Freie Universität Berlin, Fachbereich Mathematik und Informatik : Ser. B, Informatik ; 03,15
004 Datenverarbeitung; Informatik
In the robotics area, visual tracking is an important and difficult problem therefore
is necessary to have a robust and efficient control algorithm which presents immunity
characteristics to stochastic direction and speed changes of the object to be
tracked. Also is important count with a segmentation algorithm which be able to tolerate
changes in the intensity of light. We describe in this report the implementation
of fuzzy controllers based on the fuzzy condensed algorithm and also the developed of
a LVQ neural network to segment the image. For this work we used two fuzzy condensed
algorithms running in a PC to control a robot’s head which tracks a human
face. We describe the main lines of the fuzzy condensed algorithm as well as the LVQ
neural networks architecture employed and the implementation, the fuzzy condensed
controller performance in comparison to a PID controller and real time results.
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