Abstract
The present work focuses on the implementation of a robust and fault tolerant global vision system for RoboCup Small League soccer teams. It is based on a vision control approach, in which vision processes are guided by necessit yof information and knowledge aboutthe environment. The object detection is based on a chromatic approach where chromatic patterns were modeled using a mixture of gaussian functions, trained with a stochastic gradient descent method. The implemented system meets, and in certain cases exceeds, the functionality required to participate in RoboCup and reported in related works.
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© 2001 Springer-Verlag Berlin Heidelberg
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Ramírez, J., Grittani, G. (2001). Robust Chromatic Identification and Tracking. In: Mira, J., Prieto, A. (eds) Bio-Inspired Applications of Connectionism. IWANN 2001. Lecture Notes in Computer Science, vol 2085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45723-2_60
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DOI: https://doi.org/10.1007/3-540-45723-2_60
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