A brain-machine interface allowed participants to do a task with a robotic arm while performing a different task with their own arms.

Controlling a brain-computer interface (BCI) is a difficult task that requires extensive training. Particularly in the case of motor imagery BCIs, users may need several training sessions before they learn how to generate desired brain activity and reach an acceptable performance. A typical training protocol for such BCIs includes execution of a motor imagery task by the user, followed by presentation of an extending bar or a moving object on a computer screen. In this chapter, we discuss the importance of a visual feedback that resembles human actions, the effect of human factors such as confidence and motivation, and the role of embodiment in the learning process of a motor imagery task. Our results from a series of experiments in which users BCI-operated a humanlike android robot confirm that realistic visual feedback can induce a sense of embodiment, which promotes a significant learning of the motor imagery task in a short amount of time. We review the impact of humanlike visual feedback in optimized modulation of brain activity by the BCI users.

This paper provides insight into how recent progress in robotics could affect children's lives in the not-so-distant future. We describe two studies in which robots were presented to children in the context of their daily lives. The results of the first study, which was conducted in an elementary school with a mechanical-looking humanoid robot, showed that the robot affected children's behaviors, feelings, and even their friendships. The second study is a case study in which children performed daily conversational tasks with a geminoid, a teleoperated android robot that resembles a living individual. The results showed that children gradually adapted to conversations with the geminoid and developed an awareness of the personality or presence of the person controlling the geminoid. These studies provide clues to the process of children's adaptation to interactions with robots and particularly how they start treating robots as intelligent beings.

This research constitutes an initial investigation into key issues which arise in designing a flying humanoid robot (FHR), with a focus on human-robot interaction (HRI). The humanoid form offers an interface for natural communication; flight offers excellent mobility. Combining both will yield companion robots capable of approaching, accompanying, and communicating naturally with humans in difficult environments. Problematic is how such a robot should best fly around humans, and what effect a robot's flight will have on a person in terms of non-verbal communicative cues. To answer these questions, we propose an extension to existing proxemics theory (“z-proxemics”) and predict how typical humanoid flight motions will be perceived (“z-kinesics”). Data obtained from participants watching animated sequences are analyzed to check our predictions. The paper also reports on the building of a flying humanoid robot, which we will use in interactions.