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In an experiment we manipulated a robot's voice in two ways: First, we varied robot gender; second, we equipped the robot with a human-like or a robot-like synthesized voice. Moreover, we took into account user gender and tested effects of these factors on human-robot acceptance, psychological closeness and psychological anthropomorphism. When participants formed an impression of a same-gender robot, the robot was perceived more positively. Participants also felt more psychological closeness to the same-gender robot. Similarly, the same-gender robot was anthropomorphized more strongly, but only when it utilized a human-like voice. Results indicate that a projection mechanism could underlie these effects.

Regarding the future usage of social robots in workplace scenarios, we addressed the question of potential mere robotic presence effects on human performance. Applying the experimental social facilitation paradigm in social robotics, we compared task performance of 106 participants on easy and complex cognitive and motoric tasks across three presence groups (alone vs. human present vs. robot present). Results revealed significant evidence for the predicted social facilitation effects for both human and robotic presence compared to an alone condition. Implications of these findings are discussed with regard to the consideration of the interaction of robotic presence and task difficulty in modeling robotic assistance systems.

A recent theoretical framework on anthropomorphism emphasizes the role of elicited agent knowledge in anthropomorphic inferences about nonhuman entities. According to the Three-Factor Model of psychological Anthropomorphism, people use anthropocentric knowledge structures when judging unfamiliar objects (e.g., robots). In the present research, our goal was to manipulate the accessibility of such elicited agent knowledge by varying features of a robot's voice: Specifically, we examined effects of vocal cues that reflected both gender of robot (i.e., a male vs. female voice) and voice type (i.e., a human-like vs. robot-like voice). This was done to test the impact of these vocal features on anthropomorphic inferences about the robot and on human-robot interaction (HRI) acceptance. Our results demonstrate that a robot's vocal cues clearly influence subsequent judgments of the robot and particularly so, when participant gender taken into account. Implications of our research for robotics will be discussed.

A robot's physical appearance is the most visible and most easily accessible information about its capabilities. The objective of the experiment presented in this paper is to bring insights into the evaluation of a robot's aesthetic design with regard to its social capabilities. Specifically, participants evaluated four human-like and four highly anthropomorphic robots regarding their aesthetic design, specific capabilities, and human-likeness. The robots varied in the quality of the industrial design: two of the human-like as well as two of the anthropomorphic robots have obviously been professionally designed while the others appear less professionally (i.e., rather unsophisticated) designed. The findings demonstrate that participants judged sophisticated designed robots to possess significantly more social capabilities (e.g., honesty, intelligence, emotionality). Human-likeness of the different robots did not have any significant effects on the attribution of social capabilities.

In this paper, we present a first step towards a typology of relevant signals and cues in human-robot interaction (HRI). In human as well as in animal communication systems, signals and cues play an important role for senders and receivers of such signs. In our typology, we systematically distinguish between a robot's signals and cues which are either designed to be human-like or artificial to create meaningful information. Subsequently, developers and designers should be aware of which signs affect a user's judgements on social robots. For this reason, we first review several signals and cues that have already been successfully used in HRI with regard to our typology. Second, we discuss crucial human-like and artificial cues which have so far not been considered in the design of social robots - although they are highly likely to affect a user's judgement of social robots.

A robot's head is important both for directional sensors and, in human-directed robotics, as the single most visible interaction interface. However, designing a robot's head faces contradicting requirements when integrating powerful sensing with social expression. Furher, reactions of the general public show that current head designs often cause negative user reactions and distract from the functional capabilities. Therefore, this contribution presents a novel anthropomorphic robot head called "Flobi", which combines state-of-the-art sensing functionality with an exterior that elicits a sympathetic emotional response. It can display primary and secondary emotions in a human-like way, to enable intuitive human-robot-interaction. To facilitate further research on facial appearance, the exterior is fully modular and replaceable. While current state-of-the-art still requires trade-offs when integrating sensing and social expression, Flobi has been designed to enable service robotic applications, with high-resolution, wide-angle stereo vision, gyroscope motion compensation and stereo audio. For ease of integration, the head is self-contained, including 18 actuators, sensors and control boards, all in a human-head sized package.

We examined the effects of a robots' nonverbal response on evaluations of anthropomorphism and other dimensions (e.g., liking, closeness, pleasantness of human-robot interaction) in a case study. Our work both conceptually replicates and extends previous research: On the one hand, we replicated previous findings and generalized them to a different robot type, the iCat. On the other hand, our work extends existing research in that it includes a wider range of dependent variables, with a particular focus on perceptions of anthropomorphism. Taken together, most of our results support the experimental hypotheses for the dependent measures: That is, a robot that provided emotional feedback during the interaction was perceived to be superior to a robot that responded neutrally. Thus, our findings highlight the importance of the interplay of form and function in the attribution of humanness to robots.

This paper introduces the industrial design of the social robot `Flobi'. In total, three key concepts influenced the industrial design: First, the robot head of Flobi appears as a cartoon-like character and has a `hole-free' design without any visible conjunctions. Second, Flobi has dynamic features to display not only primary emotions, but also shame, a typical secondary emotion. Third, the structural design implements exchangeable modular parts. Through modular design, the underlying hardware is quickly accessible and the visual features of the robot (e.g., hairstyle, facial features) can be altered easily. A first study demonstrated the successful implementation of Flobi's dynamic features, whereas a second study demonstrates that the exchangeable hair modules influence gender-schematic perceptions of the robot.

Research on social robots is mainly comprised of research into algorithmic problems in order to expand a robot's capabilities to improve communication with human beings. Also, a large body of research concentrates on the appearance, i.e. aesthetic form of social robots. However, only little reference to their definition is made. In this paper we argue that form, function, and context have to be taken systematically into account in order to develop a model to help us understand social robots. Therefore, we address the questions: What is a social robot, what are the interdisciplinary research aspects of social robotics, and how are these different aspects interlinked? In order to present a comprehensive and concise overview of the various aspects we present a framework for a definition towards social robots.

This paper investigates the influence of visual appearance of social robots on judgments about their potential applications. 183 participants rated the appropriateness of thirteen categories of applications for twelve social robots in an online study. The ratings were based on videos displaying the appearance of the robot combined with basic information about the robots' general functions. The results confirmed the hypothesis that the visual appearance of robots is a significant predictor for the estimation of applications in the eye of the beholder. Furthermore, the ratings showed an attractiveness bias: robots being judged as more attractive by the users also received more positive evaluations (i.e., ldquolikingrdquo).

Theory of Mind (ToM) is not only a key capability for cognitive development but also for successful social interaction. In order for a robot to interact successfully with a human both interaction partners need to have an adequate representation of the other's actions. In this paper we address the question of how a robot's actions are perceived and represented in a human subject interacting with the robot and how this perception is influenced by the appearance of the robot. We present the preliminary results of an fMRI-study in which participants had to play a version of the classical Prisoners' Dilemma Game (PDG) against four opponents: a human partner (HP), an anthropomorphic robot (AR), a functional robot (FR), and a computer (CP). The PDG scenario enables to implicitly measure mentalizing or Theory of Mind (ToM) abilities, a technique commonly applied in functional imaging. As the responses of each game partner were randomized unknowingly to the participants, the attribution of intention or will to an opponent (i.e. HP, AR, FR or CP) was based purely on differences in the perception of shape and embodiment.

Anthropomorphism is one of the keys to understand the expectations people have about social robots. In this paper we address the question of how a robotpsilas actions are perceived and represented in a human subject interacting with the robot and how this perception is influenced only by the appearance of the robot. We present results of an interaction-study in which participants had to play a version of the classical Prisonerspsila Dilemma Game (PDG) against four opponents: a human partner (HP), an anthropomorphic robot (AR), a functional robot (FR), and a computer (CP). As the responses of each game partner were randomized unknowingly to the participants, the attribution of intention or will to an opponent (i.e. HP, AR, FR or CP) was based purely on differences in the perception of shape and embodiment. We hypothesize that the degree of human-likeness of the game partner will modulate what the people attribute to the opponents - the more human like the robot looks the more people attribute human-like qualities to the robot.

The paper introduces an online user study on applications for social robots with 127 participants. The potential users proposed 570 application scenarios based on the appearance and functionality of four robots presented (AIBO, BARTHOC, BIRON, iCat). The items were grouped into 13 categories which are interpreted and discussed by means of four dimensions: public vs. private use, intensity of interaction, complexity of interaction model, and functional vs. human-like appearance. The interpretation lead to three classes of applications for social robots according to the degree of social interaction: (1) Specialized Applications where the robot has to perform clearly defined tasks which are delegated by a user, (2) Public Applications which are directed to the communication with many users, and (3) Individual Applications with the need of a highly elaborated social model to maintain a variety of situations with few people.