusting vision system for robotic soccer. In: Polani, D., Browning, B., Bonarini, A., Yoshida, K. (eds.) RoboCup 2003. LNCS (LNAI), vol. 3020, pp. 214–225. Springer, Heidelberg (2004)
Coath, G., Musumeci, P.: Adaptive arc fitting for ball detection in robocup. In: APRS Workshop on Digital Image Analysing, pp. 63–68 (2003)
Mitchell, M.: An Introduction to Genetic Algorithms (1996)
Whitley, L.: Cellular Genetic Algorithms. In: Proceedings of the 5th International Conference on Genetic Algorithms table of contents. Morgan Kaufmann Publishers Inc., San Francisco (1993)
Foley, J.D., van Dam, A., Feiner, S.K., Hughes, J.F.: Computer graphics: principles and practice. Addison-Wesley Longman Publishing Co., Inc., Amsterdam (1990)
Borenstein, J., Everestt, H., Feng, L.: Where am I? Sensors and Methods for Mobile Robot Positioning (1996)
Bach, J., Jungel, M.: Using pattern matching on a flexible, horizon-aligned grid for robotic vision. Concurrency, Specification and Programming-CSP 1(2002), 11–19 (2002)
Moscato, P.: Memetic algorithms: a short introduction. Mcgraw-Hill’S Advanced Topics In Computer Science Series, pp. 219–234 (1999)
Fox, D., Burgard, W., Thrun, S.: Active markov localization for mobile robots (1998)
Negenborn, R.: Robot localization and kalman filters (2003)
Martínez-Gómez, J., José, A., Gámez, I.G.V.: An improved markov-based localization approach by using image quality evaluation. In: Proceedings of the 10th International Conference on Control, Automation, Robotics and Vision (ICARCV), pp. 1236–1241 (2008)
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Martínez-Gómez, J., Gámez, J.A., García-Varea, I., Matellán, V. (2010). Using Genetic Algorithms for Real-Time Object Detection. In: Baltes, J., Lagoudakis, M.G., Naruse, T., Ghidary, S.S. (eds) RoboCup 2009: Robot Soccer World Cup XIII. RoboCup 2009. Lecture Notes in Computer Science(), vol 5949. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11876-0_19
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DOI: https://doi.org/10.1007/978-3-642-11876-0_19
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