The main goal of the proposed project is to enhance a mobile robot with evolutionary optimization capabilities for tasks like egomotion estimation and/or obstacle avoidance. The robot will learn to navigate different environments and will adapt to changing conditions. This implies the implementation of vision-based navigation of robots using artificial vision, computed with on-board FPGAs. The current paper aim to contribute on the implementation of a real-time motion extraction from video a feed using embedded FPGA circuits.
 A. Vatavu, R. Danescu, |S. Nedevschi, “Real-Time Dynamic Environment Perception in Driving Scenarios Using Difference Fronts”, Proceedings of the 2012 IEEE Intelligent Vehicle Symposium, June 2012, Alcala de Henares, Spain, pp. 717-722.
 R. Danescu, S. Nedevschi, “Probabilistic Lane Tracking in Difficult Road Scenarios Using Stereovision”, in IEEE Trans. on Intelligent Transportation Systems, vol. 10, no. 2, 2009, pp. 272-282
 Dellaert, F., Thorpe, C.: Robust Car Tracking using Kalman filtering and Bayesian templates. In: proceedings of Conference on Intelligent Transportation Systems, vol. 3207, pp. 72--83. (1997)
 Nedevschi, S., Danescu, R., Marita, T., Oniga, F., Pocol, C., Sobol, S., Tomiuc, C. Vancea, C., Meinecke, M. M., Graf, T., To, T. B., Obojski, M. A.: A sensor for urban driving assistance systems based on dense stereovision. In: Intelligent Vehicles 2007, pp. 278--286, Istanbul (2007)
 D. Floreano, R. Pericet-Camara, S. Viollet, F. Ruffier and A. Brückner et al. Miniature curved artificial compound eyes, in Proceedings of the National Academy of Sciences, vol. 110, num. 23, p. 9332-9337, 2013.
 R. Pericet Camara, M. Dobrzynski, G. L'Eplattenier, J.-C. Zufferey and F. Expert et al. CURVACE - CURVed Artificial Compound Eyes. 2nd European Future Technologies Conference and Exhibition 2011 (FET 11), Budapest, Hungary, Procedia Computer Science, 2011.
 Kirschfeld K (1976) The resolution of lens and compound eyes. Neural Principles in Vision, eds Zettler F & Weiler R (Springer, Berlin, Germany), pp 354-370.
 Trong-Yen, L., et al. Sophisticated Computation of Hardware-Software Partition for Embedded Multiprocessor FPGA Systems. in Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on. 2008.
 Krichen, F., et al. Designing dynamic reconfiguration for distributed real time embedded systems. in New Technologies of Distributed Systems (NOTERE), 2010 10th Annual Intern. Conf. on. 2010.
 Bako, L., Real-time classification of datasets with hardware embedded neuromorphic neural networks. Briefings in Bioinform, 2010. 11(3): p. 348-63.
 Bako, L. and S.T. Brassai, Embedded neural controllers based on spiking neuron models. Pollack Periodica, 2009. 4(3): p. 143-154
 J. Barron, D. Fleet, S. Beauchemin, Performance of Optical flow techniques, International Journal of Computer Vision (IJCV) 12 (1994) 43-77.
 B. Horn, B. Schunck, Determining Optical flow, AI 17 (1981) 185-203.
 Lucas, B. and Kanade, T. 1981. An iterative image registration technique with an application to stereo vision. In Proceedings of the International Joint Conference on Artificial Intelligence, pp. 674- 679.