LEARNING
Human recognition of a partner robot based on relevance theory and neuro-fuzzy computing
Naoyuki Kubota, Kentaro Nishida
- 发表年份
- 2005
- 引用次数
- 13
摘要
This paper proposes a human recognition method of a partner robot for natural communication with human. Basically, human recognition is performed by using various types of information. In this paper, we use the color image of human face and pattern of conversation with the human. The proposed method is composed of k-means algorithm, spiking neural network, self-organizing map, and steady-state genetic algorithm. Furthermore, we show experimental results of the partner robot based on the proposed method.
关键词
Computer scienceArtificial intelligenceRelevance (law)RobotArtificial neural networkFuzzy logicHuman–robot interactionNatural (archaeology)Pattern recognition (psychology)Conversation
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