In recent years, robots working in human living space with human-robot interactions are actively studied. To these robots, it is important to perform environmental cognition not only building environment map for autonomous motion of the robots but also estimating presences of human around the robots. In this study, by utilizing human state estimation function and SLAM based mapping technology, a concept and architecture of Human Motion Map by representing human behavior in the human living space as a hybrid map system are proposed. Beyond the conventional map which represents the existence of wall and objects, Human Motion Map represents not only the existence of humans in a particular location but also motion distributions. With recent improvements of the cloud computing technology, Human Motion Map can be accumulated as a kind of big data while measurements of robots are performed continuingly while it is moving around. In this paper, we propose a motion feature classification algorithm for clustering human motions geographically. Some experiment result of basic motion feature extraction, geographical clustering, and human motion behavior analyzing are provided for illustrating the validity of proposed algorithm.

In collaborative learning, participants interact with other members by exchanging not only verbal information but also nonverbal information, such as looking at other participants and note taking, which plays an important role in facilitating effective learning. In order to utilize such non-verbal information to analyze collaborative learning interaction, we conducted experiments to collect non-verbal information (gaze direction, speech intervals, and writing actions of participants) using multimodal measurement devices. In this paper, we propose a visualization method of collaborative learning based on a multimodal corpus of collaborative learning. The method intuitively visualizes the learning interaction with respect to collaborative and learning attitudes of each participant. We introduce the prototype system and show an example of the interface.