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Vol: 56(70) No: 1 / March 2011 A Barcode Based Kin Recognition and Identification Method for Robot Swarms Kalman Bolla Kecskemet College, Izsaki ut 10, 6000 Kecskemet, Hungary, e-mail: bolla.kalman@gamf.kefo.hu Tamas Kovacs Kecskemet College, Izsaki ut 10, 6000 Kecskemet, Hungary, e-mail: kovacs.tamas@gamf.kefo.hu Gabor Fazekas University of Debrecen, Egyetem t. 1, 4032 Debrecen, Hungary, e-mail: fazekasg@inf.unideb.hu Keywords: mobile robot swarm, kin recognition, robot identification Abstract This paper focuses on a barcode based kin recognition, identification and distance evaluation method for mobile-robot swarms. Every robot in the swarm is equipped with a zebra pattern and our idea is based on the Fast Fourier Transform (FFT), which has a relatively low complexity. We sampled the camera images of the robot by columns, and the sampled column were the inputs of the FFT since the Fourier Transform can detect this kind of pattern. Moreover, based on the FFT spectrum this method is capable to estimate the distance of the kin robot. Besides, the zebra pattern is modified into a barcode like pattern, and so the identification of the swarm members is also possible. To test our idea several experiments were accomplished with Surveyor SRV-1 robots, which have an on-board camera system. The captured pictures of the observer robot were sent to and processed in a PC using MATLAB program. References [1] C. Stachniss, W. Burgard, “Exploring unknown environments with mobile robots using coverage maps”, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 2003, pp. 1127-1134. [2] S. Rutishauser, N. Correll and A. Martinoli, “Collaborative coverage using a swarm of networked miniature robots”, Robotics and Autonomous Systems, doi:10.1016/j.robot.2008.10.023. [3] M. N. Rooker and A. Birk, “Multi-robot exploration under the constraints of wireless networking”, Control Engineering Practice, vol. 15, 2007, pp. 435–445. [4] S. Nouyan and M. Dorigo, “Chain based path formation in swarms of robots”, Ant Colony Optimization and Swarm Intelligence, M. Dorigo et al., Eds., Springer-Verlag Berlin Heidelberg, 2006, pp. 120–131. [5] I. Engedy, G. Horváth, “A global camera –based mobile robot localization”, Proceedings of 10th International Symposium of Hungarian Researchers on Computational Intelligence (CINTI 2009), Budapest, Hungary, 2009, pp. 217-228. [6] I. Rekleitis, G. Dudek, E. Milios, “Multi-robot collaboration for robust exploration”, Annals of Math. and Artifical Intelligence 31, 2001, pp. 7-40. [7] Y. Han, H. Hahn, “Visual Tracking of a moving Target using Active Contour based SSD Algorithm”, Robotics and Autonomous Systems 53, 2005, pp. 265-281. [8] V. K. Ingle, J. G. Proakis, Digital Signal Processing using MATLAB, Thomson Bookware Companion Series, 2007. [9] I. Z. Yalniz and S. Aksoy, “Unsupervised detection and localization of structural textures using projection profiles”, Pattern Recognition, vol. 43, no. 10, 2010, pp. 3324-3337. [10] K. Bolla, T. Kovacs and G. Fazekas, “Compact image processing based kin recognition, distance measurement and identification method in a robot swarm”, Proceedings of IEEE International Joint Conferences on Computational Cybernetics and Technical Informatics (ICCC-CONTI 2010), Timisoara, Romania, 2010. |