Resumen este artículo presenta el desarrollo de un

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Resumen Este artículo presenta el desarrollo de un algoritmo para la extracción de bordes basado en la teoría de lógica difusa, mediante el cual es posible reconocer las marcas de un campo de juego para la liga humanoide de RoboCup. El algoritmo propuesto describe la creación de un sistema de inferencia difuso que permite evaluar la relación existente entre los pixe- les de una imagen, encontrando así las variaciones en los niveles de gris para una vecindad de pixeles específica. Posteriormente se plantea la implementación del método OTSU para binarizar la imagen obtenida en el proceso difuso y así generar una imagen que contiene solo los bordes extraídos, validando el algoritmo en imágenes de la liga humanoide. Luego se analizan los resultados obtenidos evidenciando el buen desem- peño del algoritmo, considerando que el tiempo de procesamiento de la propuesta es tan solo el 35% más del tiempo necesario en métodos tradi- cionales, mientras que los bordes extraídos son unos 52% menos suscepti- bles al ruido. Palabras clave Sistemas difusos, robótica, robots humanoides, sistema de visión.
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Tecno. Lógicas., No. 30, enero-junio de 2013 [35] 1. INTRODUCCIÓN The developments applied to robots able to perform human ac- tivities such as locomotion, vision, among others, has been ad- dressed from various research fields. Therefore it has become a fundamental part of global initiatives which seeks to promote the study and development of autonomous robots with human charac- teristics. An initiative with the largest global interested popula- tion is RoboCup Soccer, where making robots to play soccer seeks to promote the development of intelligent systems capable to per- form cooperative works (Asada et al. , 1998; Cheng, 2006). Among categories that have been raised as part of this initia- tive it is the Humanoid league. This category is divided by the size of competing robot. It has three sub-categories: KidSize, TeenSize and AdultSize. All categories of Humanoid robots have local vision system and the proposed challenge is the same (Zickler, 2010), develop a robot team able to play soccer overcoming technical problems of mobility and vision, but differ in size allowed for ro- bots; finding in KidSize size limitation from 30 to 60 cm, for TeenSize from 100 to 120 cm and AdultSize from 130 cm onwards. To introduce solutions to problems of vision is necessary to look for an algorithm capable to detect edge into an image cap- tured by the player, as a tool for locating robot into play field. In addition increases perception of ball and other reference objects to help its spatial location (Cheng, 2006). Beginning on the theory of edge detection based on the differ- ence between intensity of a reference pixel and each one of neigh- boring pixels, we use fuzzy logic theory to implement the proposed algorithm. As processing has significant advantages because it is less susceptible to noise on image and considering that the robot works in varying conditions, it is possible that images contain a high noise level, so a fuzzy logic method is more suitable for this case (Chacón et al. , 2002; Chi et al. , 1996).
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