Cognitive Environment System by Joint Attention Behaviors and Relevance Theory for Robot Partners

In recent years, various kinds of communication robots are active in our lives. However, most of them consider only the existence of speaker and listener. In this paper, we aim to realize a more lively and lifelike communication by developing the relationship between speaker, listener and objects that exist in the environment. We propose a cognitive environment system for a robot partner to determine objects that referred by humans. The proposed system measures the degree of relevance of objects existing in the environment from two perspectives such as the verbal information based on relevance theory and non-verbal information based on joint attention behaviors. We validate the proposed system through series of interaction experiments. Experiment results showed that robot is able to identify objects that referenced by humans with the proposed communication system.