85 research outputs found

    Multiple-Robot Mediated Discussion System to support group discussion ∗

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    S. Ikari, Y. Yoshikawa and H. Ishiguro, "Multiple-Robot Mediated Discussion System to support group discussion *," 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), Naples, Italy, 2020, pp. 495-502, doi: 10.1109/RO-MAN47096.2020.9223444.The 29th IEEE International Conference on Robot & Human Interactive Communication [31 AUG - 04 SEPT, 2020

    Assessment of Society\u27s Awareness, Acceptance, and Demand for Robotic Wait Staff in Restaurant Operations

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    This research study consists of an assessment of participants\u27 awareness of robotics in general and also their acceptance and consumer demand for mobile, humanoid robots in the role of robotic waiters in restaurants. The study also includes the awareness and consumer demand for Microsoft Surface Computers to be potentially used as restaurant tables capable of electronic order entry, payment, and entertainment. The social impacts of such high technology upon the human occupation of waiter or waitress were also examined relative to the resistance to automation from current human wait staff. The overall results of the study were luke-warm demand for robotic waiters, strong demand for Microsoft Surface Computers, and resistance to robotic waiters among most wait staff

    TikTok Cyberbully Responses: Communicating the Narrative

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    This study analyzed TikTok cyberbullying response videos to understand how content creators use verbal and nonverbal communication within their performance, creating audience engagement and awareness for cyberbullying and social advocacy issues. This study was conducted with 200 TikTok creator accounts analyzing communication, performance, engagement, and analytics narrative content analysis. Codes were separated into themes that represented the creator\u27s emotional responses. These responses were analyzed to learn how the audience presented the content. The combination of narrative content analysis and analytics data was used to determine the effectiveness of the creators\u27 ability to engage with their audience and create cyberbullying and social advocacy awareness. The study found a connection between a TikTok content creator’s performance and audience engagement. The content creators with successful performances convinced their audience to engage with comments supporting anti-cyberbullying and promoting social causes. The combination of scholarly research and new media technology allows this topic to be examined through a Communications lens analyzing verbal and nonverbal communication. The research project can be helpful for academics, social advocacy groups, and those interested in TikTok content engagement

    Machine Performers: Agents in a Multiple Ontological State

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    In this thesis, the author explores and develops new attributes for machine performers and merges the trans-disciplinary fields of the performing arts and artificial intelligence. The main aim is to redefine the term “embodiment” for robots on the stage and to demonstrate that this term requires broadening in various fields of research. This redefining has required a multifaceted theoretical analysis of embodiment in the field of artificial intelligence (e.g. the uncanny valley), as well as the construction of new robots for the stage by the author. It is hoped that these practical experimental examples will generate more research by others in similar fields. Even though the historical lineage of robotics is engraved with theatrical strategies and dramaturgy, further application of constructive principles from the performing arts and evidence from psychology and neurology can shift the perception of robotic agents both on stage and in other cultural environments. In this light, the relation between representation, movement and behaviour of bodies has been further explored to establish links between constructed bodies (as in artificial intelligence) and perceived bodies (as performers on the theatrical stage). In the course of this research, several practical works have been designed and built, and subsequently presented to live audiences and research communities. Audience reactions have been analysed with surveys and discussions. Interviews have also been conducted with choreographers, curators and scientists about the value of machine performers. The main conclusions from this study are that fakery and mystification can be used as persuasive elements to enhance agency. Morphologies can also be applied that tightly couple brain and sensorimotor actions and lead to a stronger stage presence. In fact, if this lack of presence is left out of human replicants, it causes an “uncanny” lack of agency. Furthermore, the addition of stage presence leads to stronger identification from audiences, even for bodies dissimilar to their own. The author demonstrates that audience reactions are enhanced by building these effects into machine body structures: rather than identification through mimicry, this causes them to have more unambiguously biological associations. Alongside these traits, atmospheres such as those created by a cast of machine performers tend to cause even more intensely visceral responses. In this thesis, “embodiment” has emerged as a paradigm shift – as well as within this shift – and morphological computing has been explored as a method to deepen this visceral immersion. Therefore, this dissertation considers and builds machine performers as “true” performers for the stage, rather than mere objects with an aura. Their singular and customized embodiment can enable the development of non-anthropocentric performances that encompass the abstract and conceptual patterns in motion and generate – as from human performers – empathy, identification and experiential reactions in live audiences

    Social Touch

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    Interpersonal or social touch is an intuitive and powerful way to express and communicate emotions, comfort a friend, bond with teammates, comfort a child in pain, and soothe someone who is stressed. If there is one thing that the current pandemic is showing us, it is that social distancing can make some people crave physical interaction through social touch. The notion of “skin-hunger” has become tangible for many.Social touch differs at a functional and anatomical level from discriminative touch, and has clear effects at physiological, emotional, and behavioural levels. Social touch is a topic in psychology (perception, emotion, behaviour), neuroscience (neurophysiological pathways), computer science (mediated touch communication), engineering (haptic devices), robotics (social robots that can touch), humanities (science and technology studies), and sociology (the social implications of touch). Our current scientific knowledge of social touch is scattered across disciplines and not yet adequate for the purpose of meeting today's challenges of connecting human beings through the mediating channel of technology

    Human Computer Interaction and Emerging Technologies

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    The INTERACT Conferences are an important platform for researchers and practitioners in the field of human-computer interaction (HCI) to showcase their work. They are organised biennially by the International Federation for Information Processing (IFIP) Technical Committee on Human–Computer Interaction (IFIP TC13), an international committee of 30 member national societies and nine Working Groups. INTERACT is truly international in its spirit and has attracted researchers from several countries and cultures. With an emphasis on inclusiveness, it works to lower the barriers that prevent people in developing countries from participating in conferences. As a multidisciplinary field, HCI requires interaction and discussion among diverse people with different interests and backgrounds. The 17th IFIP TC13 International Conference on Human-Computer Interaction (INTERACT 2019) took place during 2-6 September 2019 in Paphos, Cyprus. The conference was held at the Coral Beach Hotel Resort, and was co-sponsored by the Cyprus University of Technology and Tallinn University, in cooperation with ACM and ACM SIGCHI. This volume contains the Adjunct Proceedings to the 17th INTERACT Conference, comprising a series of selected papers from workshops, the Student Design Consortium and the Doctoral Consortium. The volume follows the INTERACT conference tradition of submitting adjunct papers after the main publication deadline, to be published by a University Press with a connection to the conference itself. In this case, both the Adjunct Proceedings Chair of the conference, Dr Usashi Chatterjee, and the lead Editor of this volume, Dr Fernando Loizides, work at Cardiff University which is the home of Cardiff University Press

    Participant responses to virtual agents in immersive virtual environments.

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    This thesis is concerned with interaction between people and virtual humans in the context of highly immersive virtual environments (VEs). Empirical studies have shown that virtual humans (agents) with even minimal behavioural capabilities can have a significant emotional impact on participants of immersive virtual environments (IVEs) to the extent that these have been used in studies of mental health issues such as social phobia and paranoia. This thesis focuses on understanding the impact on the responses of people to the behaviour of virtual humans rather than their visual appearance. There are three main research questions addressed. First, the thesis considers what are the key nonverbal behavioural cues used to portray a specific psychological state. Second, research determines the extent to which the underlying state of a virtual human is recognisable through the display of a key set of cues inferred from the behaviour of real humans. Finally, the degree to which a perceived psychological state in a virtual human invokes responses from participants in immersive virtual environments that are similar to those observed in the physical world is considered. These research questions were investigated through four experiments. The first experiment focused on the impact of visual fidelity and behavioural complexity on participant responses by implementing a model of gaze behaviour in virtual humans. The results of the study concluded that participants expected more life-like behaviours from more visually realistic virtual humans. The second experiment investigated the detrimental effects on participant responses when interacting with virtual humans with low behavioural complexity. The third experiment investigated the differences in responses of participants to virtual humans perceived to be in varying emotional states. The emotional states of the virtual humans were portrayed using postural and facial cues. Results indicated that posture does play an important role in the portrayal of affect however the behavioural model used in the study did not fully cover the qualities of body movement associated with the emotions studied. The final experiment focused on the portrayal of affect through the quality of body movement such as the speed of gestures. The effectiveness of the virtual humans was gauged through exploring a variety of participant responses including subjective responses, objective physiological and behavioural measures. The results show that participants are affected and respond to virtual humans in a significant manner provided that an appropriate behavioural model is used

    Real-time generation and adaptation of social companion robot behaviors

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    Social robots will be part of our future homes. They will assist us in everyday tasks, entertain us, and provide helpful advice. However, the technology still faces challenges that must be overcome to equip the machine with social competencies and make it a socially intelligent and accepted housemate. An essential skill of every social robot is verbal and non-verbal communication. In contrast to voice assistants, smartphones, and smart home technology, which are already part of many people's lives today, social robots have an embodiment that raises expectations towards the machine. Their anthropomorphic or zoomorphic appearance suggests they can communicate naturally with speech, gestures, or facial expressions and understand corresponding human behaviors. In addition, robots also need to consider individual users' preferences: everybody is shaped by their culture, social norms, and life experiences, resulting in different expectations towards communication with a robot. However, robots do not have human intuition - they must be equipped with the corresponding algorithmic solutions to these problems. This thesis investigates the use of reinforcement learning to adapt the robot's verbal and non-verbal communication to the user's needs and preferences. Such non-functional adaptation of the robot's behaviors primarily aims to improve the user experience and the robot's perceived social intelligence. The literature has not yet provided a holistic view of the overall challenge: real-time adaptation requires control over the robot's multimodal behavior generation, an understanding of human feedback, and an algorithmic basis for machine learning. Thus, this thesis develops a conceptual framework for designing real-time non-functional social robot behavior adaptation with reinforcement learning. It provides a higher-level view from the system designer's perspective and guidance from the start to the end. It illustrates the process of modeling, simulating, and evaluating such adaptation processes. Specifically, it guides the integration of human feedback and social signals to equip the machine with social awareness. The conceptual framework is put into practice for several use cases, resulting in technical proofs of concept and research prototypes. They are evaluated in the lab and in in-situ studies. These approaches address typical activities in domestic environments, focussing on the robot's expression of personality, persona, politeness, and humor. Within this scope, the robot adapts its spoken utterances, prosody, and animations based on human explicit or implicit feedback.Soziale Roboter werden Teil unseres zukßnftigen Zuhauses sein. Sie werden uns bei alltäglichen Aufgaben unterstßtzen, uns unterhalten und uns mit hilfreichen Ratschlägen versorgen. Noch gibt es allerdings technische Herausforderungen, die zunächst ßberwunden werden mßssen, um die Maschine mit sozialen Kompetenzen auszustatten und zu einem sozial intelligenten und akzeptierten Mitbewohner zu machen. Eine wesentliche Fähigkeit eines jeden sozialen Roboters ist die verbale und nonverbale Kommunikation. Im Gegensatz zu Sprachassistenten, Smartphones und Smart-Home-Technologien, die bereits heute Teil des Lebens vieler Menschen sind, haben soziale Roboter eine VerkÜrperung, die Erwartungen an die Maschine weckt. Ihr anthropomorphes oder zoomorphes Aussehen legt nahe, dass sie in der Lage sind, auf natßrliche Weise mit Sprache, Gestik oder Mimik zu kommunizieren, aber auch entsprechende menschliche Kommunikation zu verstehen. Darßber hinaus mßssen Roboter auch die individuellen Vorlieben der Benutzer berßcksichtigen. So ist jeder Mensch von seiner Kultur, sozialen Normen und eigenen Lebenserfahrungen geprägt, was zu unterschiedlichen Erwartungen an die Kommunikation mit einem Roboter fßhrt. Roboter haben jedoch keine menschliche Intuition - sie mßssen mit entsprechenden Algorithmen fßr diese Probleme ausgestattet werden. In dieser Arbeit wird der Einsatz von bestärkendem Lernen untersucht, um die verbale und nonverbale Kommunikation des Roboters an die Bedßrfnisse und Vorlieben des Benutzers anzupassen. Eine solche nicht-funktionale Anpassung des Roboterverhaltens zielt in erster Linie darauf ab, das Benutzererlebnis und die wahrgenommene soziale Intelligenz des Roboters zu verbessern. Die Literatur bietet bisher keine ganzheitliche Sicht auf diese Herausforderung: Echtzeitanpassung erfordert die Kontrolle ßber die multimodale Verhaltenserzeugung des Roboters, ein Verständnis des menschlichen Feedbacks und eine algorithmische Basis fßr maschinelles Lernen. Daher wird in dieser Arbeit ein konzeptioneller Rahmen fßr die Gestaltung von nicht-funktionaler Anpassung der Kommunikation sozialer Roboter mit bestärkendem Lernen entwickelt. Er bietet eine ßbergeordnete Sichtweise aus der Perspektive des Systemdesigners und eine Anleitung vom Anfang bis zum Ende. Er veranschaulicht den Prozess der Modellierung, Simulation und Evaluierung solcher Anpassungsprozesse. Insbesondere wird auf die Integration von menschlichem Feedback und sozialen Signalen eingegangen, um die Maschine mit sozialem Bewusstsein auszustatten. Der konzeptionelle Rahmen wird fßr mehrere Anwendungsfälle in die Praxis umgesetzt, was zu technischen Konzeptnachweisen und Forschungsprototypen fßhrt, die in Labor- und In-situ-Studien evaluiert werden. Diese Ansätze befassen sich mit typischen Aktivitäten in häuslichen Umgebungen, wobei der Schwerpunkt auf dem Ausdruck der PersÜnlichkeit, dem Persona, der HÜflichkeit und dem Humor des Roboters liegt. In diesem Rahmen passt der Roboter seine Sprache, Prosodie, und Animationen auf Basis expliziten oder impliziten menschlichen Feedbacks an
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