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