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Träfflista för sökning "AMNE:(NATURAL SCIENCES Computer and Information Sciences Computer Vision and Robotics Autonomous Systems) ;lar1:(his)"

Sökning: AMNE:(NATURAL SCIENCES Computer and Information Sciences Computer Vision and Robotics Autonomous Systems) > Högskolan i Skövde

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1.
  • Cai, Haibin, et al. (författare)
  • Sensing-enhanced Therapy System for Assessing Children with Autism Spectrum Disorders : A Feasibility Study
  • 2019
  • Ingår i: IEEE Sensors Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 1530-437X .- 1558-1748. ; 19:4, s. 1508-1518
  • Tidskriftsartikel (refereegranskat)abstract
    • It is evident that recently reported robot-assisted therapy systems for assessment of children with autism spectrum disorder (ASD) lack autonomous interaction abilities and require significant human resources. This paper proposes a sensing system that automatically extracts and fuses sensory features such as body motion features, facial expressions, and gaze features, further assessing the children behaviours by mapping them to therapist-specified behavioural classes. Experimental results show that the developed system has a capability of interpreting characteristic data of children with ASD, thus has the potential to increase the autonomy of robots under the supervision of a therapist and enhance the quality of the digital description of children with ASD. The research outcomes pave the way to a feasible machine-assisted system for their behaviour assessment. IEEE
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2.
  • Sun, Jiong, et al. (författare)
  • Tactile Interaction and Social Touch : Classifying Human Touch using a Soft Tactile Sensor
  • 2017
  • Ingår i: HAI '17. - New York : Association for Computing Machinery (ACM). - 9781450351133 ; , s. 523-526
  • Konferensbidrag (refereegranskat)abstract
    • This paper presents an ongoing study on affective human-robot interaction. In our previous research, touch type is shown to be informative for communicated emotion. Here, a soft matrix array sensor is used to capture the tactile interaction between human and robot and 6 machine learning methods including CNN, RNN and C3D are implemented to classify different touch types, constituting a pre-stage to recognizing emotional tactile interaction. Results show an average recognition rate of 95% by C3D for classified touch types, which provide stable classification results for developing social touch technology. 
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3.
  • Thill, Serge (författare)
  • What we need from an embodied cognitive architecture
  • 2019
  • Ingår i: Cognitive Architectures. - Cham : Springer. - 9783319975498 - 9783319975504 ; , s. 43-57
  • Bokkapitel (refereegranskat)abstract
    • Given that original purpose of cognitive architectures was to lead to a unified theory of cognition, this chapter considers the possible contributions that cognitive architectures can make to embodied theories of cognition in particular. This is not a trivial question since the field remains very much divided about what embodied cognition actually means, and we will see some example positions in this chapter. It is then argued that a useful embodied cognitive architecture would be one that can demonstrate (a) what precisely the role of the body in cognition actually is, and (b) whether a body is constitutively needed at all for some (or all) cognitive processes. It is proposed that such questions can be investigated if the cognitive architecture is designed so that consequences of varying the precise embodiment on higher cognitive mechanisms can be explored. This is in contrast with, for example, those cognitive architectures in robotics that are designed for specific bodies first; or architectures in cognitive science that implement embodiment as an add-on to an existing framework (because then, that framework is by definition not constitutively shaped by the embodiment). The chapter concludes that the so-called semantic pointer architecture by Eliasmith and colleagues may be one framework that satisfies our desiderata and may be well-suited for studying theories of embodied cognition further.
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