Abstract
The theory of behavioral communication for humanoid robots that interact with humans is discussed in this paper. For behavioral communication, it is fundamental for a humanoid robot to recognize the meaning of the whole body motion of a human. According to the previous works, it can be done in the symbolic level by adopting the proto-symbol space defined by the Hidden Markov Models based on the mimesis theory. The generation of robot motions from the proto-symbols is also to be done in the same framework. In this paper, we first introduce the meta proto-symbols that stochastically represent and become signifiants of the interaction of a robot and a human. The meta proto-symbols are a little more abstract analogy of the proto-symbols and recognize/generate the relationship of the two. A hypothesis is then proposed as the principle of fundamental communication. The experimental result follows.
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