To prevent elderly people from being socially isolated, encouraging their self-disclosure takes an important role. We discuss a use case of social robots in which they are deployed as mediators for humans that intermediate remote communication between elderly people and their family members or friends. The goal of this article is to present a design guideline for such social mediator robots based on results obtained from two studies in which a total of 741 elderly people participated. In study 1, we explored topics in dialogues and found that a social mediator robot could well encourage the self-disclosure of the elderly people, particularly in topics of which they usually feel resistance in talking to others (e.g., loss experiences). Thus, we confirmed the feasibility of the social mediator robot. Study 2 pursued the effective personality traits of the social mediator robot. We re-investigated a well-studied research question of matching robot personality to the user. The results provided more detailed knowledge as to similarity-attraction/repulsion than had been reported previously. Finally, design recommendations were discussed by considering the personality traits of the elderly users as well.

The video describes the novel concept of “culturally competent robotics”, which is the main focus of the project CARESSES (Culturally-Aware Robots and Environmental Sensor Systems for Elderly Support). CARESSES a multidisciplinary project whose goal is to design the first socially assistive robots that can adapt to the culture of the older people they are taking care of. Socially assistive robots are required to help the users in many ways including reminding them to take their medication, encouraging them to keep active, helping them keep in touch with family and friends. The video describes a new generation of robots that will perform their actions with attention to the older person's customs, cultural practices and individual preferences.

For generating interactive behavior of robot to build a long-term relationship between humans and robots, we focus on the difference in familiarity of the human behaviors during conversation. It is difficult to extract interaction motion features correlated to such familiarity as a model in manual. Therefore, we use a machine learning technique: convolution neural network to learn and generate interaction behavior with different familiarity. In the evaluation experiment, we generated interaction behavior using a convolution neural network, which learned from the behaviors of friendship and unknown relationship, who have high and low familiarity respectively. We evaluated how much such interaction behavior affect the human impression by questionnaire survey.

The social isolation of elderly people is becoming a big problem. To solve this problem, social robots have been regarded as suitable interfaces to support these elderly people to communicate with others (e.g. family members). In such robot-mediated communication, it can be expected to elicit self-disclosure from elderly people. In this study, we explored the requirements for intermediately robots to encourage elderly people's self-disclosure. The results suggested that an intermediately robot with human-like behavior can encourage elderly people's self-disclosure about experiences of loss (e.g. health and financial issues). Additionally, we found that warmth and competence judgments to the robot are correlated to elderly people's self-disclosure. From these results, it was suggested that the influence on the self-disclosure of the intermediately robot are strengthened by being regarded as a social other.

Cultural competence is a well known requirement for an effective healthcare, widely investigated in the nursing literature. We claim that personal assistive robots should likewise be culturally competent, aware of general cultural characteristics and of the different forms they take in different individuals, and sensitive to cultural differences while perceiving, reasoning, and acting. Drawing inspiration from existing guidelines for culturally competent healthcare and the state-of-the-art in culturally competent robotics, we identify the key robot capabilities which enable culturally competent behaviours and discuss methodologies for their development and evaluation.

In this article, we aim to discover the important factors for determining the psychological safety of humanoids and to develop a new psychological scale to measure the degree of safety quantitatively. To discover the factors that determine the psychological safety of humanoids from an ordinary person's perspective, we studied 919 Japanese, who observed movies of 11 humanoids and then freely described their impressions about what the safety of each humanoid was for them. Five psychologists categorized all of the obtained descriptions into several categories and then used the categories to compose a new psychological scale. Then, 2,624 different Japanese evaluated the same 11 humanoids using the new scale. Factor analysis on the obtained quantitative data revealed six factors of psychological safety: Performance, Humanness, Acceptance, Harmlessness, Toughness, and Agency. Additional analysis revealed that Performance, Acceptance, Harmlessness, and Toughness were the most important factors for determining the psychological safety of general humanoids. The usability of the new scale is discussed.

This study identifies the basic general perspectives that ordinary people use to evaluate humanoids (Study 1). In addition, it develops a new psychological scale to quantify general impressions regarding humanoids based on these basic perspectives (Study 2). In Study 1, to discover the basic perspectives toward humanoids, we used 11 humanoids and collected data from 919 Japanese people ranging from teenagers to people in their 70s in three big cities. We asked people to describe their impressions in free text about the robots. Five psychologists analyzed the qualitative data to categorize all the descriptions into several categories. Then, we made the items based on the obtained descriptions to construct a new psychological scale for evaluating general impressions regarding humanoids. In Study 2, we asked 2,624 Japanese who did not participate in Study 1 to evaluate 11 humanoids on the developed scale. Factor analysis showed that nine factors should be used for evaluating the general impressions regarding humanoids: Familiarity, Repulsion, Performance, Utility, Motion, Sound, Voice, Humanness, and Entitativity. The factor structure is clear and its reliability as a psychological scale is satisfactorily high. Finally, we discuss the usability of the new scale.

The aim of this study was to compare a robot designed using a virtual reality (VR) system (termed VR robot) with a real robot by using a psychological evaluation to investigate whether the VR robot can be used in the same manner as a real robot. To make the direct comparison between a VR and real robots possible, the same designed robots in both VR and real are used in the experiment. For evaluating the robots on a psychological basis, we focused on six basic dimensions (Utility, Clumsiness of motion, Possibility of communication, Controllability, Vulnerability, and Objective hardness) that ordinary people generally use to perceive robots. Sixty-one participants observed and evaluated a real and VR humanoid robots using a psychological scale. Results show that the real robot was evaluated to have higher scores for Utility, Possibility of communication, and Objective hardness and lower ones for Controllability as compared to a VR robot. The Vulnerability scores of the real robot and the VR robot were not significantly different. The usability of a VR robot is discussed in the paper.

In this study we explored basic dimensions used to perceive humanoid robots and developed a scale to evaluate perception of humanoid robots, PERNOD. Previous studies of perception of humanoid robots used psychological scales created for interpersonal perception between humans. This study clarified the basic dimensions of perception of humanoid robots and developed PERNOD by means of psychological methodology. The results revealed six basic dimensions of perception of humanoid robots: Utility, Clumsiness of motion, Possibility of communication, Controllability, Vulnerability, and Objective hardness. The 6 dimensions of PERNOD were originally developed for humanoid robots. Thus, these dimensions represent the organization of knowledge used in the recognition of humanoid robots. Usability of PERNOD was discussed.