112 research outputs found

    Accessibility requirements for human-robot interaction for socially assistive robots

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    Mención Internacional en el título de doctorPrograma de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: María Ángeles Malfaz Vázquez.- Secretario: Diego Martín de Andrés.- Vocal: Mike Wal

    User Experience Design and Evaluation of Persuasive Social Robot As Language Tutor At University : Design And Learning Experiences From Design Research

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    Human Robot Interaction (HRI) is a developing field where research and innovation are progressing. One domain where Human Robot Interaction has focused is in the educational sector. Various research has been conducted in education field to design social robots with appropriate design guidelines derived from user preferences, context, and technology to help students and teachers to foster their learning and teaching experience. Language learning has become popular in education due to students receiving opportunities to study and learn any interested subjects in any language in their preferred universities around the world. Thus, being the reason behind the research of using social robots in language learning and teaching in education field. To this context this thesis explored the design of language tutoring robot for students learning Finnish language at university. In language learning, motivation, the learning experience, context, and user preferences are important to be considered. This thesis focuses on the Finnish language learning students through language tutoring social robot at Tampere University. The design research methodology is used to design the persuasive language tutoring social robot teaching Finnish language to the international students at Tampere University. The design guidelines and the future language tutoring robot design with their benefits are formed using Design Research methodology. Elias Robot, a language tutoring application designed by Curious Technologies, Finnish EdTech company was used in the explorative user study. The user study involved Pepper, Social robot along with the Elias robot application using Mobile device technology. The user study was conducted in university, the students include three male participants and four female participants. The aim of the study was to gather the design requirements based on learning experiences from social robot tutor. Based on this study findings and the design research findings, the future language tutoring social robot was co-created through co design workshop. Based on the findings from Field study, user study, technology acceptance model findings, design research findings, student interviews, the persuasive social robot language tutor was designed. The findings revealed all the multi modalities are required for the efficient tutoring of persuasive social robots and the social robots persuade motivation with students to learn the language. The design implications were discussed, and the design of social robot tutor are created through design scenarios

    Advances in Human-Robot Interaction

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    Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers

    Socially Assistive Robot Enabled Home-Based Care for Supporting People with Autism

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    The growing number of people diagnosed with Autism Spectrum Disorder (ASD) is an issue of concern in Australia and many countries. In order to improve the engagement, reciprocity, productivity and usefulness of people with ASD in a home-based environment, in this paper the authors report on a 9 month Australian home-based care trial of socially assistive robot (Lucy) to support two young adults with autism. This work demonstrates that by marrying personhood (of people with ASD) with human-like communication modalities of Lucy potentially positive outcomes can be achieved in terms of engagement, productivity and usefulness as well as reciprocity of the people with ASD. Lucy also provide respite to their carers (e.g., parents) in their day to day living

    Reinforcement Learning in Autonomous Robots: An Empirical Investigation of the Role of Emotions

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    Institute of Perception, Action and BehaviourThis thesis presents a study of the provision of emotions for artificial agents with the ultimate aim of enhancing their autonomy, i.e. making them more exible, robust and self-sufficient. In recent years, the importance of emotions and their assistance to cognition has been increasingly acknowledged. Emotions are no longer considered undesirable or simply useless. Their role in various aspects of human and animal cog- nition like perception, attention, memory, decision-making and social interaction has been recognised as essential. The importance of emotions is much more evident in social interaction and therefore much of the emotions research done in artificial systems focuses on the expression and recognition of emotions. However, recent neurophysiological research suggests that emotions also play a crucial part in cognition itself. This thesis investigates ways in which artificial emotions can improve autonomous behaviour in the domain of a simple, but complete, solitary learning agent. For this purpose, a non-symbolic emotion model was designed and implemented. It takes the form of a recurrent artificial neural network where emotions influence the perception of the state of the world, on which they ultimately depend. This is done through a hormone system that acts as a persistence mechanism. This model is somewhat more sophisticated than those usually found in equivalent non-symbolic systems, yet the emotions themselves were restricted to a few simplified emotions that do not try to mimic the complexity of the human counterparts, but are afforded by the agent's interaction with the environment. Several hypotheses were investigated of how the emotion model above could be integrated in a reinforcement learning framework which, by itself, provides the base for the adaptiveness necessary for autonomy. Experiments were carried out in a realistic robot simulator that compared the performance of emotional with non-emotional agents in a survival task that consists of maintaining adequate energy levels in an environment with obstacles and energy sources. One of the most common roles attributed to emotions is as source of reinforcement and was therefore examined first. In experiments with a controller that selects between primitive actions, the reinforcement provided by emotions was found inappropriate because of the time scale discrepancies introduced by the emotion model. The reinforcement provided by emotions proved to be much more successful when used by a controller that selects between behaviours rather than actions, achieving equivalent performance to that of a standard reinforcement function. One of the crucial issues for efficient and productive learning, highlighted by the latter experiments, is to determine exactly when the controller should re-evaluate its decision concerning which behaviour to activate. The emotions proved to be particularly helpful in this role, enabling better performance with substantially less computational effort than the best suited interruption mechanism using regular time intervals. The modulation of learning parameters such as learning rate and the exploration vs. exploitation ratio was also explored. Experiments suggested that emotions might also be useful for this purpose. This research led to the conclusion that artificial emotions are a useful construct to have in the domain of behaviour-based autonomous agents, because they provide a unifying way to tackle different issues of control, analogous to natural systems' emotions

    Designing Sound for Social Robots: Advancing Professional Practice through Design Principles

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    Sound is one of the core modalities social robots can use to communicate with the humans around them in rich, engaging, and effective ways. While a robot's auditory communication happens predominantly through speech, a growing body of work demonstrates the various ways non-verbal robot sound can affect humans, and researchers have begun to formulate design recommendations that encourage using the medium to its full potential. However, formal strategies for successful robot sound design have so far not emerged, current frameworks and principles are largely untested and no effort has been made to survey creative robot sound design practice. In this dissertation, I combine creative practice, expert interviews, and human-robot interaction studies to advance our understanding of how designers can best ideate, create, and implement robot sound. In a first step, I map out a design space that combines established sound design frameworks with insights from interviews with robot sound design experts. I then systematically traverse this space across three robot sound design explorations, investigating (i) the effect of artificial movement sound on how robots are perceived, (ii) the benefits of applying compositional theory to robot sound design, and (iii) the role and potential of spatially distributed robot sound. Finally, I implement the designs from prior chapters into humanoid robot Diamandini, and deploy it as a case study. Based on a synthesis of the data collection and design practice conducted across the thesis, I argue that the creation of robot sound is best guided by four design perspectives: fiction (sound as a means to convey a narrative), composition (sound as its own separate listening experience), plasticity (sound as something that can vary and adapt over time), and space (spatial distribution of sound as a separate communication channel). The conclusion of the thesis presents these four perspectives and proposes eleven design principles across them which are supported by detailed examples. This work contributes an extensive body of design principles, process models, and techniques providing researchers and designers with new tools to enrich the way robots communicate with humans

    Conversational affective social robots for ageing and dementia support

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    Socially assistive robots (SAR) hold significant potential to assist older adults and people with dementia in human engagement and clinical contexts by supporting mental health and independence at home. While SAR research has recently experienced prolific growth, long-term trust, clinical translation and patient benefit remain immature. Affective human-robot interactions are unresolved and the deployment of robots with conversational abilities is fundamental for robustness and humanrobot engagement. In this paper, we review the state of the art within the past two decades, design trends, and current applications of conversational affective SAR for ageing and dementia support. A horizon scanning of AI voice technology for healthcare, including ubiquitous smart speakers, is further introduced to address current gaps inhibiting home use. We discuss the role of user-centred approaches in the design of voice systems, including the capacity to handle communication breakdowns for effective use by target populations. We summarise the state of development in interactions using speech and natural language processing, which forms a baseline for longitudinal health monitoring and cognitive assessment. Drawing from this foundation, we identify open challenges and propose future directions to advance conversational affective social robots for: 1) user engagement, 2) deployment in real-world settings, and 3) clinical translation

    A Sociable Humanoid Autonomous Robotic Platform (the SHARP Project): An evaluation of the G.E.N.E.S.I.S. robot as an interactive consumer robotic platform

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    The Social Humanoid Autonomous Robotic Platform (SHARP) project is an android project that was created with the intent of making learning about androids and robotics easier for the novice, diverse for the expert, educational in the classroom, and useful in the home or business. The project centers itself on its simplicity, low cost, and expandability. This paper illustrates how the SHARP Project has the potential to be an affordable fit in nearly every modern setting. The introduction of the SHARP project lays the groundwork for people of many ages, incomes, and educational levels to take advantage of robotics technology. The SHARP project features research based, in part, on a personal android project named G.E.N.E.S.I.S. as an example of the SHARP project\u27s features. The features of G.E.N.E.S.I.S. include voice recognition, speech synthesis, and responses to various sensor stimuli which help encourage human-robot interaction. This study uses survey results to examine the factors that make these robots desirable to consumers and identifies which factors make some robots more sociable than others. The study concludes with an evaluation of the G.E.N.E.S.I.S. robotic platform and suggests an appropriate market niche for this and other similar sociable humanoid robotic platforms

    NASA space station automation: AI-based technology review

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    Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

    People Can Be So Fake: A New Dimension to Privacy and Technology Scholarship

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    This article updates the traditional discussion of privacy and technology, focused since the days of Warren and Brandeis on the capacity of technology to manipulate information. It proposes a novel dimension to the impact of anthropomorphic or social design on privacy. Technologies designed to imitate people-through voice, animation, and natural language-are increasingly commonplace, showing up in our cars, computers, phones, and homes. A rich literature in communications and psychology suggests that we are hardwired to react to such technology as though a person were actually present. Social interfaces accordingly capture our attention, improve interactivity, and can free up our hands for other tasks. At the same time, technologies that imitate people have the potential to implicate long-standing privacy values. One of the well-documented effects on users of interfaces and devices that emulate people is the sensation of being observed and evaluated. Their presence can alter our attitude, behavior, and physiological state. Widespread adoption of such technology may accordingly lessen opportunities for solitude and chill curiosity and self-development. These effects are all the more dangerous in that they cannot be addressed through traditional privacy protections such as encryption or anonymization. At the same time, the unique properties of social technology also present an opportunity to improve privacy, particularly online
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