2,104 research outputs found

    Introduction for speech and language for interactive robots

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    This special issue includes research articles which apply spoken language processing to robots that interact with human users through speech, possibly combined with other modalities. Robots that can listen to human speech, understand it, interact according to the conveyed meaning, and respond represent major research and technological challenges. Their common aim is to equip robots with natural interaction abilities. However, robotics and spoken language processing are areas that are typically studied within their respective communities with limited communication across disciplinary boundaries. The articles in this special issue represent examples that address the need for an increased multidisciplinary exchange of ideas

    Symbol Emergence in Robotics: A Survey

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    Humans can learn the use of language through physical interaction with their environment and semiotic communication with other people. It is very important to obtain a computational understanding of how humans can form a symbol system and obtain semiotic skills through their autonomous mental development. Recently, many studies have been conducted on the construction of robotic systems and machine-learning methods that can learn the use of language through embodied multimodal interaction with their environment and other systems. Understanding human social interactions and developing a robot that can smoothly communicate with human users in the long term, requires an understanding of the dynamics of symbol systems and is crucially important. The embodied cognition and social interaction of participants gradually change a symbol system in a constructive manner. In this paper, we introduce a field of research called symbol emergence in robotics (SER). SER is a constructive approach towards an emergent symbol system. The emergent symbol system is socially self-organized through both semiotic communications and physical interactions with autonomous cognitive developmental agents, i.e., humans and developmental robots. Specifically, we describe some state-of-art research topics concerning SER, e.g., multimodal categorization, word discovery, and a double articulation analysis, that enable a robot to obtain words and their embodied meanings from raw sensory--motor information, including visual information, haptic information, auditory information, and acoustic speech signals, in a totally unsupervised manner. Finally, we suggest future directions of research in SER.Comment: submitted to Advanced Robotic

    Overcoming barriers and increasing independence: service robots for elderly and disabled people

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    This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

    "Involving Interface": An Extended Mind Theoretical Approach to Roboethics

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    In 2008 the authors held Involving Interface, a lively interdisciplinary event focusing on issues of biological, sociocultural, and technological interfacing (see Acknowledgments). Inspired by discussions at this event, in this article, we further discuss the value of input from neuroscience for developing robots and machine interfaces, and the value of philosophy, the humanities, and the arts for identifying persistent links between human interfacing and broader ethical concerns. The importance of ongoing interdisciplinary debate and public communication on scientific and technical advances is also highlighted. Throughout, the authors explore the implications of the extended mind hypothesis for notions of moral accountability and robotics

    How might the use of apps influence students' learning experiences? Exploring a socio-technological assemblage

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    In this paper, we report on primary-school students’ views of their learning experiences when they engaged with mathematical phenomena through apps. The students commented on how they used a range of digital tools within the apps to solve problems, and we consider how the affordances of the mobile technologies, including multi-representation, dynamic and haptic, might influence the learning experiences. In particular, we focus on the interplay between the affordances of the mobile technologies with other social and pedagogical aspects, and ask how the assemblage of social and technological entities might influence mathematical learning experiences

    Early Turn-taking Prediction with Spiking Neural Networks for Human Robot Collaboration

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    Turn-taking is essential to the structure of human teamwork. Humans are typically aware of team members' intention to keep or relinquish their turn before a turn switch, where the responsibility of working on a shared task is shifted. Future co-robots are also expected to provide such competence. To that end, this paper proposes the Cognitive Turn-taking Model (CTTM), which leverages cognitive models (i.e., Spiking Neural Network) to achieve early turn-taking prediction. The CTTM framework can process multimodal human communication cues (both implicit and explicit) and predict human turn-taking intentions in an early stage. The proposed framework is tested on a simulated surgical procedure, where a robotic scrub nurse predicts the surgeon's turn-taking intention. It was found that the proposed CTTM framework outperforms the state-of-the-art turn-taking prediction algorithms by a large margin. It also outperforms humans when presented with partial observations of communication cues (i.e., less than 40% of full actions). This early prediction capability enables robots to initiate turn-taking actions at an early stage, which facilitates collaboration and increases overall efficiency.Comment: Submitted to IEEE International Conference on Robotics and Automation (ICRA) 201

    Future touch in industry: exploring sociotechnical imaginaries of tactile (tele)robots

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    This paper explores sociotechnical imaginaries for industrial robotics. It is motivated by the prospect of promoting human-centred industrial futures. Investigating the tactility of labour through a critical social perspective the research attends to the future of tactile (tele)robots and elaborates on the concepts of pedagogic, collaborative and superhuman touch. These concepts are offered as starting points to foster productive dialogues between social scientists, roboticists, environmentalists, policy makers, industrial leaders and labourers (e.g. union representatives). This paper is framed through literature and ethnographic fieldwork that contextualises and maps the dominant sociotechnical imaginaries for a future touch in industry, identifying the role of a comparative-competitive frame in sustaining a splintering of the imaginary towards utopic and dystopic extremes. Against this, the paper draws on interviews with leading roboticists to chart alternative futures where humans and robots may work together as collaborators, not competitors
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