Research in robotics and human-robot interaction is becoming more and more mature. Additionally, more affordable social robots are being released commercially. Thus, industry is currently demanding ideas for viable commercial applications to situate social robots in public spaces and enhance customers experience. However, present literature in human-robot interaction does not provide a clear set of guidelines and a methodology to (i) identify commercial applications for robotic platforms able to position the users» needs at the centre of the discussion and (ii) ensure the creation of a positive user experience. With this paper we propose to fill this gap by providing a methodology for the design of robotic applications including these desired features, suitable for integration by researchers, industry, business and government organisations. As we will show in this paper, we successfully employed this methodology for an exploratory field study involving the trial implementation of a commercially available, social humanoid robot at an airport.

Robots interacting with humans in public spaces often need to collect users' private information in order to provide the required services. Current privacy legislation in major jurisdictions requires organisations to disclose information about their data collection process and obtain user's consent prior to collecting privacy sensitive information. In this study, we consider a privacy-sensitive design of a data collection system for face identification. We deployed a face enrolment system on a humanoid robot with human-like gesturing and speech. We compared it with an equivalent system, in terms of capability and interactive process, on a screen-based interactive kiosk. In our previous contribution, we investigated the effects that embodiment has on users' privacy considerations. We found that an embodied humanoid robot is capable of collecting more private information from users in comparison to a disembodied interactive kiosk. However, this effect was statistically significant only when the two compared systems were using a transparent interface, i.e. an interface communicating to users the privacy policies for data processing and storage. Thus, in this work, we aim to further investigate the effects of transparency on users' privacy considerations and their experience with robot applications. We found that when comparing a non-transparent vs. transparent interface within the same system (i.e. on an embodied robot or on a disembodied kiosk) transparency does not lead to significant effects on users' privacy considerations. However, we found that transparency leads to a significantly better user experience for both systems. Therefore, our overall analyses suggest that both the interactive robot and the interactive kiosk are capable of enhancing the user experience by providing transparent information to users, which is required by privacy legislation. However, an interactive kiosk providing transparent information elicits significantly more privacy concerns in users as compared to the robot supplying the very same transparent information. This exploratory study provides conclusions that provide valuable insights for designing robot applications dealing with users privacy and it discusses the related legal implications, concluding with recommendations for privacy policymakers.

Nowadays, robots are gradually appearing in public spaces such as libraries, train stations, airports and shopping centres. Only a limited percentage of research literature explores robot applications in public spaces. Studying robot applications in the wild is particularly important for designing commercially viable applications able to meet a specific goal. Therefore, in this paper we conduct an experiment to test a robot application in a shopping centre, aiming to provide results relevant for today's technological capability and market. We compared the performance of a robot and a human in promoting food samples in a shopping centre, a well known commercial application, and then analysed the effects of the type of engagement used to achieve this goal. Our results show that the robot is able to engage customers similarly to a human as expected. However unexpectedly, while an actively engaging human was able to perform better than a passively engaging human, we found the opposite effect for the robot. In this paper we investigate this phenomenon, with possible explanation ready to be explored and tested in subsequent research.

This paper investigates the problem of how humans understand and control human-robot collaborative action and how to build natural interactions during human-robot collaborative action. We use a `pick and place' experiment to study collaborative activities between a human and a robot. The results show that even if human participants had a good understanding of the maximum reachability of the robot, they consistently take a surprisingly long time to help and assist the robot when a target object is out of its reach. We implemented a number of social cues in the experiment, analysed their effects in order to identify the role they could play to improve the fluency of human-robot collaboration. The experimental results showed that when the robot uses head movements, two hands or a gesture to indicate non-reachability, people react in a more natural way to assist the robot.

The aim of the movie is to highlight some of the key challenges facing social robots in the wild. The opening scene shows a PR2 leaving a research laboratory venturing into the real world alone in search of meaning. Each subsequent scene in the movie raises important research questions highlighting problems that need to be addressed in the field of social service robotics. When will robots wander around buildings unsupervised? How will they navigate and localize with glass walls: this research problem is exposed when a robot finds itself having to move around a real building.

Pointing is a typical means of directing a human's attention to a specific object or event. Robot pointing behaviours that direct the attention of humans are critical for human-robot interaction, communication and collaboration. In this paper, we describe an experiment undertaken to investigate human comprehension of a humanoid robot's pointing behaviour. We programmed a NAO robot to point to markers on a large screen and asked untrained human subjects to identify the target of the robots pointing gesture. We found that humans are able to identify robot pointing gestures. Human subjects achieved higher levels of comprehension when the robot pointed at objects closer to the gesturing arm and when they stood behind the robot. In addition, we found that subjects performance improved with each assessment task. These new results can be used to guide the design of effective robot pointing behaviours that enable more effective robot to human communication and improve human-robot collaborative performance.