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In health care and public health practice, it is critical to settings control practices that are critical to reducing the transmission of infections through cross-contamination. To provide protection from cross-contamination, use and throw gloves are routinely used. However, single-time use and inconsistent sanitization of used gloves remain a large problem and elevate the risk of catching viruses, germs, pathogens, and contaminants. The study reports reusable self-sanitizing gloves via 3D-printing and common hand molding methods. The major contribution is frequent self-sanitization of gloves without any manual intervention. The elastomeric material is used for fabricating gloves and continuous channels are embedded within the elastomeric material that runs through the entire glove surface, covering the front, back, and fingers. Elastomeric material allows the engagement of fingers for gripping objects. While the embedded channel is provided with uniformly spaced openings to eject the sanitizing solution. The glove surface is textured with a porous morphology that acts as mini and micro reservoirs for sterilizing solution ejected through embedded channel opening. The embedded channel is connected to a sanitizing solution storage tank. The incorporation of sanitizing solution storage tank enables its usage over a longer period. This uniquely constructed design of the gloves even assists in the effective sterilization of infected surface that comes in contact with the gloves. The gloves can be customized to improve comfortability by fabricating them from the 3D-printed mound developed based on the palm size of the user. The developed technology can be used by individuals working in hospitals, the transport sector, delivery units, schools, offices, industries, etc. We strongly believe that this technology will be highly useful in minimizing the risk of getting infected through cross-contamination and will help in maintaining hygienic as well as safe surroundings. This work was supported by the RRC-2-063-133 grant from the Qatar National Research Fund (a member of Qatar Foundation). Open Access funding was provided by the Qatar National Library.

Infectious diseases are responsible for an immense global burden of disease that impacts public health systems and economies worldwide. The rapid increase in the use of protective items has introduced an urge for their reuse and safe dumping to minimize the threat of disease transmission through cross-contamination. The existing disinfection processes are mostly powered with non-renewable energy sources and focus on single disinfecting technology that limits their installation to in-house applications and reduces the degree of disinfection, respectively. Thus there is a need to develop new strategies and innovations powered by renewable energy sources that enhance the degree of disinfection of daily-use objects and curtail the spread of the infection through cross-contamination. The present study reports a smart automatic technology called “REACTIV-FIT”. The technology is developed as an exercise bike with a disinfection chamber that efficiently kills viruses, bacteria, and other germs/pathogens. The current developed technology is equipped with three disinfecting protocols in one system. The system is powered by renewable solar energy and utilizes the mechanical energy during exercise into electrical energy using a generator-based mechanism. The portable smart automatic disinfection box embedded in the bike utilizes the synergetic effect of ultraviolet (UV), thermal, and vapor treatment for sterilizing objects. During vapor treatment, the continuous supply of the sterilizing solution is maintained through a storage tank attached to the outer body of the box and can be easily refilled. In the final step of the disinfecting protocol, the objects are exposed to UV-A light having a peak wavelength of 365–370 nm. The automatic disinfection process is powered by renewable solar and mechanical energy during cycling. The developed technology can be installed in schools, offices, and industries, and its renewable energy-powered feature offers installation in parks, tourist places, streets, remote areas, etc. This work was supported by the RRC-2-063-133 grant from the Qatar National Research Fund (a member of Qatar Foundation).

Theoretically, it is more challenging to anticipate the conversion and selectivity of a photochemical experiment compared to thermally generated reactivity. This is due to the interaction of light with a photoreactive substrate. Photochemical reactions do not yet receive the same level of broad analytical study. Here, we close this research gap by presenting a methodology for statistically forecasting the time-dependent progression of photoreactions using widely available LEDs. This study uses NiS/ZnO in perovskite (MAPbI3) solar cells as an additive (5 volume %). The effect of monolithic perovskite solar cells (mPSCs) on forecasting the wavelength of LEDs has been carefully investigated using various characterization methods, including X-ray diffraction (XRD) and Transmission electron microscopy (TEM). The photocatalytic activity was analyzed by measuring the voltage produced. Various factors like selectivity, stability and sensitivity were also examined. This work provides a new perspective to validate NiS/ZnO photocatalysts for predicting the wavelength of different light sources and to apply in photolithography. 2023, The Author(s). This work was supported by the Qatar National Research Fund under NPRP12S-0131-190030. The statements made herein are solely the responsibility of the authors. Open access funding is provided by Qatar National Library. Scopus

The quality of a companion robot’s reaction is important to make it acceptable to the users and to sustain interactions. Furthermore, the robot’s reaction can be used to train socially acceptable behaviors and to develop certain skills in both normally developing children and children with cognitive disabilities. In this study, we investigate the influence of reaction time in the emotional response of a robot when children display aggressive interactions toward it. Different interactions were considered, namely, pickup, shake, drop and throw. The robot produced responses as audible sounds, which were activated at three different reaction times, namely, 0.5 s, 1.0 s, and 1.5 s. The results for one of the tasks that involved shaking the robotic toys produced a significant difference between the timings tested. This could imply that producing a late response to an action (i.e. greater than 1.0 s) could negatively affect the children’s comprehension of the intended message. Furthermore, the response should be comprehensible to provide a clear message to the user. The results imply that the designers of companion robotic toys need to consider an appropriate timing and clear modality for their robots’ responses.Other Information Published in: International Journal of Social Robotics License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1007/s12369-020-00626-z

Many studies have investigated the effect of robot genderedness on the attribution of gender stereotypes to a robot, often with mixed results. This paper aims to overcome some of the limitations of previous research. We adopted a mixed study design with stereotypical trait type (communion vs. agency) or task type (stereotypical female vs. stereotypical male) and robot genderedness (female vs. male vs. neutral) as within-subjects factors, and participant gender (men vs. women) as between-subjects factor. We asked participants to rate 24 robots (8 per category) in terms of their perceived communion, agency, and suitability for stereotypical female and male tasks. The results disclosed that female robots activate paternalistic stereotypes (higher communion than agency, higher suitability for female tasks than male tasks), while male robots do not. Moreover, they reveal that the ambivalence of these stereotypes is stronger in men than in women. Even more interestingly, our analyses showed that neutral robots activate paternalistic stereotypes in men and envious stereotypes (higher agency than communion) in women. This last finding is particularly relevant as it suggests that gender neutrality is not enough to safeguard robots from harmful biases.

Social robots have shown some efficacy in assisting children with autism and are now being considered as assistive tools for therapy. The physical proximity of a small companion social robot could become a source of harm to children with autism during aggressive physical interactions. A child exhibiting challenging behaviors could throw a small robot that could harm another child’s head upon impact. In this paper, we investigate the effects of the mass and shape of objects thrown on impact at different velocities on the linear acceleration of a developed dummy head. This dummy head could be the head of another child or a caregiver in the room. A total of 27 main experiments were conducted based on Taguchi’s orthogonal array design. The data were then analyzed using ANOVA and then optimized based on the signal-to-noise ratio. Our results revealed that the two design factors considered (i.e. mass and shape) and the noise factor (i.e. impact velocities) affected the response. Finally, confirmation runs at the optimal identified shape and mass (i.e. mass of 0.3 kg and shape of either cube or wedge) showed an overall reduction in the resultant peak linear acceleration of the dummy head as compared to the other conditions. These results have implications on the design and manufacturing of small social robots whereby minimizing the mass of the robots can aid in mitigating the potential harm to the head due to impacts.Other Information Published in: SN Applied Sciences License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1007/s42452-019-1447-7

Research has shown that a pet robot could constitute a leverage point to open a communication channel in a triadic relation between a person with dementia and others. Additionally, tangible light projections have been shown to capture the attention of people with dementia and contribute to social interaction. Following these findings, we designed a prototype of a light-enhanced Human-Robot Interaction (HRI) for people with dementia using the robot Pleo and tested its potential to foster social interaction with 19 experts in the field of dementia and care technology in a within-subjects online study. Experts were shown a video of the prototype, as well as two videos of comparable activities with only the light or only the robot. Results showed no significant differences in the activities’ potential to stimulate social interaction and enjoyment, while they disclosed that the light-enhanced HRI could be more difficult to understand at a cognitive level. While experts considered the robot-only activity as more suited for individual interactions, they perceived the light-enhanced HRI as more suited for small sized groups. This latter result seems to suggest that adding a tangible light to an HRI for people with dementia could convert it from an individual to a group activity.

We report on the exploratory design and study of a robot math tutor that can provide feedback on specific errors made by children solving basic addition and subtraction problems up to 100. We discuss two interaction design patterns, one for speech recognition of answers when children think aloud, and one for providing error-specific feedback. We evaluate our design patterns and whether our feedback mechanism motivates children and improves their performance at primary schools with children (N=41) aged 7–9. We did not find any motivational or learning effects of our feedback mechanism but lessons learnt include that the robot can execute our interaction design patterns autonomously, and advanced algorithms for error classification and adaptation to children’s performance levels in our feedback mechanism are needed.

We are developing a social robot that should autonomously interact long-term with pediatric oncology patients. The child and the robot need to get acquainted with one another before a long-term interaction can take place. We designed five interaction design patterns and two sets of robot behaviors to structure a getting acquainted interaction. We discuss the results of a user study (N = 75, 8–11 y.o.) evaluating these patterns and robot behaviors. Specifically, we are exploring whether the children successfully got acquainted with the robot and to what extent the children bonded with the robot. Results show that children effectively picked up how to talk to the robot. This is important, because the better the performance the more comfortable the children are, the more socially attractive the robot is, and the more intimate the conversation gets. The evaluation furthermore revealed that it is important for children, in order to get familiar with the robot, to have shared interests with the robot. Finally, most children did initiate a bond with the robot.

This paper presents the design and validation of a measurement instrument for children’s perceptions of robots’ social competence. The need for a standardized validated instrument has emerged as a requisite for meta-analyses and comparisons among various studies in the field of child-robot interaction. We report on the development of the instrument and its validation, which adopted a design-based method with two iterations. We used construct validity, which was formed by divergent and convergent validity. Children’s perceptions of three different robotic platforms were examined in two empirical studies with 78 children aged 7–9 years, which was based on semi-structured interviews with qualitative thematic content analysis. The results indicated that children differentiate their perception of social competence depending on the perceived intentionality of the robot and they ascribe discrete categorizations to the robot such as a machine, social artifact and social agent. The findings are discussed in relation to existing literature.

Improving the quality of life of people with dementia in long-term care facilities is very important and can be achieved by designing engaging activities for the residents. The introduction of social robots for people with dementia has already proven its benefits, and we expected that adding contextual cues to this interaction would enhance the positive engagement of these individuals. A total of five participants took part in a comparison study in which they engaged in a free-play session with the robot PLEO and in a free-play session with the robot PLEO within a jungle-themed context. The gaze and arm/hand behaviors of the participants were measured and were used to determine the level of their engagement. Contrary to our expectations, we found a significant decrease in engagement for the sessions where the context was added to the interaction. Our explanation of this result is that the added cues increased the threshold to interact with the robot, but the elderly were still engaged as spectators.

In many scenarios where robots could assist humans, handover situations are essential. But they are still challenging for robots, especially if these are initiated by the human interaction partner. Human-human handover studies report average reaction times of 0.4 s, which is only achievable for robots, if they are able to predict the object transfer point (OTP) sufficiently early and then adapt to the human movement. In this paper, we propose a hand tracking system that can be used in the context of human initiated handover as a basis for human reaching motion prediction. The OTP prediction implemented is based on the minimum jerk model and combines a static estimation utilizing the human’s initial pose and a dynamic estimation from the current hand trajectory. Results are generated and analyzed for a broad spectrum of human initiated scenarios. For these cases we examine the dynamics of different variants of the proposed prediction algorithm, i.e., how early is a robot’s prediction of the OTP within a certain error range? The tracking delivers results with an average delay, after the initialization, of 0.07 s. We show that the OTP prediction delivers results after 75 % of the movement within a 10 cm precision box.

There is a growing interest in social robots to be considered in the therapy of children with autism due to their effectiveness in improving the outcomes. However, children on the spectrum exhibit challenging behaviors that need to be considered when designing robots for them. A child could involuntarily throw a small social robot during meltdown and that could hit another person’s head and cause harm (e.g. concussion). In this paper, the application of soft materials is investigated for its potential in attenuating head’s linear acceleration upon impact. The thickness and storage modulus of three different soft materials were considered as the control factors while the noise factor was the impact velocity. The design of experiments was based on Taguchi method. A total of 27 experiments were conducted on a developed dummy head setup that reports the linear acceleration of the head. ANOVA tests were performed to analyze the data. The findings showed that the control factors are not statistically significant in attenuating the response. The optimal values of the control factors were identified using the signal-to-noise (S/N) ratio optimization technique. Confirmation tests at the optimal parameters (e.g. thickness of 3 mm or 5 mm) showed better responses as compared to other conditions. Designers of social robots should consider the application of soft materials to their designs as it helps in reducing the potential harm to the head.Other Information Published in: SN Applied Sciences License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1007/s42452-019-0467-7

Drones are often used in a context where they interact with human users. They, however, lack the social cues that their robotic counterparts have. If drones would possess such cues, would people respond to them more positively? This paper investigates people’s evaluations of a drone with eyes versus one without. Results show mainly positive effects, i.e. a drone with eyes is seen as more social and human-like than a drone without eyes, and that people are more willing to interact with it. These findings imply that adding eyes to a drone that is designed to interact with humans may make this interaction more natural, and as such enable a successful introduction of social drones.

Previous research has shown that gender-related stereotypes are even applied to robots. In HRI, a robot’s appearance, for instance, visual facial gender cues such as hairstyle of a robot have successfully been used to elicit gender-stereotypical judgments about male and female prototypes, respectively. To complement the set of features to visually indicate a robot’s gender, we explored the impact of waist-to-hip ratio (WHR) and shoulder width (SW) in robot prototypes. Specifically, we investigated the effect of male vs. female appearance on perceived robot gender, the attribution of gender stereotypical traits, the robots’ suitability for stereotypical tasks, and participants’ trust toward the robots. Our results have demonstrated that the manipulation of WHR and SW correctly elicited gendered perceptions of the two prototypes. However, the perception of male robot gender did not affect the attribution of agentic traits and cognitive trust. Nevertheless, participants tended to rate the male robot as more suitable for stereotypically male tasks. In line with our predictions, participants preferred to use the female robot shape for stereotypically female tasks. They tended to attribute more communal traits and showed more affective trust toward the robot that was designed with a female torso versus a male robot torso. These results demonstrate that robot body shape activates stereotypes toward robots. These in turn, deeply impact people’s attitudes and trust toward robots which determine people’s motivation to engage in HRI.

Service robots are expected to closely interact with humans in the near future. Their tasks often include delivering and taking objects. Thus, handover scenarios play an important role in human-robot-interaction. A lot of work in this field of research focuses on speed, accuracy and predictability of the robot’s movement during object handover. Those robots need to closely interact with naive users and not only experts. In order to evaluate handover interaction performance between human and robot a force measurement based approach was implemented on the humanoid robot Floka. Different gestures with the second arm were added to analyze the influence on synchronization, predictability, and human acceptance. In this paper we present a study where users with different levels of experience were asked to help the robot to learn new objects. We evaluated the impact of previous knowledge with robots on handover interactions. Disparities in timing, distance, and applied force during handover could be observed. We present an automated annotation pipeline for human-robot-interaction that will be used in future studies. While the commonly used force measurement based approach proved to be a valid starting point, our results show that naive user interaction could benefit from better anticipation.

We present design strategies for Human Robot Interaction for school-aged autistic children with limited receptive language. Applying these strategies to the DE-ENIGMA project (large EU project addressing emotion recognition in autistic children) supported development of a new activity for in facial expression imitation whereby the robot imitates the child's face to encourage the child to notice facial expressions in a play-based game. A usability case study with 15 typically-developing children aged 4--6 at an English-language school in the Netherlands was performed to observe the feasibility of the setup and make design revisions before exposing the robot to autistic children.

How can we generate appropriate behavior for social artificial agents? A common approach is to (1) establish with controlled experiments which action is most appropriate in which setting, and (2) select actions based on this knowledge and an estimate of the setting. This approach faces challenges, as it can be very hard to acquire and reason with all the required knowledge. Estimating the setting is challenging too, as many relevant aspects of the setting (e.g. personality of the interactee) can be unobservable. We formally describe an alternative approach that can handle these challenges; responsiveness. This is the idea that a social agent can utilize the many feedback cues given in social interactions to continuously adapt its behavior to something more appropriate. We theoretically discuss the relative advantages and disadvantages of these two approaches, which allows for more explicitly considering their application in social agents.

Social robots are machines developed to interact with humans. Unlike other technological devices, their presence in society requires accepting and treating them as social agents. This has important implications in terms of social changes for humans’ personal and social identity, and social interactions. We aim to explain the core features that characterize social robots by highlighting what makes them distinct from other types of innovative technology. Equally important, we illustrate how social psychology can provide a useful perspective to understand human-robot interactions. To do so, we focus on studies that have investigated the role of intergroup relations and social identity in the context of human-machine interactions to demonstrate that robots may comprise a new type of social outgroup in future society.

Preventing diseases of affluence is one of the major challenges for our future society. Recently, robots have been introduced as support for people on dieting or rehabilitation tasks. In our current work, we are investigating how the companionship and acknowledgement of a socially assistive robot (SAR) can influence the user to persist longer on a planking task. We conducted a 2 (acknowledgement vs. no-acknowledgment) x 2 (instructing vs. exercising together) x 1 (baseline) study with 96 subjects. We observed a motivational gain if the robot is exercising together with the user or if the robot is giving acknowledging feedback. However, we could not find an increase in motivation if the robot is showing both behaviors. We attribute the later finding to ceiling effects and discuss why we could not find an additional performance gain. Moreover, we highlight implications for SAR researchers developing robots to motivate people to extend exercising duration.

In the present study, we investigated teachers’ attitudes toward teaching with education robots and robot-mediated learning processes. We further explored predictors of attitudes, and investigated teachers’ willingness to use robots in diverse learning settings. To do so, we conducted a survey with 59 German school teachers. Our results suggest that teachers held rather negative attitudes toward education robots. Further, our findings indicate a positive association between technology commitment and teachers’ attitudes. Teachers reported a preferable use of robots in domains related to science, technology, engineering, and mathematics (STEM). Regarding expectations toward the future use of education robots, teachers mentioned their motivational potential, using robots as information source, or easy handling. Teachers’ concerns, however, were associated with the disruption of teaching processes, additional workload, or the fear that robots might replace interpersonal relationships. Implications of our findings for theory and design of education robots are discussed.

In an online survey, we studied user expectations and preferences for functions and apps in the context of a smart apartment. Furthermore, we explored which type of interface users would choose for an interaction with the smart apartment. Equally important, we investigated users’ acceptance of a service robot in the smart home. Results showed high levels of acceptance for both, the smart apartment and the robot, although the preferred interface for the apartment was context dependent. We discuss implications of the current survey and highlight key aspects to be taken into consideration when developing innovation technology for the home context.

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A growing field in Human-Robot Interaction aims at social assistance for users on specific tasks. These applications allow for insights regarding the acceptance of the robot's presence and interaction-related performance effects. We present a scenario in which a socially assistive robot assists users on a cognitive task. Furthermore, we quantitatively evaluate the effects of two distinct interaction strategies on performance of the user and acceptance of the robot's presence. In one strategy, the robot acts as a structuring guide and in the other, the robot tries to individually enhance the performance of the user. Results show that users benefit from a suited interaction strategy in terms of test performance and that the robot's presence is regarded as acceptable and also desirable.

Social interaction between humans takes place in the spatial dimension on a daily basis. We occupy space for ourselves and respect the dynamics of spaces that are occupied by others. In human-robot interaction, the focus has been on other topics so far. Therefore, this work applies a spatial model to a humanoid robot and implements an attention system that is connected to it. The resulting behaviors have been verified in an on-line video study. The questionnaire revealed that these behaviors are applicable and result in a robot that has been perceived as more interested in the human and shows its attention and intentions to a higher degree.

Customization has been widely studied in the context of information systems and interfaces, but research on customization in human-robot interaction (HRI) is scarce. However, customization and user involvement may exert positive effects regarding attitudes and trust toward robots, hence improving HRI quality. The aim of the present work is to contribute to the theoretical understanding of customization in the HRI context by testing whether customization (none, low, or high) of a robot would elicit feelings of psychological ownership (PO), which, in turn, would increase trust toward the robot. Moreover, we hypothesized that the more people customize a robot, the less they would tend to anthropomorphize it. In line with our predictions, customization (vs. none) significantly increased psychological ownership and trust toward the robot. Further, the level of customization affected perceptions of robot agency. Additionally, PO mediated the effect of customization on trust toward the robot. The implications of these findings for research on HRI are discussed.

3D printing is the new frontier in building construction. It is especially useful for building small houses within a short period of time. Complete construction including the interior partitions and exterior facade can be achieved with 3D printing. In this thesis, a parametric Voronnoi model is proposed for quickly generating and fabricating 3D printed partitions for interior design. Parametric design allows rapid customization and enables manufacturing of unique structures with 3D printing. This technique allows for the fabrication of complex designs that would be difficult to fabricate with traditional manufacturing methods. Furthermore, the fabricated Voronoi structures are aesthetically pleasing and exhibits artistic expressions while maintaining structural integrity. Modular design allows different type of structural designs as needed with easy assembly using magnetic coupling. This study introduces a parametric design of a hexagonal block with an enclosed surface of relaxed Voronoi cells. A number of those blocks have been manufactured through a 3D printing process to be puzzle-like assemblage, producing a large-scale cohesive artistic wall. This study provides comprehensive and comparative testing to ensure the validity of the mechanical properties of the design and investigating the energy absorption characteristics for the proposed 3D printed hexagonal block. The best Voronoi structures exhibit superior mechanical and energy absorption properties compared to their non-Voronoi counterparts with energy absorption values ranging from 350 J to 435 J and crash force efficiency being 1.42 to 1.65.

People with upper-limb reductions or amputations need prosthetic replacements throughout their lives as they grow and change. The standard method of prosthetic development takes a lot of time for fabrication by technicians and requires expert designers for patient-specific customizations. This can cause significant hardships for patients living in remote regions. Furthermore, many high-functional electric-powered prostheses are expensive and beyond the affordability of a large segment of users. Additionally, they require experts for maintenance whose availability maybe limited. To address these issues, a parametric 3D-printed passive upper-limb prosthesis design is proposed in this thesis. The parameters are based on few anthropometric features from the healthy hand that can be easily measured. Since polymer-based 3D printing has become popular and affordable, low-cost rapid fabrication of custom designs is no longer challenging. The prosthetic hand model is made using state-of-the-art 3D parametric modeling software. Seven anthropometric features are used as input for the generation of the custom model: palm length, wrist diameter and circumference, middle finger length and circumference, and metacarpal circumference and diameter. The fabricated passive prosthetic hand can perform up to 31 grasps.

Gas detection is a critical task in dangerous environments that involve hazardous or contaminant gases. Quick detection of gas leaks and their rectification ensure the protection of lives and safeguards equipment installed in workplaces and industrial sites. Extensive work has been done in remote monitoring of the gas leaks via sensors installed at the locations. Even though these devices can detect harmful gases in the environment, they are not designed to take instant action for gas/smoke removal. We have surveyed the literature and gathered information that smoke from the fire accidents causes a lack of visibility to the exit, and many untimely lives are lost. Thus, further research has to be carried out to develop devices that can not only detect the harmful gases but also have the technology for gas/smoke removal supported by standard protocols to mitigate the effects of the harmful gas on the surrounding environment, such as an explosion, asphyxiation, fire. This thesis addresses the tasks required for developing a mobile robot that not only detects the presence of leakage of harmful gas like carbon dioxide (CO2), carbon monoxide(CO), ammonia NH3, liquid petroleum gas (LPG) and broadcast the information via wireless communication modeling system but also has gas filtration mechanism that helps in purifying the surrounding air that has been contaminated by the leakage of the harmful gas. The contributions presented in this thesis are three-fold. Firstly, the fabrication of gas sensors via a 3D printing technique. The 3D printing approach enables the bulk production of the sensors in a short period. It gives control over the repeatability, reproducibility, and sensitivity of the fabricated sensors, especially for CO2.

Social robots are being considered to be a part of the therapy for children with autism due to the reported efficacy such technology in improving the outcomes. How ever, children diagnosed with autism exhibit challenging behaviors that could cause harm to themselves and to others around them. Throwing, hitting, kicking, and self harming are some examples of the challenging behaviors that were reported to occur among this population. The occurrence of such behaviors during the presence of a social robot could raise some safety concerns. For this reason, this research attempts toidentify the potential for harm due to the diffusion of social robots and investigate means to mitigate them. Considering the advancement in technology and the progress made in many computer science disciplines are making small and adaptable social robots a foreseeable possibility, the studies presented here focus on small robotic form factors.The first study quantities the potential harm to the head due to one of the identi?ed risky scenarios that might occur between a child and a social robot. The results re leaved that the overall harm levels based on the selected severity indices are relatively low compared to their respective thresholds. However, the investigation of harm due to throwing of a small social robot to the head revealed that it could potentially causet issue injuries, sub-concussive or even concussive events in extreme cases. The second two studies are aimed to make small robots safer by optimizing their design. Hence,studies are conducted investigating how robot design can be made safer by investigating different design factors. The study investigated the in?uence of the mass and shape on the linear acceleration of a developed dummy head. The results revealed that the two design factors considered (i.e. mass and shape) affected the resultant response. The second study investigated the in offence three different soft material sonthesa meresponse. The endings showed that the control factors considered are not statistically significant in attenuating the response. Finally, the last two studies attempt to make small robots more adaptable to promote safer interactions. This is carried out by em bedding the recognition of unwanted physical interactions into companion robot with the appropriate timing of responses. The findings of the first study highlight the pos sibility of characterizing children's negative interactions with robotic toys relying on accelerometer sensor. The second study showed that producing a late response to an action (i.e. greater than 1.0 s) could negatively affect the children's comprehension of the intended message. The work presented in this dissertation is multidisciplinary that involves the field of Mechanical Engineering and Information Technology.

The introduction of service robots to our daily life requires adaptation of the current navigation strategies. In the presence of humans, robots must be designed to ensure their safety and comfort. This paper proposes a layered costmap architecture that incorporates social norms to generate trajectories compatible with human preferences. The implemented framework creates a social abstraction of the environment – in the form of an occupancy grid – to plan human-friendly paths. It employs information about individuals in the scene to model their personal spaces. In addition, it uses predicted human trajectories to improve the efficiency and legibility of the robot trajectory. Different simulation scenarios resembling everyday situations have been used to evaluate the proposed framework. The results of the experiments have demonstrated its ability to behave according to social conventions. Furthermore, the navigation system was assessed in real life experiments where it was proved capable of following similar paths to those performed by humans.

This paper is about speaker verification and horizontal localisation in the presence of conspicuous noise. Specifically, we are interested in enabling a mobile robot to robustly and accurately spot the presence of a target speaker and estimate his/her position in challenging acoustic scenarios. While several solutions to both tasks have been proposed in the literature, little attention has been devoted to the development of systems able to function in harsh noisy conditions. To address these shortcomings, in this work we follow a purely data-driven approach based on deep learning architectures which, by not requiring any knowledge either on the nature of the masking noise or on the structure and acoustics of the operation environment, it is able to reliably act in previously unexplored acoustic scenes. Our experimental evaluation, relying on data collected in real environments with a robotic platform, demonstrates that our framework is able to achieve high performance both in the verification and localisation tasks, despite the presence of copious noise.

Care robots are often seen to introduce a risk to human, touch based care. In this study, we analyze care workers’ opinions on robot assistance in elderly services and reflect them to the idea of embodied relationship between a caregiver, care receiver and technology. Our empirical data consists of a survey for professional care workers (n = 3800), including registered and practical nurses working in elderly care. The questionnaire consisted scenarios of robot assistance in care work and in elderly services and the respondents were asked to evaluate whether they see them as desirable. The care workers were significantly more approving of robot assistance in lifting heavy materials compared to moving patients. Generally, the care workers were reserved towards the idea of utilizing autonomous robots in tasks that typically involve human touch, such as assisting the elderly in the bathroom. Stressing the importance of presence and touch in human care, we apply the ideas of phenomenology of the body to understand the envisioned robot-human constellations in care work.

Researching human-robot interaction “in-the-wild” cansometimes require insight from different fields. Experiments that involvecollaborative tasks are valuable opportunities for studying HRI anddeveloping new tools. The following describes a framework for an “in thewild” experiment situated in a public museum that involved a Wizardof OZ (WOZ) controlled robot. The UR10 is a non-humanoid collabora- AQ1tive robot arm and was programmed to engage in a collaborative drawingtask. The purpose of this study was to evaluate how movement by a nonhumanoidrobot could affect participant experience. While the currentframework is designed for this particular task, the control architecturecould be built upon to provide a base for various collaborative studies.

Orienting attention towards another person of interest is a fundamental social behaviour prevalent in human-human interaction and crucial in human-robot interaction. This orientation behaviour is often governed by the received audio-visual stimuli. We present an adaptive neural circuit for multisensory attention orientation that combines auditory and visual directional cues. The circuit learns to integrate sound direction cues, extracted via a model of the peripheral auditory system of lizards, with visual directional cues via deep learning based object detection. We implement the neural circuit on a robot and demonstrate that integrating multisensory information via the circuit generates appropriate motor velocity commands that control the robot’s orientation movements. We experimentally validate the adaptive neural circuit for co-located human target and a loudspeaker emitting a fixed tone.

This paper investigates the role of tutor feedback in grounded language learning experiments. We compare two dominant paradigms in language learning: interactive learning and cross-situational learning using robot-robot experiments in the real world. In particular, we study a mixed paradigm, introduced in earlier work, only now in real world interaction. Our experiments quantify the potential impact of social feedback in language learning. Since the grounded world is a more structured environment than random worlds, we also quantify whether algorithms can make use of that structure.

This paper proposes an alternative approach to evaluating Human- Robot Interaction (HRI), drawing on the field of Anthropology. Considering the user in the traditional robot-environment dyad has major practical and philosophical implications. This paper contends that the traditional scientific method, by itself, is not sufficient to account for the complexity and social nature of the interaction. Instead, it should be complemented with exploratory, ethnographic and reflexive research in order to make additional philosophical, practical and ethical contributions. The HRI evaluation model proposed in this paper builds on existing HRI models and draws on theories and methodologies from the field of Anthropology. It applies a ‘refunctioned’ approach to ethnography, in which roboticists and anthropologists collaborate to evaluate robot interactions from an ethnographic, experimental and ethical perspective to reconcile three distinct ontological views of the user experience: robot-centric, human-centred, and societal impact. The model represents a formative approach to evaluation, in which early-stage explorative and empirical data is used to capture a holistic view of the interaction. This descriptive data may subsequently be parsed to develop specific and testable hypotheses and design principles.

Elderly people moving into assisted living facilities often face profound changes in their daily routines and social relationships, which may lead to feelings of social isolation and even to depression. Telepresence robots can alleviate this by enabling easily accessible virtual presence of family members and other close ones at the ward. Telepresence robots have been tested in different care environments with often positive responses, but there are still challenges, both technical and non-technical, that hinder the wider adoption of the robots in residential care settings. We seek for more understanding of the non-technical challenges by studying the use of a telepresence robot Double in a residential care facility. In a 12-week field trial, we installed a telepresence robot in a room of a long-term care home resident for communicating with her family members. The qualitative interview data included the perspectives of the resident, her family members and care workers at the ward. The results confirm the potential of telepresence robots in assisted living in order to increase the presence of family members to the resident and vice versa; the study also provides insight about how the increased presence of family members may affect the care work.

Social service robots are gradually entering into shopping malls to provide guidance and information services to the consumer customers. Earlier literature has reported that usually consumers response positively to these robots. Less is known about how do retailers and other business actors in the shopping mall perceive the robots. We present results of an interview study carried out with eight retailers and other service providers in a shopping mall, and three shopping mall managers. The results provide insight into their views about potential application roles of social service robot in the mall: what kind of services the robot could provide to customers besides guiding and information providing, and what kind of opportunities, requirements and constraints a shopping mall sets as a business environment for robot developers and service providers. The capability of the robot to emotionally engage with the customers was seen highly potential in shopping business but balancing entertainment with utility functions is crucial. A Pepper robot was used as a demonstrative platform in the study.

he paper highlights how the material affordances of a teleoperated robot (Telenoid) enable identity construction in interactions with people living with acquired brain injury (ABI). The focus is set on the identity construction of the robot in relation to both its operator and the interlocutors. The analysis is based on video recordings of a workshop in which people with ABI were communicating with a teleoperated robot for the first time. A detailed multimodal conversation analysis of video-recorded interactions demonstrates how identity construction a) is embedded in the situated and interactional unfolding of the encounter and b) is fragmented and reflexively intertwined with the identity construction of the other parties. The paper discusses how an understanding of identity as situated and interactional constructions contributes to the field of HRI and how teleoperated robots can be used in the field of communication impairment.

In this literature review we explain anthropomorphism and its role in the design of socially interactive robots and human-robot interaction. We illus-trate the social phenomenon of anthropomorphism which describes people’s tendency to attribute lifelike qualities to objects and other non lifelike artifacts. We present theoretical backgrounds from social sciences, and integrate related work from robotics research, including results from experiments with social ro-bots. We present different approaches for anthropomorphic and humanlike form in a robot’s design related to its physical shape, its behavior, and its interaction with humans. This review provides a comprehensive understanding of anthro-pomorphism in robotics, collects and reports relevant references, and gives an outlook on anthropomorphic human-robot interaction.

We explored the potential of teleoperated android robots, which are embodied telecommunication media with humanlike appearances, and how they affect people in the real world when they are employed to express a telepresence and a sense of ‘being there’. In Denmark, our exploratory study focused on the social aspects of Telenoid, a teleoperated android, which might facilitate communication between senior citizens and Telenoid’s operator. After applying it to the elderly in their homes, we found that the elderly assumed positive attitudes toward Telenoid, and their positivity and strong attachment to its huggable minimalistic human design were cross-culturally shared in Denmark and Japan. Contrary to the negative reactions by non-users in media reports, our result suggests that teleoperated androids can be accepted by the elderly as a kind of universal design medium for social inclusion.

International audience; Providing guidance to customers in a shopping mall is a suitable task for a social service robot. To be useful for customers, the guidance needs to be intuitive and effective. We conducted a four-phase qualitative study to explore what kind of guidance customers need in a shopping mall, which characteristics make human guidance intuitive and effective there, and what aspects of the guidance should be applied to a social robot. We first interviewed staff working at the information booth of a shopping mall and videotaped demonstrated guidance situations. In a human-human guidance study, ten students conducted seven way-finding tasks each to ask guidance from a human guide. We repli-cated the study setup to study guidance situations with a social service robot with eight students and four tasks. The robot was controlled using Wizard of Oz technique. The characteristics that make human guidance intuitive and effective, such as estimation of the distance to the destination , appropriate use of landmarks and pointing gestures, appear to have the same impact when a humanoid robot gives the guidance. Based on the results, we identified nine design implications for a social guidance robot in a shopping mall.