27 research outputs found

    Transparency, teleoperation, and children's understanding of social robots

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    Teleoperation or Wizard-of-Oz control of social robots is commonly used in human-robot interaction (HRI) research. This is especially true for child-robot interactions, where technologies like speech recognition (which can help create autonomous interactions for adults) work less well. We propose to study young children's understanding teleoperation, how they conceptualize social robots in a learning context, and how this affects their interactions. Children will be told about the teleoperator's presence either before or after an interaction with a social robot. We will assess children's behavior, learning, and emotions before, during, and after the interaction. Our goal is to learn whether children's knowledge about the teleoperator matters (e.g., for their trust and for learning outcomes), and if so, how and when it matters most (e.g. at what age)

    Creating robotic characters for long-term interaction

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    Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 177-181).Researchers studying ways in which humans and robots interact in social settings have a problem: they don't have a robot to use. There is a need for a socially expressive robot that can be deployed outside of a laboratory and support remote operation and data collection. This work aims to fill that need with DragonBot - a platform for social robotics specifically designed for long-term interactions. This thesis is divided into two parts. The first part describes the design and implementation of the hardware, software, and aesthetics of the DragonBot-based characters. Through the use of a mobile phone as the robot's primary computational device, we aim to drive down the hardware cost and increase the availability of robots "in the wild". The second part of this work takes an initial step towards evaluating DragonBot's effectiveness through interactions with children. We describe two different teleoperation interfaces for allowing a human to control DragonBot's behavior differing amounts of autonomy by the robot. A human subject study was conducted and these interfaces were compared through a sticker sharing task between the robot and children aged four to seven. Our results show that when a human operator is able to focus on the social portions of an interaction and the robot is given more autonomy, children treat the character more like a peer. This is indicated by the fact that more children re-engaged the robot with the higher level of autonomy when they were asked to split up stickers between the two participants.by Adam Setapen.S.M

    Socially guided machine learning

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2006.Includes bibliographical references (p. 139-146).Social interaction will be key to enabling robots and machines in general to learn new tasks from ordinary people (not experts in robotics or machine learning). Everyday people who need to teach their machines new things will find it natural for to rely on their interpersonal interaction skills. This thesis provides several contributions towards the understanding of this Socially Guided Machine Learning scenario. While the topic of human input to machine learning algorithms has been explored to some extent, prior works have not gone far enough to understand what people will try to communicate when teaching a machine and how algorithms and learning systems can be modified to better accommodate a human partner. Interface techniques have been based on intuition and assumptions rather than grounded in human behavior, and often techniques are not demonstrated or evaluated with everyday people. Using a computer game, Sophie's Kitchen, an experiment with human subjects provides several insights about how people approach the task of teaching a machine. In particular, people want to direct and guide an agent's exploration process, they quickly use the behavior of the agent to infer a mental model of the learning process, and they utilize positive and negative feedback in asymmetric ways.(cont.) Using a robotic platform, Leonardo, and 200 people in follow-up studies of modified versions of the Sophie's Kitchen game, four research themes are developed. The use of human guidance in a machine learning exploration can be successfully incorporated to improve learning performance. Novel learning approaches demonstrate aspects of goal-oriented learning. The transparency of the machine learner can have significant effects on the nature of the instruction received from the human teacher, which in turn positively impacts the learning process. Utilizing asymmetric interpretations of positive and negative feedback from a human partner, can result in a more efficient and robust learning experience.by Andrea Lockerd Thomaz.Ph.D

    Aerospace medicine and biology: A continuing bibliography with indexes (supplement 376)

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    This bibliography lists 265 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during Jun. 1993. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

    Robotics 2010

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    Without a doubt, robotics has made an incredible progress over the last decades. The vision of developing, designing and creating technical systems that help humans to achieve hard and complex tasks, has intelligently led to an incredible variety of solutions. There are barely technical fields that could exhibit more interdisciplinary interconnections like robotics. This fact is generated by highly complex challenges imposed by robotic systems, especially the requirement on intelligent and autonomous operation. This book tries to give an insight into the evolutionary process that takes place in robotics. It provides articles covering a wide range of this exciting area. The progress of technical challenges and concepts may illuminate the relationship between developments that seem to be completely different at first sight. The robotics remains an exciting scientific and engineering field. The community looks optimistically ahead and also looks forward for the future challenges and new development

    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

    TECHNOLOGY STRATEGY FOR DEVELOPING THE ASSISTIVE ROBOTICS MARKET

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    Robotics has increased productivity in industries such as manufacturing, defence and construction but less so in healthcare where, despite the pressures from demographic changes, barriers to the adoption of assistive robotics (AR) persist. Due to the cutting-edge nature of the technology, the field requires studies that explore how it is developed and applied, effectively resulting in the development of an AR market in healthcare. Therefore, the research question for this thesis is ‘What strategy can be adopted to develop the AR market?’ This thesis adopted a Collaborative Action Research methodology to explore the development of an AR market in one UK region (Cornwall), and through this experience develop a Technology Strategy for building and orchestrating the creation of AR markets in other regions. This thesis is based on interdisciplinary research that draws from fields such as business management, entrepreneurship policy, robotics development and evaluation, and health technology adoption research. The intervention in Cornwall focussed on two key market constituents: the healthcare sector and producers (suppliers, i.e. firms and developers). The main work with the healthcare sector focused on supporting the AR adoption process. To this end, 35 events in Cornwall were used to raise awareness of AR, exploring healthcare challenges and the sector’s role in co-creation activities. The main work with the producers was to identify market barriers while actively supporting them in the product development process. Here, 28 AR companies in total from the UK, Ireland, the US, France and China working at different business stages were supported as part of this activity. Eight case studies were generated, including two completed trials of AR and two external strategic partnerships. An entrepreneurship programme that supported 58 entrepreneurs was designed, creating four robotic start-ups for the region. Finally, a lab for the evaluation of AR technologies to support companies was also established. Through the work with the healthcare sector, this thesis identified a lack of awareness of the AR market and the critical role that the sector plays in its development process. On the supply side, this thesis explored the main market barriers, including a lack of specialized agencies at a planning level, a fragmented healthcare sector that inhibits entrepreneurship, and outdated governmental policies for technology-based innovations. Overall, the findings confirmed a complete lack of preparedness and a need for changing traditional methods that are blocking innovation. Building upon these findings, this thesis presents a Technology Strategy for the creation of AR markets. The strategy offers practical recommendations on how regions can build and benefit from AR development. Through co-creation and open innovation principles, the strategy establishes key market actors and the multilateral nature of relationships between them. It also details a complete entrepreneurship programme to create companies for the region and business platforms to start the AR market. For the healthcare sector, it describes a complete AR knowledge awareness programme to guide the engagement with the sector. For the producers, it presents best practices and a new model for the development of AR technologies. This is the first study of its kind to offer a sector-specific Technology Strategy for the emerging AR market, aiming to improve the consolidation of this sector. The strategy could be used in regions that share characteristics with Cornwall, but its applicability to other regions is also worth exploring

    Socially assistive robots : the specific case of the NAO

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    Numerous researches have studied the development of robotics, especially socially assistive robots (SAR), including the NAO robot. This small humanoid robot has a great potential in social assistance. The NAO robot’s features and capabilities, such as motricity, functionality, and affective capacities, have been studied in various contexts. The principal aim of this study is to gather every research that has been done using this robot to see how the NAO can be used and what could be its potential as a SAR. Articles using the NAO in any situation were found searching PSYCHINFO, Computer and Applied Sciences Complete and ACM Digital Library databases. The main inclusion criterion was that studies had to use the NAO robot. Studies comparing it with other robots or intervention programs were also included. Articles about technical improvements were excluded since they did not involve concrete utilisation of the NAO. Also, duplicates and articles with an important lack of information on sample were excluded. A total of 51 publications (1895 participants) were included in the review. Six categories were defined: social interactions, affectivity, intervention, assisted teaching, mild cognitive impairment/dementia, and autism/intellectual disability. A great majority of the findings are positive concerning the NAO robot. Its multimodality makes it a SAR with potential
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