A large number of artifacts are called robots even if the developers did not intend to use that name for their products. However, we cannot say what is a “robot” clearly; there is a contradiction between the image of a “robot” and the actual existing robots. In this article, we first categorize robots into two categories. And then we describe that we focus on communication robots, especially, android robots. Following, we propose a remote-controlled android system called Geminoid HI-1. At this article’s conclusion, we will discuss a remote-control system that uses a human-like android robot as a new telecommunication medium and our sight of future robots.

Information technology can be classified into three categories; the physical signal processing, the logical symbol processing and the KANSEI (emotional) information processing. Human communication is related to the last one. To treat KANSEI information, computer must have physical body because the KANSEI is strictly related to the fact that we have finite size of body and lifetime. Robot is one of the most suitable information terminals with multi-modal communication channel to realize a new type of man-machine interface with KANSEI. This article describes some considerations on KANSEI as the third target of information processing and human-robot interactions with some examples.

The paper describes a Bayesian-based method for inferring a dialogist’s emotion from his or her voice, for Kansei robotics. The method uses a Bayesian model of prosodic features. This research focuses on the emotional elements included in the dialogist’s voice. Thus, the training datasets are prosodic features extracted from emotionally expressive voice data. The Bayesian information criterion, an information-theoretical selection method, is used in the learning Bayesian networks. Our method learns the dependence and its strength between the dialogist’s utterance and his emotional state. We propose a reasoner to infer the dialogist’s emotional state by using a Bayesian network for the prosodic features of the dialogist’s voice. The paper reports empirical reasoning findings and discusses how the relationship between certain components of prosodic features and certain emotions affects the reasoning.

In this paper, an interface to instruct robots by the movement of the human head is presented. In the proposed interface, a robot moves in cooperation with the movement of the human head. The intersection point between the extension line of the head direction and a plane on which robots work is regarded as the instruction point and an interface system in which the robot follows the movement of the instruction point is constructed. In addition, the “Kansei” transfer function is introduced with its input being the instruction point and output being the reference point of the robot motion so that the cooperative movement of the robot can be smooth and acceptable to human psychology. The parameters of the “Kansei” transfer function are determined by the relative position of the robot to the human, and the distribution of the desirable parameters is expressed using B-spline surface. The effectiveness of the proposed interface is confirmed through the experiments.

We propose a robot behavior generation scheme that generates behaviors based on senses of “curiosity” and “boredom,” to create a companion robot named SELF with which humans do not get bored. The scheme was developed using a simple but unique simulation environment. A red ball and a blue ball were displayed on a computer; the human subject moved the red ball. First, the impressions of various motions and actions of the robot were examined. The actions at moderate speed create agreeable impressions. Based on natural interpersonal interaction patterns, the actions that the robot is expected to generate are classified into four types: “following action,” “fleeing action,” “no interferential action,” and “no action.” We analyzed humans’ impressions of the behaviors of the robot generated by switching the four basic actions at moderate speed. Three types of information transfer efficiency characterized these behaviors. We proposed the behavior generation scheme for SELF. The autonomous learning capability of SELF was realized by updating this conditional probability. Using the developed scheme, SELF can display curiosity and boredom resembling that seen in animals, including humans. Lastly, impressions of the robot behaviors were examined: two were characterized by information transfer efficiency; one was controlled by the proposed scheme.

This paper discusses natural communication based on an emotional model for partner robots based on visual perception. The partner robots should have various capabilities of perceiving, acting, communicating, and surviving through physically and emotionally interacting with a human. First of all, we discuss the role of an emotional model for a partner robot. Next, we propose the concept of natural communication with an emotional model. Partner robots performs utterances based on the results of the emotional model. Furthermore, this paper proposes a method for extracting human facial landmarks to realize natural communication for partner robots. Evolutionary computation is used for human face detection and human tracking based on adaptive color template matching. A temporary template pattern is updated according to the search result of the previous image. After constructing a normalized human face image, the positions and features of facial landmarks are extracted. Finally, we show experimental results of the emotional communication based on the visual perception.

Although human symbiosis service robots have been developed in various sizes, there have been few quantitative investigations on the psychological effect that the size of a robot has on the user. We focused on the height of a robot (robot size), its relationship to the degree of fear or anxiety experienced by a human interacting with the robot, and the appropriate human-robot distance. We prepared three mobile robots measuring 0.6, 1.2 and 1.8 m tall. In our experiment, one of these robots would approach a male subject from a distance of 3 m at up to 0.4 m/s, and the subject would use a switch to stop the robot when he felt anxious. We measured the human-robot distance at the point when the subject stopped the robot. Then we asked the subject to fill out a questionnaire to evaluate the difference in degree of anxiety for robots of different sizes. Experiments with 19 subjects showed a tendency towards a longer human-robot distance for a larger robot. The questionnaire results revealed that the subjects felt maximum anxiety for the 1.8-m-tall robot although some subjects experienced anxiety in the case of the 0.6-m-tall robot, too. The results for both human-robot distance and the questionnaires will be useful in designing service robots.

Familiarity is one of the most important requirements for human symbiosis robots, such as care service robots. To improve familiarity of a human symbiosis robot, we proposed a novel concept called “robot avatar.” A robot avatar is a small robot mounted on a main robot, and it performs gestures instead of the main robot. Although our previous study revealed that a robot avatar was effective for increasing users’ familiarity with a robot, the effect of users’ age on the improvement of familiarity by a robot avatar was not investigated well because the most of the subjects in the previous study were young. When considering the application of a robot avatar to care service robots, it is important to investigate the effect of a robot avatar on elderly people. In this paper, we focus on elderly subjects, and carried out an experiment to test if a robot avatar is effective for elderly people to improve familiarity. The result was positive, and the effect of a robot avatar on elderly people was stronger than that on younger people. From a comparison of the results from elderly subjects with those from younger subjects, we found that the elderly paid less attention to dialogue between a human and a robot.

Aiming at securing a comfortable, safe and high-quality life for all people, including the elderly, children, the physically impaired, and women, our research evaluates the conditions of living or working spaces using virtual reality. After comparing virtual spaces and real spaces by experiment and revealing the similarities and differences between the two, we planned a further experiment to evaluate the conditions of spaces that provide a feeling of safety and comfort, especially for women. From our questionnaire survey, the features of the answers given only by women are related to the condition of being seen or unseen. Therefore, we planned an experiment to clarify the conditions of openness of space related to feeling unsafe or safe. In generating the virtual spaces, we focused our attention on the window, since it is known that windows have the greatest impact on the openness of living spaces and that such openness is determined by both the size and view of a window. Experiments were conducted to evaluate the impressions given by rooms with a window of various sizes and outside views. From the results of questionnaire analysis, there were significant effects of window view for various impression items. Moreover, the results showed a difference in the feeling of openness between men and women. In this article, we introduce the results of the latest experiment in which we targeted only the window view and employed both a questionnaire and biological signals for evaluation of spaces.

In this study we propose a framework using neural oscillators for human-robot physical interaction such as “handshaking”. Neural oscillators are used for synchronization and entrainment between human and robot motions. Passiveness of the handshake can be changed by adjusting strength of the synchronization. Joint torque information is taken as an input signal for the neural oscillators, which generates the desired trajectory of each robot joint. This paper addresses a model structure of the neural oscillator for human-robot physical interaction. Computer simulations of handshaking show the synchronization and the entrainment. In addition, the experiments with a joint torque sensing robot arm show that a handshake between a robot and a human being can be realized by the proposed method. Finally, the validity of the proposed method was examined through a psychological evaluation with a paired comparison method, which found that the proposed method was better than conventional impedance control in terms of “Flexible”, “Natural”, “Kind” and “Affinity”.

This study proposes a new method of constructing the KANSEI (emotions, feelings and affective behaviors) engine using Hidden Markov Model (HMM). The KANSEI engine aims to generate human-like emotion transition. HMM is suitable for nondeterministic time-series data such as emotion transition of human. This paper describes three types of proposed engines using the HMM technique and compares for their performances. One of the engines was also compared with the conventional KANSEI engine using Petri-Net with Genetic Algorithm. The experiment showed that the proposed engine performed better than the conventional KANSEI engine.

We attempted to investigate the relationships between the relaxing effects of music and rhythm on the human body (fingerplethysmograms (or so called “pulses”) were adopted) using two EEG-and-HRV-based relaxation indicators. We focused on the synchronization between pulses and music, and the tendencies of pulse beats and the pulse-music tempo ratio (µ). We classified participants into three groups by analyzing the synchronization between pulses and music tempo. Furthermore, relaxation indicators were classified into four groups by the states of pulses and music. This paper also reports our analysis of the relationships between the pulse-music tempo ratio (µ) and the relaxation effect from the two indicators under the classification.

In this paper, the author aims to construct the environmental learning program and analyzes the map-making by the PC and examines its value or usability from the viewpoint of Kansei philosophy. First is a description of the design summary of the PC based map-making system. Next, the author explains the flow of the map-making program using this system. After that, the author verifies the practical effect of the learning on 40 sixth-grade children, analyzing questionnaires given to the children. According to this analysis, the children have developed awareness of real places and other people by the process of the PC based map-making. In the world of virtual “play”, they were able to develop interpretations of other people, understand real places deeply and come to notice changes in their own recognition.