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Extraction of Robot Primitive Control Rules from Natural Language Instructions 被引量:1
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作者 Guang-Hong Wang Ping Jiang Zu-Ren Feng 《International Journal of Automation and computing》 EI 2006年第3期282-290,共9页
A support vector rule based method is investigated for the construction of motion controllers via natural language training. It is a two-phase process including motion control information collection from natural langu... A support vector rule based method is investigated for the construction of motion controllers via natural language training. It is a two-phase process including motion control information collection from natural language instructions, and motion information condensation with the aid of support vector machine (SVM) theory. Self-organizing fuzzy neural networks are utilized for the collection of control rules, from which support vector rules are extracted to form a final controller to achieve any given control accuracy. In this way, the number of control rules is reduced, and the structure of the controller tidied, making a controller constructed using natural language training more appropriate in practice, and providing a fundamental rule base for high-level robot behavior control. Simulations and experiments on a wheeled robot are carried out to illustrate the effectiveness of the method. 展开更多
关键词 Support vector machines (SVMs) fuzzy neural networks motion primitives motion controller language instruction based training natural language programming.
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