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Skill-based visual parking control using neural and fuzzy networks

This paper presents an approach for acquisition and transfer of an experienced driver's skills to an automatic parking controller. The controller processes visual input information from a video sensor and generates the corresponding steering commands. Two neural control architectures are considered. In the direct neural control architecture the controller is a single artificial neural network. In the fuzzy hybrid control architecture the controller is configured as a combination of an artificial neural network and a fuzzy network. Both control architectures are experimentally validated with a mobile robot.