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Motion Generation Considering Physical Consistency

Virtual fighting between a human and a humanoid robot at EXPO2005
Fig.1  Virtual fighting between a human and a humanoid robot at EXPO2005

Motion database including captured data, HMMs, and word labels
Fig.2  Motion database including captured data, HMMs, and word labels

Outline

    We have modeled the primitive nonverbal communication between two persons by the mimetic communication model. This model consists of two groups of Hidden Markov Models (HMMs) hierarchically combined to recognize the motions of a human and to generate the corresponding interactive motions of a robot. HMMs in the lower layer abstract the motion patterns and those in the upper layer represent the interaction patterns. We call the former "Proto Symbols" and the latter "Meta Proto Symbols." Since this model includes Meta Proto Symbols, i.e., the representations of interaction patterns between a robot and a human, it enables the robot to estimate the current interaction and to respond socially to human behaviors. Fig. 1 shows the demonstration of our system at EXPO 2005.

    In addition, we are investigating the acquisition of language based on motion-pattern symbols because both motion and language are a type of linguistic processing. So far, we have proposed a method to build a stochastic model mapping the relationship between Proto Symbols and words. Fig.2 shows the overview of this study. Each Proto Symbol abstracts several motion patterns, while the word labels are given to the motion data manually. By establishing the connection between motions and a language, we would like to make the robot understand natural language and behave as described by that language.



Bibliography
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Awards, Patents



Members

Wataru TAKANO, Dana KULIC, Minoru KANAZAWA, Naoto KAWABE, Youtaroh ISHIKAWA, Tatsuhiro JORDAN

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