Robot design often involves gendered choices that shape Human–Robot Interaction. Voice is a key channel through which gendering occurs, yet little is known about how it influences people’s mental images of robots. This study examines how ambiguous, feminine, and masculine voices affect physical robot design. Participants (N = 45) listened to robot voices (ambiguous, feminine, masculine), built a physical prototype, took part in an interview to explain their design process, and concluded by evaluating both the voice and the robot prototype they built. The findings show that although participants’ explicit ratings of the robots showed no differences across conditions, analyses of the physical prototypes and interview data revealed consistent patterns, suggesting that voice strongly shaped design choices. Specifically, we found that ambiguous voices led to less human-like forms and more hybrid human-machine-like and masculine forms, whereas masculine voices encouraged more human-like prototypes. The results suggest that starting robot design from voice, particularly ambiguous voices, helps reduce gendering and fosters more inclusive robots.

Voice interfaces come in many forms in Human-Computer Interaction (HCI), such as voice assistants and robots. These are often gendered, i.e. they sound masculine or feminine. Recently, there has been a surge in creating gender-ambiguous voices, aiming to make voice interfaces more inclusive and less prone to stereotyping. In this paper, we present the first systematic review of research on gender-ambiguous voices in HCI literature, with an in-depth analysis of 36 articles. We report on the definition and availability of gender-ambiguous voices, creation methods, user perception and evaluation techniques. We conclude with several concrete action points: clarifying key terminology and definitions for terms such as gender-ambiguous, gender-neutral, and non-binary; conducting an initial acoustic analysis of gender-ambiguous voices; taking initial steps toward standardising evaluation metrics for these voices; establishing an open-source repository of gender-ambiguous voices; and developing a framework for their creation and use. These recommendations provide important insights for fostering the development and adoption of inclusive voice technologies.

This hands-on workshop will explore the potential implementations of human-agent interaction and mental health, with a specific focus on virtual companions. To achieve this, we will be using design fiction to anticipate individual, societal, ethical, and cultural implications. In this workshop, we will together create design fiction stories that explore virtual companions and practical, ethical, and societal issues with their possible implementation in mental healthcare.

Drones will soon deliver packages to recipients in public spaces, where drones may encounter difficulties identifying safe drop-off locations. Such uncertainties can reduce trust and raise safety concerns. This augmented reality study investigates how recipients perceive being asked to guide the drone in uncertain situations using hand gestures, and to what extent they feel comfortable with different levels of involvement. Results show that participants preferred a basic level of involvement, which received higher trust and usability scores than either no or high involvement. We recommend involving recipients in the final stage of delivery to not only support drone operations but also improve recipient trust and clarity in uncertain conditions.

What if the future of assistive technology isn’t built in labs, but by our memories of science fiction? Departing from traditional design fiction approaches that rely on curated prompts, we asked non-expert designers to prototype low-fidelity assistive systems for planetary settlements based on their own remembered cultural references. Across two workshops (n = 21) and a group interview (n = 5), participants prepared prototypes. Reflexive thematic analysis of their designs revealed five core themes: cultural templates as design scaffolds, speculative mobility logics, affective support, ethical concerns around system autonomy, and adaptive technologies responsive to alien conditions. These findings suggest that science fiction serves as aesthetic inspiration and an embedded framework. We argue that cultural memory can surface user expectations of assistive agents, informing the design of future human-agent interactions.

TRUST in human-robot interactions (HRI) is essential for effective collaboration and user acceptance of robotic systems. However, trust can be challenged by conflicting goals between the user and the system, such as in the context of proxemics when a robot invades a human’s personal space. As robotic systems increasingly adapt their actions autonomously, intelligent conflict resolution is necessary to not undermine humans’ trust in the robot’s decisions due to a decreased sense of control and understanding. Therefore, this study investigates how humans can be involved and supported during automated conflict resolution to maintain their trust by exploring different degrees of explainability and automation. We applied a within-subjects experimental design, where 20 participants experienced four conditions varying in levels of automation and explainability during a simulated conflict between their need to preserve their personal space and the robot’s requirement to approach to perform a task. We measured the participants’ trust through questionnaires and interviews. Our findings suggest that trust is positively influenced by the level of control users have during conflict situations. However, the robot’s explanations did not significantly impact trust. Our insights highlight the need for conflict management strategies in HRI that balance automation with user involvement to foster greater levels of trust when collaborating with robots.

When a robot is developed, it usually has well-defined physical and occupational characteristics that are often gendered. This can influence the Human-Robot Interaction (HRI) experience and also risks fostering harmful gender stereotypes in society. One factor contributing to gender attribution to robots is their voice, which can be manipulated and changed to fit any need. Thanks to the recent development of gender-ambiguous voices, this provides an interesting research space to investigate if this modality can reduce robot gendering. Our research investigates whether these voices influence how people picture a robot in different occupational contexts. We asked participants to sketch a robot after listening to either a gender-ambiguous voice presenting a neutral, feminine, masculine scenario, a female voice presenting a feminine scenario, or a male voice presenting a masculine scenario. Results indicate that an ambiguous voice influences gender associations, as participants were less likely to assign a gender to their sketched robots when exposed to an ambiguous voice, compared to a male or female voice. This finding highlights the potential of deploying ambiguous voices to reduce gender biases in HRI, even in stereotypically gendered roles, such as security guards or secretaries.

The deployment of autonomous robots in human environments requires an understanding of social interactions and the factors that influence them. Human-robot proxemics is an important factor that impacts interactions, and modeling personalized proxemic behavior has always been a challenge, as it depends on multiple user attributes, including gender, age, and height. In this paper, we propose a novel approach that uses rubber-sheet transformation models to represent human-robot proxemics. We do this by collecting human-robot interpersonal distance data from 20 users and model it with respect to their height, age, gender, and the angle at which the robot approaches. We present an evaluation of the model, and the outcome of our results, which show a promising approximation of proxemic distances based on different user attributes. Finally, we provide a coefficient table for rubber-sheet models to lay the foundation for personalized human-robot proxemics and outline future research directions.

The potential for drones to engage with people and find applications in social contexts is often constrained by their mechanical design, leading to concerns and negative associations that significantly affect people’s acceptance of drones in their personal space. In this study, we explore how social cues can impact the spatial dynamic of Human–Drone Interaction. Within a fully immersive virtual environment, 25 participants engaged with and navigated around a drone that communicated several facial emotions on a digital display such as Joy, Sadness and Anger, and enacted distinct “gaze” behaviors (i.e., following participants or averting its gaze). Our results indicate that participants responded to the drone’s gaze in a manner akin to what is reported during human interaction: maintaining a greater distance when the drone established eye contact and instinctively getting closer when it averted its gaze. A more granular analysis revealed that participants who lacked prior familiarity with drones or possessed neutral to positive attitudes toward them demonstrated a higher sensitivity to the drone’s digital facial emotions. This finding highlights the potential for leveraging social cues to facilitate the integration of drones into various human-centric environments and tailor their design and behavior to suit specific individuals and situations.

Tables are a ubiquitous piece of furniture, a familiar sight in most environments from intimate to public. The dimensions of social interplay surrounding every single table are profoundly complex. In our project, we lift the importance of the neglected space under the table through the playful development of a tangible prototype. We approached this by a design remake of the Mediated Body: a wearable prototype encouraging touch between strangers using the conductivity of the skin. Instead, we leverage the familiarity of tables as a means to encourage playful explorations of bare-skin touch. We report in visual and textual form on the emerging design knowledge throughout our design process, including first-person narratives by the designers. We contribute with (1) a series of counterfactual table artifacts inspired by the Mediated Body; (2) a sequence of participant studies analysed through reflexive thematic analysis and summarised into the notion of “an odd invitation” as a new lens for homo explorens; and (3) an appeal to the importance of design remakes for research-through-design.

In this paper, we motivate and introduce a novel concept in using a tangible prototype with the intention of creating a new type of relationship between a plant and its owner. The HoneyPot uses ambient light to create a cozy vibe and atmosphere to evoke pleasant emotions as an attempt to reduce isolation issues in adolescent populations. By remotely connecting two pots, users can also stay socially connected to each other despite the physical distances separating them. After explaining our iterative design process and testing of the product, we discuss our results and the findings of four main themes regarding the usage of HoneyPot.

This paper introduces the ZenStem, an interactive prototype that facilitates meditation by visually guiding a user’s breathing pattern. The ZenStem links users’ breathing and heart rate to the irrigation of an indoor plant, as it will water the plant so long as the user can maintain a meditative state. Upon feedback from a pulse-sensing armband that the user’s heart rate has risen, it will initialize its light-based breathing guide to help the user re-enter their meditative state. We describe the ideation and prototyping process of the ZenStem, followed by the initial impressions gained from pilot evaluations with potential users. Based on impressions pertaining to the appearance and functionality of the ZenStem, we end by proposing future research directions and design suggestions.

The utilization of extra-robotic limbs to regain and extend motor abilities poses challenges. Nonetheless, the evidence suggesting the extension of these abilities without functional interference holds promise for the advancement of extra-robotic fingers or limbs. To gain insights into design improvement from diverse perspectives, we conducted a focus group study utilizing a prototype supernumerary robotic finger (SRF). The main purpose of the study is to gain knowledge on the current prototype, and then use the outcomes in a future co-designing process of SRF having the potential to be used as an assistive and augmented tool. Fifteen healthy subjects with an engineering background participated in the current study. We analyzed the collected data through a thematic analysis process to generate key design recommendations. These recommendations contain suggestions for designing for personal and social acceptance, adaptability, and multi-modal interaction. The results serve as a subset of future subsequent studies to be carried out with other stakeholders of the prototype, including patients, clinicians, and designers. Future work focuses on using the recommendations in a co-design process to inform the prototyping of SRF technologies supporting and extending motor abilities in upper limbs.

There are current methodological and epistemological gaps and struggles between Human-Drone Interaction research and the field of design. We highlight five HDI design considerations and suggest a non-exhaustive list of design methods to approach them. We present an appeal to a more diverse and inclusive study of drones where current research can be balanced with a deeply qualitative and critical understanding of these flying robots through embracing design knowledge.

Assistive technologies are vital for individuals with physical limitations, and understanding the diverse impact of physical pain is crucial for designing effective assistive robotic solutions. Through an iterative study, we aim to develop comprehensive design recommendations that cover personalization, concealment, compatibility, ease of use, preventive measures, skin-friendliness, affordability, adaptability, and multimodal features. These recommendations prioritize user experience and acceptance, ultimately contributing to innovative and user-centric assistive robotic technologies.

Augmented reality (AR) technologies are today more frequently being introduced to Human-Robot Interaction (HRI) to mediate the interaction between human and robot. Indeed, better technical support and improved framework integration allow the design and study of novel scenarios augmenting interaction with AR. While some literature reviews have been published, so far no classifications have been devised for the role of AR in HRI. AR constitutes a vast field of research in HCI, and as it is picking up in HRI, it is timely to articulate the current knowledge and information about the functionalities of AR in HRI. Here we propose a multidimensional taxonomy for AR in HRI that distinguishes the type of perception augmentation, the functional role of AR, and the augmentation artifact type. We place sample publications within the taxonomy to demonstrate its utility. Lastly, we derive from the taxonomy some research gaps in current AR-for-HRI research and provide suggestions for exploration beyond the current state-of-the-art.

With the rising use of Augmented Reality (AR) technologies in Human-Robot Interaction (HRI), it is crucial that HRI research examines the role of AR in HRI to better define AR-HRI systems and identify potential areas for future research. A taxonomy for AR in HRI has recently been proposed for the field. However, it was limited to the definition of the framework, and exemplifying its use was missing. In this paper, we perform a demonstration of how the aforementioned taxonomy of AR in HRI can be used to analyse an existing AR-HRI system and come up with questions for alternative ways AR-HRI could be designed and further extended.

Human-drone interaction is a growing topic of interest within HCI research. Researchers propose many innovative concepts for drone applications, but much of this research does not incorporate knowledge on existing applications already adopted by professionals. This limits the validity of said research. To address this limitation, we present our findings from an in-depth interview study with 10 professional drone pilots. Our participants were armed with significant experience and qualifications – pertinent to both drone operations and a set of applications covering diverse industries. Our findings have resulted in design recommendations that should inform both ends and means of human-drone interaction research. These include, but are not limited to: safety-related protocols, insights from domain-specific use cases, and relevant practices outside of hands-on flight.

Domestic robotic entities are on the rise, out of which, domestic drones are taking place in our society as one of the upcoming interactive technologies that we will see in our daily lives. In this paper, we scope for research literature that addresses the use of domestic drones within our environments to understand the current usage as well as identifying future research directions. After performing a search based collection of relevant papers in the ACM digital library (N=61 papers), we analysed the drone's application areas, their interaction modalities, the target users, and the level of autonomy of the proposed systems. The results show interesting trends in the modalities of interaction (visual projection combined with hand/foot gestures) as well as important research gaps such as child-drone interaction, and the use of drones for healthcare or education, given that currently most use cases for domestic drones are generic in nature.

The design space of social drones, where autonomous flyers operate in close proximity to human users or bystanders, is distinct from use cases involving a remote human operator and/or an uninhabited environment; and warrants foregrounding human-centered design concerns. Recently, research on social drones has followed a trend of rapid growth. This paper consolidates the current state of the art in human-centered design knowledge about social drones through a review of relevant studies, scaffolded by a descriptive framework of design knowledge creation. Our analysis identified three high-level themes that sketch out knowledge clusters in the literature, and twelve design concerns which unpack how various dimensions of drone aesthetics and behavior relate to pertinent human responses. These results have the potential to inform and expedite future research and practice, by supporting readers in defining and situating their future contributions. The materials and results of our analysis are also published in an open online repository that intends to serve as a living hub for a community of researchers and designers working with social drones.

Depictions of robots and AIs in popular science fiction movies and shows have the potential to showcase visions of Human-Robot Interaction (HRI) to the general public and computer science researchers alike. In contrast, studies on the referral, usage, and appropriation of these portrayals by computer scientists in their research publications is an academic void at present. However, such investigations are critical to better understand the potential utility and latent shortcomings of science fiction robots for future HRI research, innovation, and education. To address this research gap, this study investigates the overall presence, nature, and frequency of referrals of 18 popular science fiction robots in the Association for Computing Machinery (ACM) Digital Library. These robots were either portrayed in various movies and subsequently inducted into the Robot Hall of Fame, created by Carnegie Mellon University in 2003, or were top-ranked in a user-curated Internet Movie Database (IMDB) list. To do so, we performed full-text search and retrieval queries of all 18 robots in the ACM Digital Library. In total, we identified 121 relevant mentions, across 102 individual publications, in a time span from 1973 to 2017. These 121 mentions were then qualitatively analysed to determine the nature of the robot mentions. Our results indicate that the robot attributes of voice or dialogue were emerging as a popularly mentioned element. In addition, we find that research papers of philosophical nature mention sci-fi robots more frequently than papers of technical or theoretical nature. We also observe that the dystopian element of science fiction is under-utilised, with the majority of robot mentions exhibiting neutral or utopian characteristics. In conclusion, we speculate on our results and present possible avenues of future HRI research on the topic.

Through a user-centered design approach, we explored how a robotic agent can be designed to support students practicing Swedish at home and in class. The process started with design workshops and user-feedback that helped to create a cardboard prototype of a language companion robotic agent. The prototype was used in semi-structured interviews where eight participants created scenarios on how to use the agent, both at home and in a classroom. Our result presents design impressions for a language companion robotic agent categorized into embodiment, emotions, dialogue, and personality. The findings also suggest tasks for the agent at home and in a classroom.

In the domain of robotic tutors, personalised tutoring has started to receive scientists' attention, but is still relatively underexplored. Previous work using reinforcement learning (RL) has addressed personalised tutoring from the perspective of affective policy learning. However, little is known about the effects of robot behaviour personalisation on user's task performance. Moreover, it is also unclear if and when personalisation may be more beneficial than a robot that adapts to its users and the context of the interaction without personalising its behaviour. In this paper we build on previous work on affective policy learning that used RL to learn what robot's supportive behaviours are preferred by users in an educational scenario. We build a RL framework for personalisation that allows a robot to select verbal supportive behaviours to maximise the user's task progress and positive reactions in a learning scenario where a Pepper robot acts as a tutor and helps people to learn how to solve grid-based logic puzzles. A between-subjects design user study showed that participants were more efficient at solving logic puzzles and preferred a robot that exhibits more varied behaviours compared with a robot that personalises its behaviour by converging on a specific one over time. We discuss insights on negative effects of personalisation and report lessons learned together with design implications for personalised robots.

In this paper, we investigate the applicability of deep learning methods to adapt and predict comfortable human-robot proxemics. Proposing a network architecture, we experiment with three different layer configurations, obtaining three different end-to-end trainable models. Using these, we compare their predictive performances on data obtained during a human-robot interaction study. We find that our long short-term memory based model outperforms a gated recurrent unit based model and a feed-forward model. Further, we demonstrate how the created model can be used to create customized comfort zones that can help create a personalized experience for individual users.

The process of managing one's daily intake of medication has been shown to be error-prone for a variety of reasons. In this paper, we explore, through a rapid prototyping approach, the design implications for a social robotic agent intended for dispensing medicine. The process started with initial interviews with medical experts to allow for a better understanding of the design space. Their input helped us realise a low-fidelity, animal-like, robotic prototype for pill-dispensing. We report initial impressions of the prototype from four pharmacists. Based on those findings, we present design implications categorised into:look and feel, social role, desired task, and the agent's presence in a home environment.

Most currently existing tools for cognitive memory therapy require physical interaction or at least the presence of another person. The goal of this paper is to investigate whether a social robot might be an acceptable solution for a more inclusive therapy for people with memory disorder and severe physical limitations. Applying a user-centered design approach, we conducted semi-structured interviews with five healthcare professionals; four medical doctors and a psychologist, in three iterations followed by a focus group activity. An analysis of the collected data suggests several implications for design with an emphasis on embodiment, social skills, interaction, and memory training exercises.

Recent research has focused on how to facilitate interaction between humans and robots, giving rise to the field of human robot interaction. A related research area is human-drone interaction (HDI), investigating how interaction between humans and drones can be expanded in novel and meaningful ways. In this work, we explore the use of drones as companions in a home environment. We present three consecutive studies addressing user requirements and design space of companion drones. Following a user-centered approach, the three stages include online questionnaire, design workshops, and simulated virtual reality (VR) home environment. Our results show that participants preferred the idea of a drone companion at home, particularly for tasks such as fetching items and cleaning. The participants were also positive towards a drone companion that featured anthropomorphic features.

The HAI conference is the premier discussion venue on the topic of Human Agent Interaction. In this paper we present our findings from the scientometric analysis of full papers from the HAI conference since its inception to date. We extracted various bibliometric measures and qualitatively coded our sample of 107 full papers over the 4 years of the conference. Our results show that the conference has not really grown rapidly and attracts papers from predominantly Asian Pacific regions. User studies were the common research methodology undertaken in HAI papers and humanoid robots are the popular agent of choice. Domains such as Education and Health were surprisingly underrepresented whereas communication was the focus of almost half of the papers. We also report on a mini comparison with the ICSR and IVA conference as a bench-marking strategy, which provides us with some reflections on how the HAI conference can be moved forward. In conclusion, we speculate on our findings and provide some insights to the organizers and steering committee of the HAI conference.

We present a human-centered designed social drone aiming to be used in a human crowd environment. Based on design studies and focus groups, we created a prototype of a social drone with a social shape, face and voice for human interaction. We used the prototype for a proxemic study, comparing the required distance from the drone humans could comfortably accept compared with what they would require for a nonsocial drone. The social shaped design with greeting voice added decreased the acceptable distance markedly, as did present or previous pet ownership, and maleness. We also explored the proximity sphere around humans with a social shaped drone based on a validation study with variation of lateral distance and heights. Both lateral distance and the higher height of 1.8 m compared to the lower height of 1.2 m decreased the required comfortable distance as it approached.

Science fiction media has had a long lasting influence on the progression of interactive technology, however recently contradictions are emerging in the development of the two disciplines. Therefore, in this exploratory position paper we report on the insights attained through a day long workshop amongst scientists and researchers on how the collaboration between science fiction and Human Computer Interaction (HCI) can be advanced. Discussions in the workshop focused on detailing the relationship between HCI and science fiction. In conclusion, as our main contribution an action plan and agenda is presented for facilitating deeper influences amongst the two disciplines.

Most existing colorblind aids help their users to distinguish and recognize colors but not compare them. We present HaptiColor, an assistive wristband that encodes discrete color information into spatiotemporal vibrations to support colorblind users to recognize and compare colors. We ran three experiments: the first found the optimal number and placement of motors around the wrist-worn prototype, and the second tested the optimal way to represent discrete points between the vibration motors. Results suggested that using three vibration motors and pulses of varying duration to encode proximity information in spatiotemporal patterns is the optimal solution. Finally, we evaluated the HaptiColor prototype and encodings with six colorblind participants. Our results show that the participants were able to easily understand the encodings and perform color comparison tasks accurately (94.4% to 100%).

Proper break taking during office work iss necessary to prevent musculoskeletal disorders and reduce the risk of heart disease.We present APOEW -an avatar for preventing continuous office work without taking breaks.APOEW is a system that uses a personalized robot avatar to encourage proper break behaviour during office work.The avatar signals the need for a break by stooping.The system was designed to be unobtrusive and blend well with the office environment.The avatars are customisable in order to enable users to design their work environment freely.We conducted a user study where we observed developers working in front of their computers next to the avatar.Preliminary results indicate it has no negative impact on the work environment and users are intrigued by the system.Moreover, a survey on attitude to our concept reveals interesting and positive feedback that will help to develop an APOEW system further.

We present a study involving 160 participants investigating the effect of associating professional status and ethnicity with an agent by manipulating its appearance, language, and level of education. We aim to discern perceptions of status and ethnicity with respect to participants' cultural background by inviting participants from two different cultural groups (Middle Eastern and Western) to take part in our study. Results revealed that participants' cultural background had a strong impact on their ratings of the agent and its message. However, neither the agent's portrayed status nor its ethnicity appeared to have an effect on participants' perceptions of the agent. We further found that participants from both cultural backgrounds holding a negative attitude towards robots in general tend to perceive the presented message by the agent more negatively. Middle Eastern participants had a more positive attitude towards robotic agents than Western participants, which might have been the main influence on their perception of the message presented by the agent. In addition, participants who identified the agent as a member of their own cultural group perceived the presented message more positively than those from the other cultural group. We discuss our results with an intention to inform design implications for agents in a cross-cultural context.

This work aims at bringing empirical knowledge on Human-Robot Interaction obtained from user studies closer to being integrated into the capabilities of robots currently available on the market. The Takagi-Sugeno-Kang method and results of a user study conducted with thirty two participants were used to build a fuzzy data-based model for Human-Robot Proxemics. The experiment investigated the effect of robot approach distance and angle on perceived human comfort. The proposed model, consisting of a set of rules, fuzzy sets and their parameters, can be used by the robotics community thanks to their formal form. It can also be directly translated into natural language statements. Results of model cross-validation are reported.

In this paper we present a study that investigates human-robot interpersonal distances and the influence of posture, either sitting or standing on the interpersonal distances. The study is based on a human approaching a robot and a robot approaching a human, in which the human/robot maintain either a sitting or standing posture while being approached. We collected and analysed data from twenty-two participants and the results revealed that robot posture has a significant impact on the interpersonal distances in human-robot interactions. Previous interactions with a robot, and lower negative attitudes towards robots also impacted interpersonal distances. Although the effects of gender, height and age did not yield significant results, we discuss their influence on the interpersonal distances between humans and robots and how they are of interest for future research. We present design implications for human-robot interaction research and humanoid robot design.

In this article, we present a novel application domain for human computation, specifically for crowdsourcing, which can help in understanding particle-tracking problems. Through an interdisciplinary inquiry, we built a crowdsourcing system designed to detect tracer particles in industrial tomographic images, and applied it to the problem of bulk solid flow in silos. As images from silo-sensing systems cannot be adequately analyzed using the currently available computational methods, human intelligence is required. However, limited availability of experts, as well as their high cost, motivates employing additional nonexperts. We report on the results of a study that assesses the task completion time and accuracy of employing nonexpert workers to process large datasets of images in order to generate data for bulk flow research. We prove the feasibility of this approach by comparing results from a user study with data generated from a computational algorithm. The study shows that the crowd is more scalable and more economical than an automatic solution. The system can help analyze and understand the physics of flow phenomena to better inform the future design of silos, and is generalized enough to be applicable to other domains.

In this paper the nexus between fictional and real robots in Human Robot Interaction (HRI) is explored. We claim that design guidelines for HRI must not be borrowed from fiction blindly, as contradictions between the two may emerge with respect to what is desired by the human user. To understand human perception of robots appearing in movies we analyse viewing statistics and qualitative comments of a set of YouTube videos comprising of fictional and real robots. Analysis of the viewing statistics showed that real robots are more popular. Furthermore, analysis of the comments showed that two real robots (Nao and Shakey) generated significantly more positive comments and significantly more attributions of usage in human society as compared to the two fictional robots (AstroBoy and HAL9000). Based on the sample of robots considered in this research, our results reveal that contrary to expectation humans are more exposed to real robots and are more preferred, and we conclude by reasserting the contradiction that emerges between real and fictional robots.

In this paper we introduce and evaluate a concept of a drone agent that can support us to keep the environment clean. The drone has four main functions: (1) find a waste item, (2) persuade the user to pick up the item, (3) lead the user to the nearest trash bin, (4) communicate with the user when the job is done. We prototyped three types of persuasion effects with the drone (Visual, Audio, and Visual+Audio) and evaluated them through an online study with eighty two participants. The results reveal that interest in the drone technology varied significantly between developed and developing countries, with individuals in developing countries having higher ratings for drone related persuasion, compliance, pleasantness and sensibility; gender differences also emerged. Finally, evaluation results led to many design recommendations that will increase the functionality and attractiveness and usage potential of the proposed technology.

Advances in display technologies could soon make wearable mid-air displays---devices that present dynamic images floating in mid-air relative to a mobile user---available. Such devices may enable new input and output modalities compared to current mobile devices, and seamlessly offer information on the go. This paper presents a functional prototype for the purpose of understanding these modalities in more detail, including suitable applications and device placement. We first collected results from an online survey identified map navigation as one of the most desirable applications and suggested placement preferences. Based on these rankings, we built a wearable mid-air display mockup consisting of mobile phone, pico projector, and a holder frame, mountable in two alternative ways: wrist and chest. We then designed an experiment, asking participants to navigate different urban routes using map navigation displayed in mid-air. For map navigation, participants ranked wrist-mount safer than chest-mount. The experiment results validate the use of a wearable mid-air display for map navigation. Based on our online survey and experiment, we offer insights and recommendations for the design of wearable mid-air displays.

Empathy plays an important role in the interaction between humans and robots. The contagious effect of yawning is moderated by the degree of social closeness and empathy. We propose to analyse the contagion of yawns as an indicator for empathy. We conducted pilot studies to test different experimental procedures for this purpose. We hope to be able to report on experimental results in the near future.

We present an Augmented Reality (AR) system where we immerse the user's whole body in the virtual scene using a motion capturing (MoCap) suit. The goal is to allow for seamless interaction with the virtual content within the AR environment. We describe an evaluation study of a prototype application featuring an interactive scenario with a virtual agent. The scenario contains two conditions: in one, the agent has access to the full tracking data of the MoCap suit and therefore is aware of the exact actions of the user, while in the second condition, the agent does not get this information. We then report and discuss the differences we were able to detect regarding the users' perception of the interaction with the agent and give future research directions.

In social robotics, the behavior of humanoid robots is intended to be designed in a way that they behave in a human-like manner and serve as natural interaction partners for human users. Several aspects of human behavior such as speech, gestures, eye-gaze as well as the personal and social background of the user need therefore to be considered. In this paper, we investigate interpersonal distance as a behavioral aspect that varies with the cultural background of the user. We present two studies that explore whether users of different cultures (Arabs and Germans) expect robots to behave similar to their own cultural background. The results of the first study reveal that Arabs and Germans have different expectations on the interpersonal distance between themselves and robots in a static setting. In the second study, we use the results of the first study to investigate the users' reactions on robots using the observed interpersonal distances themselves. Although the data of this dynamic setting is not conclusive, it suggests that users prefer robots that show behavior that has been observed for their own cultural background before.

We present the design of an educational treasure hunt game that uses mobile Augmented Reality (AR) and adaptive virtual gardens to raise awareness on energy consumption ways. Within the game, AR is used to present 3D content that allows for visually understanding the energy consumption problems and their solutions. In addition, the players' performances are given in a form of a visual feedback as dynamic virtual gardens that change from poor to good status. Initial tests show that the presented game is highly appealing to players and motivated them to be aware of the presented problem using AR technologies and the visual effects of their virtual garden's health. Future work will focus on evaluating the learnability and engagement of players.

Interaction with personalized data on a large public display represents a sensitive scenario: first, users expose the fact of interaction in public; and, personalized data may be private. In this work we investigate how interaction design can support the user in such a scenario. Through experimentation, we compare three interaction techniques: direct, bodily, and mobile-based. We report on the users' preferences with the presented techniques at different interaction phases (identification, navigation, and collecting results). We analyze how user preferences in the personalized display scenario are similar or different to other scenarios, such as interaction with physical objects or non-personalized public displays. The analysis is summarized in a form of design recommendations that should be considered when designing for interaction with personalized public displays.