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This paper proposes a novel telemanipulation system that enables a human operator to control a dual-arm robot. The operation provides kinesthetic teaching via a digital twin of the robot which the operator cyber-physically guides to perform a task. Its key enabler is the concept of a virtual reality interactive marker, which serves as a simplified end effector of the digital twin robot. In virtual reality, the operator can interact with the marker using bare hands, which are sensed by the Leap Motion on top of a virtual reality headset. Then, the status (e.g. position/orientation) of the marker is transformed to the corresponding joint space command to the remote robot so that its end effector can follow the marker. We provide the details of the system architecture, and implement the system based on commercial robots/devices (i.e. UR5, Robotiq gripper, Leap Motion), virtual reality, ROS, and Unity3D. Moreover, the paper discusses the technical challenges that we had to address, and the system’s potential benefits from a human-robot interaction perspective.

As robots become more prevalent, particularly in complex public and domestic settings, they will be increasingly challenged by dynamic situations that could result in performance errors. Such errors can have a harmful impact on a user’s trust and confidence in the technology, potentially reducing use and preventing full realization of its benefits. A potential countermeasure, based on social psychological concepts of trust, is for robots to demonstrate self-awareness and ownership of their mistakes to mitigate the impact of errors and increase users’ affinity towards the robot. We describe an experiment examining 326 people’s perceptions of a mobile guide robot that employs synthetic social behaviours to elicit trust in its use after error. We find that a robot that identifies its mistake, and communicates its intention to rectify the situation, is considered by observers to be more capable than one that simply apologizes for its mistake. However, the latter is considered more likeable and, uniquely, increases people’s intention to use the robot. These outcomes highlight that the complex and multifaceted nature of trust in human–robot interaction may extend beyond established approaches considering robots’ capability in performance and indicate that social cognitive models are valuable in developing trustworthy synthetic social agents.

The Principles of Robotics were outlined by the EPSRC in 2010. They are aimed at regulating robots in the real world. This paper represents a response to principle number four which reads: “Robots are manufactured artefacts. They should not be designed in a deceptive way to exploit vulnerable users; instead their machine nature should be transparent”. The following critique questions the principle's validity by asking whether it is correct as a statement about the nature of robots, and the relationship between robots and people. To achieve this, the principle is broken down into the following two main component statements: 1 “Robots should not be designed in a deceptive way to exploit vulnerable users”, and, 2 “Machine nature should be transparent”. It is argued that both of the component statements that make up this principle are fundamentally flawed because of the undefined nature of the critical terms: “deceptive”, “vulnerable”, and “machine nature”, and that as such the principle as a whole is misleading.

People experience and understand cyber security differently. Our ongoing work aims to address the fundamental challenge of how we can understand a diverse range of cyber security experiences, attitudes and behaviours in order to design better, more effective cyber security services and educational materials. In this paper, we take a lifespan approach to study the language of cyber security across three main life stages - young people, working age, and older people. By applying text feature extraction and analysis techniques to lists of cyber security features generated by each age group, we illustrate the differential language of cyber security across the lifespan and discuss the implications for design and research in HCI.

The advent of sophisticated robotics and AI technology makes sending humans into hazardous and distant environments to carry out inspections increasingly avoidable. Being able to send a robot, rather than a human, into a nuclear facility or deep space is very appealing. However, building these robotic systems is just the start and we still need to carry out a range of verification and validation tasks to ensure that the systems to be deployed are as safe and reliable as possible. Based on our experience across three research and innovation hubs within the UK’s “Robots for a Safer World” programme, we present an overview of the relevant techniques and challenges in this area. As the hubs are active across nuclear, offshore, and space environments, this gives a breadth of issues common to many inspection robots.

Autonomous systems are increasingly being used in safety-and mission-critical domains, including aviation, manufacturing, healthcare and the automotive industry. Systems for such domains are often verified with respect to essential requirements set by a regulator, as part of a process called certification. In principle, autonomous systems can be deployed if they can be certified for use. However, certification is especially challenging as the condition of both the system and its environment will surely change, limiting the effective use of the system. In this paper we discuss the technological and regulatory background for such systems, and introduce an architectural framework that supports verifiably-correct dynamic self-certification by the system, potentially allowing deployed systems to operate more safely and effectively.

Smartphones are now ubiquitous and valuable in many professions and yet have also been blamed for creating an ‘always on' culture, blurring boundaries between work and home. Research has shown that checking e-mails out-of-hours via computer makes workers feel more overloaded with work but also increases their sense of coping. A total of 94 participants completed a survey exploring whether the same pattern would emerge for accessing e-mail on smartphones, showing that those who use smartphones for work e-mail experienced lower levels of overload, but not coping, and push notifications were associated with greater use of smartphones for e-mail. However, there were no significant correlations between coping or overload and e-mail use or quantity, suggesting that lower overload is not due to the ability to processes or read more e-mails outside of work.

This paper explores three fundamental attributes of the Robokind Zeno-R25 (its status as person or machine, its ‘gender’, and intensity of its simulated facial expressions) and their impact on children’s perceptions of the robot, using a one-sample study design. Results from a sample of 37 children indicate that the robot is perceived as being a mix of person and machine, but also strongly as a male figure. Children could label emotions of the robot’s simulated facial-expressions but perceived intensities of these expressions varied. The findings demonstrate the importance of establishing fundamentals in user views towards social robots in supporting advanced arguments of social human-robot interaction.

The Expressive Agents for Symbiotic Education and Learning project explores human-robot symbiotic interaction with the aim to understand the development of symbiosis over long-term tutoring interactions. The final EASEL system will be built upon the neurobiologically grounded architecture - Distributed Adaptive Control. In this paper, we present the design of an interaction scenario to support development of the DAC, in the context of a synthetic tutoring assistant. Our humanoid robot, capable of life-like simulated facial expressions, will interact with children in a public setting to teach them about exercise and energy. We discuss the range of measurements used to explore children’s responses during, and experiences of, interaction with a social, expressive robot.

Human robot interaction (HRI) often considers the human impact of a robot serving to assist a human in achieving their goal or a shared task. There are many circumstances though during HRI in which a robot may make errors that are inconvenient or even detrimental to human partners. Using the ROBOtic GUidance and Interaction DEvelopment (ROBO-GUIDE) model on the Pioneer LX platform as a case study, and insights from social psychology, we examine key factors for a robot that has made such a mistake, ensuring preservation of individuals’ perceived competence of the robot, and individuals’ trust towards the robot. We outline an experimental approach to test these proposals.

Here we present MIRO, a companion robot designed to engage users in science and robotics via edutainment. MIRO is a robot that is biomimetic in aesthetics, morphology, behaviour, and control architecture. In this paper, we review how these design choices affect its suitability for a companionship role. In particular, we consider how MIRO's emulation of familiar mammalian body language as one component of a broader biomimetic expressive system provides effective communication of emotional state and intent. We go on to discuss how these features contribute to MIRO's potential in other domains such as healthcare, education, and research.

Robotic assistants operating in multi-floor buildings are required to use lifts to transition between floors. To reduce the need for environments to be tailored to suit robots, and to make robot assistants more applicable, it is desirable that they should make use of existing navigational cues and interfaces designed for human users. In this paper, we examine the scenario whereby a guide robot uses a lift to transition between floors in a building. We describe an experiment into combining multiple data sources, available to a typical robot with simple sensors, to determine which floor of the building it is on. We show the robustness of this approach to realistic scenarios in a busy working environment.

Observational studies of situated displays have suggested that they are rarely looked at, and when they are it is typically only for a short period of time. Using a mobile eye tracker during a realistic shopping task in a shopping center, we show that people look at displays more than would be predicted from these observational studies, but still only short glances and often from quite far away. We characterize the patterns of eye-movements that precede looking at a display and discuss some of the design implications for the design of situated display technologies that are deployed in public space.

In this paper we describe a novel scenario, whereby an assistive robot is required to use a lift, and results from a preliminary investigation into floor determination using readily-available information. The aim being to create an assistive robot that can naturally integrate into existing infrastructure.

The dramatic rise in the use of social network sites (SNS) has resulted in a number of users feeling stressed about the extent of their personal use. Previous work has established that daily retrospective estimations of SNS use and access to RescueTime not only improve accuracy of estimations but also reduce perceived stress. The present study aimed to extend this by also exploring the influence of prospective estimations on stress and perceived time management. However, the study was thwarted by incredibly low engagement with RescueTime and consequently, no improvement in estimation accuracy and no reduction in stress. This indicates substantial individual differences in engagement and a requirement for external sources of motivation for using personal informatics, beyond the tasks of the study.

Contemporary robot design is influenced both by task domain (e.g., industrial manipulation versus social interaction) as well as by classification differences in humans (e.g., therapy patients versus museum visitors). As the breadth of robot use increases, we ask how will people respond to the ever increasing number of intelligent artefacts in their environment. Using the Paro robot as our case study we propose an analysis of individual differences in HRI to highlight the consequences individual characteristics have on robot performance. We discuss to what extent human-human interactions are a useful model of HRI.

The Expressive Agents for Symbiotic Education and Learning (EASEL) project will explore human-robot symbiotic interaction (HRSI) with the aim of developing an understanding of symbiosis over long term tutoring interactions. The EASEL system will be built upon an established and neurobiologically grounded architecture - Distributed Adaptive Control (DAC). Here we present the design of an initial experiment in which our facially expressive humanoid robot will interact with children at a public exhibition. We discuss the range of measurements we will employ to explore the effects our robot’s expressive ability has on interaction with children during HRSI, with the aim of contributing optimal robot personality parameters to the final EASEL model.

Recent advances in mobile technology have had many positive effects on the ways in which people can combine work and home life. For example, having remote access enables people to work from home, or work flexible hours that fit around caring responsibilities. They also support communication with colleagues and family members, and enable digital hobbies. However, the resulting 'always-online' culture can undermine work-home boundaries and cause stress to those who feel under pressure to respond immediately to digital notifications. This workshop will explore how a socio-technical perspective, which views boundaries as being constituted by everyday socio-technical practices, can inform the design of technologies that help maintain boundaries between work and home life.

Action video game players have been found to outperform nonplayers on a variety of cognitive tasks. However, several failures to replicate these video game player advantages have indicated that this relationship may not be straightforward. Moreover, despite the discovery that problematic video game players do not appear to demonstrate the same superior performance as nonproblematic video game players in relation to multiple object tracking paradigms, this has not been investigated for other tasks. Consequently, this study compared gamers and nongamers in task switching ability, visual short-term memory, mental rotation, enumeration, and flanker interference, as well as investigated the influence of self-reported problematic video game use. A total of 66 participants completed the experiment, 26 of whom played action video games, including 20 problematic players. The results revealed no significant effect of playing action video games, nor any influence of problematic video game play. This indicates that the previously reported cognitive advantages in video game players may be restricted to specific task features or samples. Furthermore, problematic video game play may not have a detrimental effect on cognitive performance, although this is difficult to ascertain considering the lack of video game player advantage. More research is therefore sorely needed.