Robots have the potential to deliver very positive impacts for society, however, it's critical that in preparing for real-world deployments, we recognize and take steps to mitigate against the potential harms, both direct and indirect, that they may cause. In this paper, we explore how the ethics canvas (EC) and the ethical risk assessment (ERA) methodology defined in British Standard 8611 can be combined to better align robot technologies with ethics and their socio-cultural context of operation. We illustrate this through a practical case-study involving the real-world introduction of a disinfection robot to a radiology department in a European hospital. Using the EC, we identified 49 distinct ways that the technology was likely to impact key stakeholders and 11 ways that failure or misuse of the technology was likely to impact service provision. From this data, 8 mitigating measures were identified. Then, using the ERA tool, 9 risks were identified that were considered to represent a high likelihood of occurrence. From these insights, a further 8 mitigation measures were proposed. The combined use of both tools was found to be complementary, since the EC fostered a bottom-up, subjective critical thinking process whereas the ERA provided a broader, more top-down objective view. This example provides a practical template for robotics practitioners to better understand and manage the ethical and socio-cultural dimensions of their work, and contributes towards the standardization of ethical assessments in robotics with an emphasis on the move from principles to practice.

The ability to interact verbally with humans is a key requirement of many social robots. It is common however for robot speech to lack contextual human-like prosody, making it intelligible but seeming inexpressive and cold. We investigated the effect that applying human-like prosody to synthetic speech had on aural comprehension during human-robot interaction. A text-to-speech system was used to generate synthetic sentences in two conditions: ‘default’ and ‘human’(informed by voice actor). A speech-in-noise experiment was then performed that required participants to transcribe perceived sentences spoken by a robot in both test conditions. Overall, we found no significant difference in comprehension between sentences spoken using the synthetic voice with prosody and the unaltered synthetic voice, however significant differences in comprehension were detected for shorter sentences (n=50), and among participants that learned English in a different country to the native dialect of the voice actor (n=26). In both of these cases, participants found the voice with human-like prosody harder to comprehend. These findings suggest that introducing human-like prosody to synthetic speech in human-robot interaction, under certain circumstances, may lead to the voice becoming less intelligible. This motivates further research and adds to the growing body of literature on the multifaceted role that voice plays in human-robot interaction.

As with all remotely controlled robots, successful teleoperation of social and telepresence robots relies greatly on operator situation awareness; however, existing situation awareness measurements, most being originally created for military purposes, are not adapted to the context of social interaction. We propose an objective technique for telepresence evaluation based on the widely accepted Situation Awareness Global Assessment Technique, adjusted to suit social contexts. This was trialled in a between-subjects participant study ( n = 56) comparing the effect of mono and spatial (binaural) audio feedback on operator situation awareness during robot teleoperation in a simulated social telepresence scenario. Subjective data were also recorded, including questions adapted from Witmer and Singer’s Presence Questionnaire, as well as qualitative feedback from participants. No significant differences in situation awareness measurements were detected; however, correlations observed between measures call for further research. This study and its findings are a potential starting point for the development of social situation awareness assessment techniques, which can inform future social and telepresence robot design decisions.

Robots that lend social and emotional support to their users have the potential to extend the quality of care that humans can provide. However, developing robotic aids to address symptoms of loneliness, anxiety and social isolation can be especially challenging due to factors that are complex and multi-faceted. Using a user-centered approach, a prototype therapeutic robot, TACO, was developed. The design of this robot was closely informed by a comprehensive needfinding process which included a detailed literature review, ethical analysis, interviews with pediatric domain experts, and a site visit to a pediatric hospital. The prototype robot was evaluated over the course of several structured play sessions, using short interviews with children as well as a modified version of the SOFIT testing procedure. Results from early-stage testing suggest that TACO was well-liked, children found playing with it engaging and frequently exhibited affective behaviors like cuddling and stroking. These findings motivate follow-on work to further advance its design and to test its effectiveness as a therapeutic tool.

Socially assistive robots have the potential to help keep people with dementia cognitively active and entertained. This is important for their wellbeing. We explored staff perceptions of the acceptability of a new humanoid robot, Stevie, in an adult day care center for people with dementia. Stevie was deployed over 2 weeks in the day center to entertain 40 guests with dementia with three activities: (i) musical bingo, (ii) quizzes, and (iii) meet and greet. Nine staff members were asked what went well, whether the robot operated as expected, experiences of any technical issues, and the extent to which it hindered or aided their duties. Staff also rated guest engagement, guest enjoyment, and whether they were able to spend more time with guests. The sessions were successfully delivered. Staff reported that Stevie operated as expected, guest engagement with the robot was high, interactions with the robot were natural and the robot’s novelty helped engagement. Use of the robot gave staff more time to attend to guests’ needs. Suggested improvements included improvements to the robot’s voice and adding a pause function during activities. With greater autonomy and/or extended use of its telepresence functionality, use of Stevie could become cost effective in such settings.

To operate in unstructured settings, robots require control strategies that effectively respond to temporal changes in their environment. In the domain of robotic manipulation, most state-of-the-art approaches assume the objects to be grasped are static. Although some research has investigated the challenges of grasping moving objects, these studies have tended to use grasping plans which require a real-time estimate of a gripper-object interception point, which can be difficult to precisely obtain. The goal of this research was to investigate the performance benefits of using a controller with a reactive component for grasping tasks involving moving objects. We hypothesised that using a reactive control strategy, based on tactile sensing in the fingertips, would lead to improved performance and robustness across a wider range of grasping conditions. To test this hypothesis, the ability of a two-finger gripper to grasp a moving ball under a range of dynamic conditions was tested in simulation using the Gazebo robotic simulator and ODE physics engine. Tests revealed that for controllers where the grasp was not informed by tactile sensing, grasping success dropped significantly with increased misalignment between the centre point of the gripper and the point of interception with the moving object. In contrast, the performance of a reactive grasping strategy based on tactile sensing was found to be more robust across these conditions. These findings indicate that tactile sensing could play an important role in enabling robots to interact more effectively with dynamic objects.

The use of ultraviolet germicidal irradiation (UVGI) technology as a means of disinfecting hospitals and other frontline settings has increased significantly in the wake of the COVID-19 pandemic. Although the science of UVGI is well established, it can be difficult to determine in practice if sufficient levels of UVC has been irradiated to kill the target microbes in a room. This research presents the development of a low-cost wireless UVC sensor that can be used to systematically track the UV irradiation dose on target surfaces during a UV disinfection procedure. We present key elements of the design of this device, which included a custom PCB, enclosure, operating software, and graphical user interface. The applicability of the system was assessed through an experiment where the devices were placed at 12 locations in a CT scan treatment room that was subject to a UVGI disinfection procedure using an autonomous UV robot. Over the course of three cleaning sessions, each lasting approximately 10 minutes, it was found that each site location received an average UVC dose of 13mJ/cm2, which is more than published D90 values for SARS-Cov-2, influenza, and a number of known pathogens that are commonly found in hospital settings. This study provides early validation of the potential effectiveness of low-power wireless UV level monitoring technology, which may form part of future distributed room sensing networks or as part of smart wearable devices carried by relevant hospital staff.

The ability to clearly communicate a wide range of emotional states is considered a desirable trait for social robots. This research proposes that the Geneva Emotion Wheel (GEW), a self-report instrument for measuring emotional reactions, has strong potential for use as a tool for evaluating the expression of affective content by robots. Factors that make the GEW advantageous over existing evaluation methods include: ease of administration, reduction in the importance of word labels, and coverage of "no emotion" states. Statistical analyses of the GEW are proposed, isolating quantitative metrics of emotion distinctness. An experiment requiring participants to rate the perceived emotion of a social robot was conducted, employing the proposed methods. Analysis using the GEW revealed significant differences in the reliability of different expressions to clearly convey emotional states. The GEW provided a repeatable, systematic framework for estimating perceived affect of robot expression. Thus, the results suggest the GEW offers a powerful tool for design purposes as well as analysis. To support future research using the GEW, the software used for the analysis has been packaged and made available as an open-source resource to the community.

It's widely accepted that a robot's embodiment plays an important role during human-robot interaction (HRI). While many studies have explored the effect of robot appearance, relatively little is known about how the texture and stiffness of the surface material, or what may be referred to as 'robot-skin', influences how the robot is perceived. Gaining improved understanding in this area may have direct and actionable consequences on robot design, since at present nearly all commercially available service robots have similar exterior surfaces composed of smooth, stiff materials, usually plastic. This study is framed around systematically investigating the type of textures that may be better suited for these robots. First, experiments were undertaken to classify the textural characteristics of 27 distinct materials which could potentially be used as a robot-skin. A representative subset of these materials was then selected for a second experiment that explored how the stiffness and tactile properties of the material influenced its perceived suitability for use on a service robot. The research found that people strongly preferred surface textures that were soft, rather than stiff. The most suitable material stiffness was found to be context dependent; soft options were preferred in the blind test condition, but for cases where participants were presented with the 3D image of a service robot in an immersive virtual reality environment, medium stiffness materials were preferred. In the final part of the study, we identified a range of textural properties that seem to correlate with high and low suitability for use on service robots. It is hoped that these findings are useful to help inform the design of future HRI systems, and motivate further investigation into the social roles of robot-skin.

Hybrid wheel-legged robots have begun to demonstrate the ability to adapt to complex terrain traditionally inaccessible to purely wheeled morphologies. Further research is needed into how their dynamics can be optimally controlled for developing highly adaptive behaviours on challenging terrain. Using optimal center of mass (COM) kinematic trajectories, this work examines the nonlinear dynamics control problem for fast height adaptation on the hybrid humanoid platform known as Aerobot. We explore the dynamics control problem through experimentation with an offline trajectory optimisation (TO) method and a task-space inverse dynamics (TSID) controller for varying the robot's height. Our TO approach uses sequential quadratic programming (SQP) to solve optimal 7th order spline coefficients for the robot's kinematics. The nonlinear Zero Moment Point (ZMP) is used to model a stability criterion that is constrained in the TO problem to ensure dynamic stability. Our TSID controller follows motion plans based on using task jacobians and a simplified passive dynamics model of the Aerobot platform. Results exhibit fast height adaptation on the Aerobot platform with significantly differing results between the control methods that prompts new research into how it may be controlled online.

Social robots have a recognizable physical appearance, a distinct voice, and interact with users in specific contexts. Previous research has suggested a `matching hypothesis', which seeks to rationalise how people judge a robot's appropriateness for a task by its appearance. Other research has extended this to cover combinations of robot voices and appearances. In this paper, we examine the missing connection between robot voice, robot appearance, and deployment context. In so doing, we asked participants to match a robot image to a voice within a defined interaction context. We selected widely available social robots, identified task contexts they are used in, and manipulated the voices in terms of gender, naturalness, and accent. We found that the task context mediates the `matching hypothesis'. People consistently selected a robot based on a vocal feature for a certain context, and a different robot based on the same vocal feature for another context. We suggest that robot voice design should take advantage of current technology that enables the creation and tuning of custom voices. They are a flexible tool to increase perception of appropriateness, which has a positive influence on Human-Robot Interaction.

Communication delays are known to create stability and performance issues in multilateral teleoperation systems. Multilateral teleoperation configurations usually include more than two communication channels, which can become problematic for robot control when limitations in network bandwidth results in delays and uncertainties in data transmission routes. This study develops a sliding surface based on the synchronization errors characterized between each sides of the considered multilateral teleoperation system. Here, two slave robots receive commands from the master system to cooperatively execute the desired teleoperation task in the remote, shared workspace. Lyapunov stability analysis approach guarantees the performance of the proposed controller. Moreover, the effectiveness of the controller is experimentally evaluated through a real-world Internet-based double-slave teleoperation system.

Socially assistive robots (SARs) have the potential to improve working conditions of care workers, empower vulnerable people to retain independence, and even provide social companionship. Through a series of focus groups, this study explores how older adults and professional care workers in a Continued Care Retirement Community (CCRC) perceived a bespoke SAR platform known as Stevie. Using a mixed-method approach, it emerged that both care staff and residents developed a strong fondness for the robot, perceived it to be useful, and could envision a range of useful applications.

It is well established that a robot's visual appearance plays a significant role in how it is perceived. Considerable time and resources are usually dedicated to help ensure that the visual aesthetics of social robots are pleasing to users and helps facilitate clear communication. However, relatively little consideration is given to how the voice of the robot should sound, which may have adverse effects on acceptance and clarity of communication. In this study, we explore the mental images people form when they hear robots speaking. In our experiment, participants listened to several voices, and for each voice they were asked to choose a robot, from a selection of eight commonly used social robot platforms, that was best suited to have that voice. The voices were manipulated in terms of naturalness, gender, and accent. Results showed that a) participants seldom matched robots with the voices that were used in previous HRI studies, b) the gender and naturalness vocal manipulations strongly affected participants' selection, and c) the linguistic content of the utterances spoken by the voices does not affect people's selection. This finding suggests that people associate voices with robot pictures, even when the content of spoken utterances was unintelligible. Our findings indicate that both a robot's voice and its appearance contribute to robot perception. Thus, giving a mismatched voice to a robot might introduce a confounding effect in HRI studies. We therefore suggest that voice design should be considered more thoroughly when planning spoken human-robot interactions.

Pneumatic artificial muscles (PAMs) have been researched for applications in powered exoskeletons, orthosis and robotics. Their high force to mass ratio, low cost and inherent compliance are particularly advantageous for systems requiring physical interaction with humans.Sleeve PAMs, which introduce an internal structure to the actuator, offer improved force capacity, contraction ratio, efficiency and operating bandwidth. In this paper sleeve PAMs are applied to a popular muscle configuration; that of a joint operated antagonistically by two muscles. It is shown that the sleeve PAM can increases the range of joint rotation by 14% or load capacity by over 50% of that of a comparable joint actuated with traditional PAMs, depending on the joint configuration. The stiffness of joints actuated with both PAM types is also studied, particularly the case of closed system operation (mass of air in the PAMs is constant), where the reduced volume of the sleeve PAM significantly increases the observed stiffness. Finally energy consumption is considered, showing substantial savings in the case of joints actuated with sleeve PAMs.

There is value in exploring new robot morphologies that combine the benefits of legged robots (i.e. high terrain adaptability, humanlike form factor) with those of wheeled systems (i.e. high stability, low energy consumption). Once the basic design concept has been demonstrated, there is a further requirement to validate the controllability of the system through adaptation and implementation of advanced control techniques. This research presents a motion planner that enables the Aerobot robot, an actively articulated wheeled humanoid robot capable of performing step climbing and gap crossing, to plan dynamically stable motion in response to a range of task conditions. Using a model of the robots kinematics, a motion planner is developed. The sequential quadratic program algorithm is used to solve quadratic objectives and non-linear constraints pertaining to stability and postural configuration adjustment requirements. The results showed good tracking of the robot's Zero Moment Point while transitioning between postural configurations and traversing obstacles. During these phase transitions, robustness in maintaining balance and position is also demonstrated via velocity control of the drive wheels.

Developing advanced robots can be a resource-intensive activity that creates many challenges for research teams. There is a need to formulate new techniques for systematically designing complex robot systems, especially in cases where high adaptability is needed and design metrics cannot be explicitly specified in advance. This research explores how the Goals/Questions/Metrics (GQM) method, a well-established technique for process measurement, can be modified for use as a design tool in robotics. To illustrate how a design-orientated GQM method may be used in practice, a sample use-case is given detailing how the approach was applied to the task of developing a bespoke robotic gripper for a service robot. The study provides an early indication that the adoption of GQM principles by designers can have significant benefits in robotics applications. However, further investigation is needed to better understand the magnitude and scope of any improvements.