The essential challenge in the future ubiquitous networks is to make information available to people not only at any time, at any place, and in any form, but with the right thing at the right time in the right way by inferring the users' situations. Several psychological experiments show that there are some associations between each user's situations including the user's emotions and each user's task selection. Utilizing those results, this article presents a situation-based task selection mechanism that enables a life-supporting robot system to perform tasks based on the user's situation. Stimulated by interactions between the robot and the user, this mechanism constructs and updates the association between the user's situation and tasks so that the robot can adapt to the user's behaviors related to the robot's tasks effectively. For the user adaptation, Radial Basis Function Networks (RBFNs) and associative learning algorithms are used. The proposed mechanism is applied to the CRF3 (Character robot face 3) system to prove its feasibility and effectiveness. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 973–1004, 2006.

This paper presents a situation-based task selection mechanism which enables a life supporting robot system to perform tasks-based on the user's situation. Stimulated by interactions between robot and user, this mechanism constructs and updates the association between the user's situation and tasks so that the robot could adapt to user's behaviors related to the robot's tasks effectively. For the user adaptation, radial basis function networks (RBFN) and associative learning algorithms are used. The proposed mechanism is applied to CRF3 (character robot face 3) system to prove its feasibility and effectiveness.

This paper explores a human-robot mutual communication system, which human users can either communicate with or use as an information terminal. In particular, we propose the deformation based facial expression system. We also propose a robotic vision system, which changes its visual attention according to the environment. Firstly, the system must have advanced abilities to express their intention by means of making facial expressions, gestures, or speech. Above all, facial expression. Reconsidering the facial action coding system and action unit from the point of what expression of the robot human recognize easily. We propose the deformation based expression system. Secondly, to realize fluent communication between human and robots, we propose a robot vision system changing its gazing communication according to the environment and situation based on visual recognition. We developed an original character robot (CR) and evaluated the proposed methods. Consequently, it was shown that human-robot mutual communication is achievable.