Despite the nuclear industry’s reliance on advanced robots being operated by humans, much of the existing research overlooks the operator’s perspective in the context of nuclear decommissioning. This study aims to address this gap by identifying the specific needs and requirements of robot operators in nuclear environments. Three focus groups of experienced robot operators from the UK Atomic Energy Authority and Sellafield Ltd. were conducted to explore key themes, including the operator’s role, tasks where robots are employed, and the risks associated with robot use. Findings reveal that: (1) robots in critical tasks are typically controlled by a team of operators; (2) for human-robot interfaces safety and reliability are the most important features, before effectiveness, intuitiveness and task focus; (3) due to high task variety operators see a need for various types of robots; and (4) operator error is regarded as the most significant and unpredictable risk. Based on these insights, a comprehensive set of 10 robot-specific requirements and 10 overall user requirements has been formulated. The paper provides recommendations for robot operators and designers, detailing how these identified requirements can inform the development of future teleoperated robots for nuclear decommissioning tasks.

This paper explores the design and development of a folding robot required to survey and characterize nuclear facilities only accessible via 150 mm diameter entry ducts. The enclosed legacy facilities at old nuclear sites like Sellafield in the UK have this sort of limited access. When a site reaches the end of its operational life, it must be decommissioned and the resulting waste material must be safely disposed of. The condition, radioactive characteristics, and accessibility of the enclosed environments are unknown; for decommissioning to occur, these environments must be mapped and characterized. For a robot to carry out this task, one of the key requirements is the ability of the robot to traverse rough terrain and obstacles that could be found inside the facility. To accommodate this, while fitting through the entry duct, the chosen design utilizes morphing whegs (i.e., wheel-legs) for locomotion. These are shape-changing wheels that can open out into a set of legs that rotate around an axle, allowing greater traction, diameter, and object traversal ability than wheels alone. The design and morphology of a folding morphing-wheg robot for nuclear characterization, as well as the manufacture and testing of a prototype, is discussed in this paper. A preliminary evaluation of the robot has shown it is capable of climbing up a maximum step height of 150 mm while having a wheel dimension of 100 mm and being able to fit through a 150 mm duct.

Thailand, as well as many other countries world-wide, is facing a shortage of medical staff. We purpose a solution to improve medical services in health centres: a robot teleoperation system to allow patients to consult with doctors from public hospitals, and for doctors to examine and make decisions about their required care. To develop such a system, a user-centred design (UCD) process is followed. Here we present an important first step in this process to establish user requirements for such a system. Hence, we have conducted a focus group with Thai medical staff from Banphaeo General Hospital and an online survey with potential patients. An online collaborative board has been setup to facilitate running the focus group virtually and provide an effective tool to gather data. A qualitative data is then analysed using a framework analysis. Based on this work, we present a list of user requirements for doctors, patients and assistants and discuss how the collected requirements can be transferred into technical specifications of the system. Our study found that communication among different user groups is the most important requirement.

Social isolation is an issue that effects many people, especially those from ethic minorities, LGBTQIA+ communities, the elderly, those in long-term healthcare, and those living with life-limiting illnesses. It has become increasingly evident during the pandemic, when mental health issues have soared, and the importance of interacting with loved ones has been highlighted. While telecommunication software helped a great deal in these unprecedented circumstances, it does not allow for navigation in remote environments, and lacks high level interactions found in face-to-face communication. Therefore, this system has been developed to address these issues, and this study was being conducted to test the technical usability of the system when being used by healthy participants. It was found that 720p is the highest resolution that can be applied before the camera delay becomes unusable; though participants suggested that they would like the option to switch to 2k resolution should they be looking close up without moving. In addition, it became apparent that overall the participants were positive about the system, but would prefer a less bulky head-mounted display, and that the choice of which robot to use with the system (Nao or Pepper) was entirely down to individual preference based on the task being completed.

In this paper we apply the recent concept of robot Ethical Risk Assessment to an exemplar Socially Assistive Robot (SAR); specifically considering ethical risks posed by anthropomorphism in this context. We draw on two complimentary studies to demonstrate that anthropomorphism is important to overall SAR function and overall relatively low ethical risk. As such, rather than avoiding anthropomoprhism all together (as suggested in a recently published standard on robot ethics), we suggest anthropomorphism in SARs should be a customisable trait that can be adapted to the user.

Body language is an important aspect of human communication, which an effective human-robot interaction interface should mimic well. Human beings exchange information and convey their thoughts and feelings through gaze, facial expressions, body language, and tone of voice along with spoken words, and infer 65% of the meaning of the communicated messages from these nonverbal cues. Modern robotic platforms are, however, limited in their ability to automatically generate behaviors that align with their speech. In this article, we develop a neural-network-based system that takes audio from a user as an input and generates upper-body gestures, including head, hand, and torso movements of the user on a humanoid robot, namely, Softbank Robotics' Pepper. Our system was evaluated quantitatively as well as qualitatively using Web surveys when driven by natural speech and synthetic speech. We compare the impact of generic and person-specific neural-network models on the quality of synthesized movements. We further investigate the relationships between quantitative and qualitative evaluations and examine how the speaker's personality traits affect the synthesized movements.

This study investigated whether virtual reality could be used as platform for conducting human-robot interaction user studies. It was investigated whether user studies performed in virtual reality elicited realistic responses from participants. To answer this question, a real world study was replicated as closely as possible in virtual reality, where a robot tour guide asked participants to keep a secret. The experiment consisted of a virtual museum tour where the robot acted as the tour guide while displaying either social or non-social behaviour. The measurements taken in this study were the objective measurement whether the participants kept the robot's secret or not. Questionnaires were taken to investigate participants' perception of the robot and its feelings, as well as their experienced level of presence and their tendency to become immersed in the virtual environment. Results show that the participants responded differently in the virtual reality study when compared to the original real world study, where the secret was kept more often for the non-social robot, but less often for the social robot. In both the original and replicated study a strong, positive correlation was found between participants' perception of the robot as a social being and their tendency to keep the robot's secret. These inconclusive findings, some changes that were required for the virtual environment compared to the original study, and different participant demographics indicate that more work is needed to determine whether virtual reality can be used as a tool to conduct human-robot interaction experiments.

There will always be occasions where robots require assistance from humans. Understanding what motivates people to help a robot, and what effect this interaction has on an individual will be essential in successfully integrating robots into our society. Emotions are important in motivating prosocial behavior between people, and therefore may also play a large role in human-robot interaction. This research explores the role of emotion in motivating people to help a robot and some of the ethical issues that arise as a result, with the ultimate aim of developing suitable methods for robots to interact with humans to acquire assistance.

In this paper we present the results of an experimental study investigating the application of human persuasive strategies to a social robot. We demonstrate that robot displays of goodwill and similarity to the participant significantly increased robot persuasiveness, as measured objectively by participant behaviour. However, such strategies had no impact on subjective measures concerning perception of the robot, and perception of the robot did not correlate with participant behaviour. We hypothesise that this is due to difficulty in accurately measuring perception of a robot using subjective measures. We suggest our results are particularly relevant for the design and development of socially assistive robots.

Previous work on ethical machine reasoning has largely been theoretical, and where such systems have been implemented, it has, in general, been only initial proofs of principle. Here, we address the question of desirable attributes for such systems to improve their real world utility, and how controllers with these attributes might be implemented. We propose that ethically critical machine reasoning should be proactive, transparent, and verifiable. We describe an architecture where the ethical reasoning is handled by a separate layer, augmenting a typical layered control architecture, ethically moderating the robot actions. It makes use of a simulation-based internal model and supports proactive, transparent, and verifiable ethical reasoning. To do so, the reasoning component of the ethical layer uses our Python-based belief-desire-intention (BDI) implementation. The declarative logic structure of BDI facilitates both transparency, through logging of the reasoning cycle, and formal verification methods. To prove the principles of our approach, we use a case study implementation to experimentally demonstrate its operation. Importantly, it is the first such robot controller where the ethical machine reasoning has been formally verified.

In this paper we present the results of a qualitative study with therapists to inform social robotics and human robot interaction (HRI) for engagement in rehabilitative therapies. Our results add to growing evidence that socially assistive robots (SARs) could play a role in addressing patients' low engagement with self-directed exercise programmes. Specifically, we propose how SARs might augment or offer more pro-active assistance over existing technologies such as smartphone applications, computer software and fitness trackers also designed to tackle this issue. In addition, we present a series of design implications for such SARs based on therapists' expert knowledge and best practices extracted from our results. This includes an initial set of SAR requirements and key considerations concerning personalised and adaptive interaction strategies.

Mimicry of social behaviours is an imitation behaviour among humans that benefits building rapport, teamwork and aids blending into social situations. As social robots become more popular, these are aspects that gain importance in robotic behaviour designs. A key part of human communication to which mimicry might be applied is co-verbal gesture, which we have investigated. In our proposed system dynamic cues are extracted from human gestures and adapted to a robot's gesture motion. We have conducted empirical studies to validate this mimicry approach. Our results support that the concept of imitating gesture features is a successful method for robotic gesture mimicry, which can be helpful to support human-robot cooperation and building rapport.

In this paper we investigate robot to human Interpersonal Emotion Transfer (IET) in a real world contextualised human-robot interaction (HRI). IET is an umbrella term which describes the impact of emotions in human-human interaction (HHI). This includes emotion contagion and social appraisal effects. These effects are particularly relevant in domains such as teaching, sports, exercise and healthy eating; domains increasingly targeted by socially assistive robotics. As such, we suggest socially assistive robots may benefit from affective communication in the same way as their human counterparts. We show that emotion recognition from robot voice and motion is possible in explicit validation experiments but does not hold in a socially assistive interaction. Our findings suggest that robot to human IET relies on the human having an expectation for, and hence recognition of, robot emotions; mimicry of valanced motion is not sufficient.

Nowadays a significant part of human-human interaction takes place over distance. Tele-operated robot avatars, in which an operator's behaviours are portrayed by a robot proxy, have the potential to improve distance interaction, e.g., improving social presence and trust. However, having communication mediated by a robot changes the perception of the operator's appearance and behaviour, which have been shown to be used alongside vocal cues in judging personality. In this paper we present a study that investigates how robot mediation affects the way the personality of the operator is perceived. More specifically, we aim to investigate if judges of personality can be consistent in assessing personality traits, can agree with one another, can agree with operators' self-assessed personality, and shift their perceptions to incorporate characteristics associated with the robot's appearance. Our experiments show that (i) judges utilise robot appearance cues along with operator vocal cues to make their judgements, (ii) operators' arm gestures reproduced on the robot aid personality judgements, and (iii) how personality cues are perceived and evaluated through speech, gesture and robot appearance is highly operator-dependent. We discuss the implications of these results for both tele-operated and autonomous robots that aim to portray personality.

In this paper we show empirically that highly humanlike robots make thoughts of death more accessible, leading to perceptions of uncanniness and eeriness of such robots. Rather than reducing the humanlikeness of robots, our research suggests the addition of emotion displays to decrease a sense of uncanniness. We show that a highly humanlike robot displaying emotions in a social context reduces death-thought accessibility (DTA), which in turn reduces uncanniness. In a pre-test with N = 95 participants, we established that not all humanoid robots elicit thoughts of death and that the extent to which a robot appears humanlike may be linked to DTA. In our Main Study, N = 44 participants briefly interacted with a highly humanlike robotic head that either showed appropriate basic emotions or reacted by blinking. The display of emotions significantly reduced perceptions of uncanniness, which was mediated by a corresponding reduction in DTA. Implications for the design of humanoid robots are proposed.

In this paper, we report a breaching study to explore the use of a tele-operated humanoid avatar from both the perspective of the robot operator and the perspective of interlocutors. Humanoid robot avatars provide capabilities that video conferencing and mobile remote presence devices lack, particularly in multi-party conversations. Specifically, we were interested whether new users encountering a tele-operated humanoid avatar in a public setting would spontaneously use head movements and arm gestures to allow better conversational flow and group interaction. Video data shows that both operators and interlocutors initially explore the system's capabilities. Most operators used social gestures such as waving and pointing, as well as gaze which in turn led to related social responses from interlocutors. Interview data additionally show that robot operators and interlocutors rated the experience very positively. This paper discusses the implications of our findings for the design of `in the wild' experiments and the usability of tele-operated humanoid avatars.

Emphasis, by means of either pitch accents or beat gestures (rhythmic co-verbal gestures with no semantic meaning), has been shown to serve two main purposes in human communication: syntactic disambiguation and salience. To use beat gestures in this role, interlocutors must be able to integrate them with the speech they accompany. Whether such integration is possible when the multi-modal communication information is produced by a humanoid robot, and whether it is as efficient as for human communicators, are questions that need to be answered to further understanding of the efficacy of humanoid robots for naturalistic human-like communication.

Co-verbal gestures are an important part of human communication, improving its efficiency for information conveyance. A key component of such improvement is the observer's ability to integrate information from the two communication channels, speech and gesture. Whether such integration also occurs when the multi-modal communication information is produced by a humanoid robot, and whether it is as efficient as for a human communicator, is an open question. Here, we present an experiment which, using a fully within subjects design, shows that for a range of iconic gestures, speech and gesture integration occurs with similar efficiency for human and for robot communicators. The gestures for this study were produced on an Aldebaran Robotics NAO robot platform with a Kinect based tele-operation system. We also show that our system is able to produce a range of iconic gestures that are understood by participants in unimodal (gesture only) communication, as well as being efficiently integrated with speech. Hence, we demonstrate the utility of iconic gestures for robotic communicators.

This paper represents the first steps in investigating issues emerging from a scenario where a robot interacts with a group of people around an interactive tabletop. In particular, the impact that a humanoid robot, acting as an avatar for a remote member of the group, has on the collaboration between the members of the group is investigated. This is carried out in the context where the avatar is depicting the actions being carried out by the remote user during a game. A preliminary study was performed to find out how the users interact when they are all co-located. The experiment is then carried out in two variants, in the first, a member of the group is moved to a remote location and allowed to interact with the other members using audio support alone. In the second, a robot is used to represent the actions of the remote user to the co-located users. The results obtained indicate that the addition of an avatar, used in such a way, has a positive impact on group interaction and allows for the task to be completed more successfully than when the avatar is not used. Further, comparative analysis of videos of the group behavior with a co-located team and group behavior with one member represented by the robot avatar, showed similar cooperative action.

Living organisms are complex systems, and yet they possess extremely high degrees of reliability. Since failures are local, their repair will often be taken on the local (cell) level. Engineers have long sought systems that could offer similar reliability and have relatively recently started trying to integrate ideas inspired by nature into the modern silicon technology of today. While bio-inspired proposals inspired by multicellular systems demonstrated feasibility, the resulting systems were often unduly complex. We are proposing a radically new methodology inspired by the characteristics, morphology, and behavior of simpler prokaryotic bacteria and bacterial communities. The hypothesis we use is that such simple unicellular organisms could help to build simpler cost effective systems, but with improved reliability than hitherto achieved by other methods. The result is a cellular array-based fault-tolerant electronic system with online self-test and self-repair capability. These ideas are simulated, tested, and verified through the successful construction of demonstrators: a proportional, integral, and differential and a robot controller. This paper discusses the underlying biological principles that guide our research and the bio-inspired model that we have derived. It also gives a detailed circuit and system description of the architecture and its run-time self-diagnostic and self-repair capability.

In this paper we have investigated the efficacy of applying multi-objective optimisation to Cartesian genetic programming (CGP) when used for evolution of cell-array configurations. A cell-array is a proposed type of custom FPGA, where digital circuits can be formed from interconnected configurable cells; thus, the CGP nodes are more complex than in its standard implementation. We have described modifications to a previously described optimisation algorithm that has led to significant improvements in performance; circuits close to a hand designed equivalent have been found, in terms of the optimised objectives. Additionally we have investigated the effect of circuit decomposition techniques on evolutionary performance. We found that using a hybrid of input and output decomposition techniques substantial reductions in evolution time were observed. Further, while the number of circuit inputs is the key factor for functional evolution time, the number of circuit outputs is the key factor for optimisation time.

Cooperative gestures are a key aspect of human-human pro-social interaction. Thus, it is reasonable to expect that endowing humanoid robots with the ability to use such gestures when interacting with humans would be useful. However, while people are used to responding to such gestures expressed by other humans, it is unclear how they might react to a robot making them. To explore this topic, we conducted a within-subjects, video based laboratory experiment, measuring time to cooperate with a humanoid robot making interactional gestures. We manipulated the gesture type (beckon, give, shake hands), the gesture style (smooth, abrupt), and the gesture orientation (front, side). We also employed two measures of individual differences: negative attitudes toward robots (NARS) and human gesture decoding ability (DANVA2-POS). Our results show that people cooperate with abrupt gestures more quickly than smooth ones and front-oriented gestures more quickly than those made to the side, people's speed at decoding robot gestures is correlated with their ability to decode human gestures, and negative attitudes toward robots is strongly correlated with a decreased ability in decoding human gestures.

In order for anthropomorphic robots to communicate with people in a human-like way they need to produce gestures along with speech. Beat gestures are a key category of gestures, accompanying emphasis and timing of talk. The standard approach for autonomously adding gestures to speech for artificial agents to perform, is to identify when gestures should occur, and then select appropriate movements from a prewritten library. However, selecting naively from a library is unlikely to result in particularly human-like gesture sequences. In order to obtain examples of engaging human beat gestures, we studied videos of chat show hosts. Our analysis reveals rules for the creation of human-like beat gestures. We have combined these rules with hand scripted non-beat gestures, to produce a monologue with a complete set of accompanying gestures; it is designed for performance by our humanoid robot BERTI. In order to test the gestures produced we carried out a pilot study at the London Science Museum. The results of the study indicate that having correctly designed gesture sequences improves observer engagement.

The human sciences have demonstrated that gesture is a critical element of human communication. While existing graphical solutions are appropriate for virtual agents, solving arm trajectories for physically embodied robots requires that we consider the challenges of robot dynamics within a realtime gesture framework. We explore and evaluate a low computational-cost gesture production algorithm that can generate adequate gesture trajectories in a humanoid torso, as judged by participants in Human-Robot gesturing studies presented in this paper. Our approach produces a constrained inverse-kinematic solution for the start and end points, and generates appropriate wrist angles. Gesture time is used to calculate the joint accelerations to give a smooth, direct hand movement. Selecting open hand gestures as an example gesture sub-domain, we implement our controller on BERTI, a bespoke upper-torso humanoid robot (Fig. 2). A qualitative pilot study highlights gesture features salient to users: gesture shape, timing, naturalness and smoothness. A controlled experimental study then demonstrates that, by these metrics, our algorithm performs well; despite some dissimilarities with users' own gestures. We establish some salient points of robot gestures based on these studies.