Whereas the reception task is a promising application domain for social robots, knowledge is lacking about how to design the appropriate re-usable communication styles for a reception robot. This paper presents the use and evaluation of an iterative interaction-design (ID) method with which task- and person-oriented multi-modal communication styles have been designed for such a robot. First, we report on an evaluation study of the ID-method with Industrial Design students (N =13) who designed these two communication styles for a Pepper robot. This provided a set of distinct designs of the two styles, for which the differences in design parameters were in line with social science theory. The task-oriented style showed a more formal, shorter and less chatty communication. Second, we present findings from a Mechanical Turk study conducted to evaluate the perception of these style designs. Participants (N =301) were presented with videos showing the robot acting as a receptionist and were asked to rate their perception of the robot, the service experience and the orientation of the designs. Overall, the interaction with the robot was appreciated well. The robot with a person-oriented style was perceived to be more animate and likeable. Analysis showed that chit-chat was the main contributor to the perceived difference between the person-oriented and task-oriented styles. This is an important finding as it gives interaction designers a validated best-practice approach to make interaction style more or less personal.

Humans use several social cues, both verbal and nonverbal, to draw the attention of others. In this study we investigate whether similar behaviors can also be effectively used by a social robot for drawing attention. To this end, we setup a welcoming humanoid (Pepper) at the entrance of a university building. Its behaviors include one or a combination of behavioral modalities (i.e., a waving gesture, utterance and movement). These behaviors are triggered automatically based on people detection software which tracks passersby and monitors their head keypoints. Our findings imply that Pepper draws more attention when displaying a combination of modalities.

Drawing the attention of passersby is a basic task of a social robot to initiate an interaction in a public environment (e.g., shopping malls, museums or hospitals). Humans use several social cues, both verbal and nonverbal, to draw the attention of others. In this study, we investigate whether similar behaviors can also be effectively used by a social robot for drawing attention. To this end, we setup a humanoid robot (Pepper) to act as a welcoming robot at the entrance of a university building. The behaviors selected for Pepper include one or a combination of behavioral modalities (i.e., a waving gesture, utterance and movement). These behaviors are triggered automatically using the output of people detection software which tracks passersby and monitors their head keypoints (nose, eyes, and ears). The reactions of people toward Pepper are observed and recorded by means of an observation sheet. For several weeks, we deployed Pepper at the entrance with the aim of wearing off the novelty effect. In our final study, we collected data from several hundreds of passersby N=364 and conducted post-interviews with randomly selected ones N=28. Passersby noticed Pepper at the entrance and clearly recognized its role as a welcoming robot. In addition, Pepper was able to draw more attention when displaying a combination of behavioral modalities. However, passersby did not recall the robot utterance as they, for example, were unable to reproduce it or mistakenly claimed that the robot said something when it was only waving.