929 research outputs found

    A Review of Verbal and Non-Verbal Human-Robot Interactive Communication

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    In this paper, an overview of human-robot interactive communication is presented, covering verbal as well as non-verbal aspects of human-robot interaction. Following a historical introduction, and motivation towards fluid human-robot communication, ten desiderata are proposed, which provide an organizational axis both of recent as well as of future research on human-robot communication. Then, the ten desiderata are examined in detail, culminating to a unifying discussion, and a forward-looking conclusion

    Towards an Interactive Humanoid Companion with Visual Tracking Modalities

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    The idea of robots acting as human companions is not a particularly new or original one. Since the notion of “robot ” was created, the idea of robots replacing humans in dangerous, dirty and dull activities has been inseparably tied with the fantasy of human-like robots being friends and existing side by side with humans. In 1989, Engelberger (Engelberger

    A Novel Greeting Selection System for a Culture-Adaptive Humanoid Robot

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    Robots, especially humanoids, are expected to perform human-like actions and adapt to our ways of communication in order to facilitate their acceptance in human society. Among humans, rules of communication change depending on background culture: greetings are a part of communication in which cultural differences are strong. Robots should adapt to these specific differences in order to communicate effectively, being able to select the appropriate manner of greeting for different cultures depending on the social context. In this paper, we present the modelling of social factors that influence greeting choice, and the resulting novel culture-dependent greeting gesture and words selection system. An experiment with German participants was run using the humanoid robot ARMAR-IIIb. Thanks to this system, the robot, after interacting with Germans, can perform greeting gestures appropriate to German culture in addition to a repertoire of greetings appropriate to Japanese culture

    A novel greeting selection system for a culture-adaptive humanoid robot

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    Robots, especially humanoids, are expected to perform human-like actions and adapt to our ways of communication in order to facilitate their acceptance in human society. Among humans, rules of communication change depending on background culture: greetings are a part of communication in which cultural differences are strong. Robots should adapt to these specific differences in order to communicate effectively, being able to select the appropriate manner of greeting for different cultures depending on the social context. In this paper, we present the modelling of social factors that influence greeting choice, and the resulting novel culture-dependent greeting gesture and words selection system. An experiment with German participants was run using the humanoid robot ARMARIIIb. Thanks to this system, the robot, after interacting with Germans, can perform greeting gestures appropriate to German culture in addition to a repertoire of greetings appropriate to Japanese culture

    Towards gestural understanding for intelligent robots

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    Fritsch JN. Towards gestural understanding for intelligent robots. Bielefeld: Universität Bielefeld; 2012.A strong driving force of scientific progress in the technical sciences is the quest for systems that assist humans in their daily life and make their life easier and more enjoyable. Nowadays smartphones are probably the most typical instances of such systems. Another class of systems that is getting increasing attention are intelligent robots. Instead of offering a smartphone touch screen to select actions, these systems are intended to offer a more natural human-machine interface to their users. Out of the large range of actions performed by humans, gestures performed with the hands play a very important role especially when humans interact with their direct surrounding like, e.g., pointing to an object or manipulating it. Consequently, a robot has to understand such gestures to offer an intuitive interface. Gestural understanding is, therefore, a key capability on the way to intelligent robots. This book deals with vision-based approaches for gestural understanding. Over the past two decades, this has been an intensive field of research which has resulted in a variety of algorithms to analyze human hand motions. Following a categorization of different gesture types and a review of other sensing techniques, the design of vision systems that achieve hand gesture understanding for intelligent robots is analyzed. For each of the individual algorithmic steps – hand detection, hand tracking, and trajectory-based gesture recognition – a separate Chapter introduces common techniques and algorithms and provides example methods. The resulting recognition algorithms are considering gestures in isolation and are often not sufficient for interacting with a robot who can only understand such gestures when incorporating the context like, e.g., what object was pointed at or manipulated. Going beyond a purely trajectory-based gesture recognition by incorporating context is an important prerequisite to achieve gesture understanding and is addressed explicitly in a separate Chapter of this book. Two types of context, user-provided context and situational context, are reviewed and existing approaches to incorporate context for gestural understanding are reviewed. Example approaches for both context types provide a deeper algorithmic insight into this field of research. An overview of recent robots capable of gesture recognition and understanding summarizes the currently realized human-robot interaction quality. The approaches for gesture understanding covered in this book are manually designed while humans learn to recognize gestures automatically during growing up. Promising research targeted at analyzing developmental learning in children in order to mimic this capability in technical systems is highlighted in the last Chapter completing this book as this research direction may be highly influential for creating future gesture understanding systems
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