Human recognition of a partner robot based on relevance theory and neuro-fuzzy computing

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.