10,666 research outputs found

    Social Situatedness: Vygotsky and Beyond

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    The concept of ‘social situatedness’, i.e. the idea that the development of individual intelligence requires a social (and cultural) embedding, has recently received much attention in cognitive science and artificial intelligence research. The work of Lev Vygotsky who put forward this view already in the 1920s has influenced the discussion to some degree, but still remains far from well known. This paper therefore aims to give an overview of his cognitive development theory and discuss its relation to more recent work in primatology and socially situated artificial intelligence, in particular humanoid robotics

    Speech-Gesture Mapping and Engagement Evaluation in Human Robot Interaction

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    A robot needs contextual awareness, effective speech production and complementing non-verbal gestures for successful communication in society. In this paper, we present our end-to-end system that tries to enhance the effectiveness of non-verbal gestures. For achieving this, we identified prominently used gestures in performances by TED speakers and mapped them to their corresponding speech context and modulated speech based upon the attention of the listener. The proposed method utilized Convolutional Pose Machine [4] to detect the human gesture. Dominant gestures of TED speakers were used for learning the gesture-to-speech mapping. The speeches by them were used for training the model. We also evaluated the engagement of the robot with people by conducting a social survey. The effectiveness of the performance was monitored by the robot and it self-improvised its speech pattern on the basis of the attention level of the audience, which was calculated using visual feedback from the camera. The effectiveness of interaction as well as the decisions made during improvisation was further evaluated based on the head-pose detection and interaction survey.Comment: 8 pages, 9 figures, Under review in IRC 201

    Gesture Recognition Aplication based on Dynamic Time Warping (DTW) FOR Omni-Wheel Mobile Robot

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    This project presents of the movement of omni-wheel robot moves in the trajectory obtained from the gesture recognition system based on Dynamic Time Warping. Single camera is used as the input of the system, which is also a reference to the movement of the omni-wheel robot. Some systems for gesture recognition have been developed using various methods and different approaches. The movement of the omni-wheel robot using the method of Dynamic Time Wrapping (DTW) which has the advantage able to calculate the distance of two data vectors with different lengths. By using this method we can measure the similarity between two sequences at different times and speeds. Dynamic Time Warping to compare the two parameters at varying times and speeds. Application of DTW widely applied in video, audio, graphics, etc. Due to data that can be changed in a linear manner so that it can be analyzed with DTW. In short can find the most suitable value by minimizing the difference between two multidimensional signals that have been compressed. DTW method is expected to gesture recognition system to work optimally, have a high enough value of accuracy and processing time is realtime

    A systematic comparison of affective robot expression modalities

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    Towards Safe and Trustworthy Social Robots : Ethical Challenges and Practical Issues

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    Maha Salem, Gabriella Lakatos, Farshid Amirabdollahian, K. Dautenhahn, ‘Towards Safe and Trustworthy Social Robots: Ethical Challenges and Practical Issues’, paper presented at the 7th International Conference on Social Robotics, Paris, France, 26-30 October, 2015.As robots are increasingly developed to assist humans so- cially with everyday tasks in home and healthcare settings, questions regarding the robot's safety and trustworthiness need to be addressed. The present work investigates the practical and ethical challenges in de- signing and evaluating social robots that aim to be perceived as safe and can win their human users' trust. With particular focus on collaborative scenarios in which humans are required to accept information provided by the robot and follow its suggestions, trust plays a crucial role and is strongly linked to persuasiveness. Accordingly, human-robot trust can directly aect people's willingness to cooperate with the robot, while under- or overreliance may have severe or even dangerous consequences. Problematically, investigating trust and human perceptions of safety in HRI experiments proves challenging in light of numerous ethical con- cerns and risks, which this paper aims to highlight and discuss based on experiences from HRI practice.Peer reviewe
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