Recent research in mobile robot navigation make it feasible to utilize autonomous robots in service fields. But, such applications require more than just navigation. To operate in a peopled environment, robots should recognize and act according to human social behavior. In this paper, we present the design and implementation of one such social behavior: a robot that stands in line much as people do. The system employs stereo vision to recognize lines of people, and uses the concept of personal space for modeling the social behavior. Personal space is used both to detect the end of a line and to determine how much space to leave between the robot and the person in front of it. Our model of personal space is based on measurements from people forming lines. We demonstrate our ideas with a mobile robot navigation system that can purchase a cup of coffee, even if people are waiting in line for service.

No abstract

No abstract

In this paper, we propose a telepresence robot for avoiding speech collisions occurred in remote conversa-tions.In face-to-face conversations, humans predict who will speak in next by referring other participants' motions. These motions are called pre-motions. However, pre-motions are likely to be unperceived in teleconferences such as video chat conversations using two-dimensional video. The failure of the prediction causes speech collisions. It undermines the participants' motivation and wastes time. To solve this problem, we propose a telepresence robot conveying gestures including pre-motions.We use Kinect for the gesture perception device and humanoid robot for conveying unconscious gestures.

No abstract