From stochastic motion generation and recognition to geometric symbol development and manipulation

Abstract

Abstract. Mimesis theory is one of the primitive skill of imitative learning, which is regarded as an origin of human intelligence because imitation is fundamental function for communication and symbol manipulation. When the mimesis is adopted as learning method for humanoids, loads for designing full body behavior would be decrease because bottomup learning approaches from robot side and top-down teaching approaches from user side involved each other. Therefore, we propose a behavior acquisition and understanding system for humanoids based on the mimesis theory. This system is able to abstract observed others ' behaviors into symbols, to recognize others ' behavior using the symbols, and to generate motion patterns using the symbols. In this paper, we extend the mimesis model to geometric symbol space which contains relative distance information among symbols. We alsodiscuss how to generate complex behavior by geometric symbol manipulation in the symbol space, and how to recognize novel behavior using combination of symbols by known symbols. 1