Personal robots anticipated to become popular in the future are required to be active in joint work and community life with humans. These personal robots must recognize changing environment and must conduct adequate actions like human. Visual tracking can be said as a fundamental function from the view point of environmental sensing and reflex reaction against it. The authors developed a visual tracking motion algorithm by using upper body. Then, we integrated it with an online walking pattern generator and developed a visual tracking biped locomotion. Finally, we conducted an experimental evaluation with emotion expression.

Personal robots and robot technology (RT)-based assistive devices are expected to play a major role in our elderly-dominated society, by interacting with surrounding people both physically and psychologically. A fundamental role during the interaction is of course played by the hand. In this paper we present the evaluation of the effect of hand shape to the quality of the interaction, in particular during handshake.

Personal robots and robot technology (RT)-based assistive devices are expected to play a major role in our elderly-dominated society, with an active participation to joint works and community life with humans, as partner and as friends for us. In particular, these robots are expected to be fundamental for helping and assisting elderly and disabled people during their activities of daily living (ADLs). To achieve this result, personal robots should be also capable of human-like emotion expressions. To this purpose we developed a new whole body emotion expressing bipedal humanoid robot, named KOBIAN, which is also capable to express human-like emotions. In this paper we presented three different evaluations of the emotional expressiveness of KOBIAN. In particular In particular, we presented the analysis of the roles of the face, the body, and their combination in emotional expressions. We also compared Emotional patterns created by a Photographer and a Cartoonist with the ones created by us. Overall, although the experimental results are not as good as we were expecting, we confirmed the robot can clearly express its emotions, and that very high recognition ratios are possible.