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Cognitive Robots for Social Interaction.

机译:社交互动的认知机器人。

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摘要

One of my goals is to work towards developing Cognitive Robots, especially with regard to improving the functionalities that facilitate the interaction with human beings and their surrounding objects. Any cognitive system designated for serving human beings must be capable of processing the social signals and eventually enable efficient prediction and planning of appropriate responses.;My main focus during my PhD study is to bridge the gap between the motoric space and the visual space. The discovery of the mirror neurons ([RC04]) shows that the visual perception of human motion (visual space) is directly associated to the motor control of the human body (motor space). This discovery poses a large number of challenges in different fields such as computer vision, robotics and neuroscience. One of the fundamental challenges is the understanding of the mapping between 2D visual space and 3D motoric control, and further developing building blocks (primitives) of human motion in the visual space as well as in the motor space.;First, I present my study on the visual-motoric mapping of human actions. This study aims at mapping human actions in 2D videos to 3D skeletal representation. Second, I present an automatic algorithm to decompose motion capture (MoCap) sequences into synergies along with the times at which they are executed (or "activated") for each joint. Third, I proposed to use the Granger Causality as a tool to study the coordinated actions performed by at least two units. Recent scientific studies suggest that the above "action mirroring circuit" might be tuned to action coordination rather than single action mirroring. Fourth, I present the extraction of key poses in visual space. These key poses facilitate the further study of the "action mirroring circuit". I conclude the dissertation by describing the future of cognitive robotics study.
机译:我的目标之一是致力于开发认知机器人,尤其是在改善功能上,以促进与人类及其周围物体的交互。任何旨在为人类服务的认知系统都必须能够处理社会信号,并最终能够有效地预测和规划适当的应对措施。;在我的博士研究期间,我的主要重点是弥合运动空间和视觉空间之间的鸿沟。镜像神经元([RC04])的发现表明,人类运动(视觉空间)的视觉感知与人体的运动控制(运动空间)直接相关。这一发现在计算机视觉,机器人技术和神经科学等不同领域提出了大量挑战。基本挑战之一是对2D视觉空间和3D电机控制之间的映射的理解,以及进一步开发视觉空间以及运动空间中人体运动的构造块(原始)。关于人类动作的视觉运动映射。这项研究旨在将2D视频中的人类行为映射到3D骨骼表示。其次,我提出了一种自动算法,可以将运动捕捉(MoCap)序列与每个关节执行(或“激活”)的时间分解为协同作用。第三,我建议使用格兰杰因果关系作为研究至少两个单位执行的协调行动的工具。最近的科学研究表明,上述“动作镜像电路”可以调整为动作协调,而不是单个动作镜像。第四,我提出了视觉空间中关键姿势的提取。这些关键姿势有助于进一步研究“动作镜像电路”。最后,我通过描述认知机器人学的未来来总结论文。

著录项

  • 作者

    Li, Yi.;

  • 作者单位

    University of Maryland, College Park.;

  • 授予单位 University of Maryland, College Park.;
  • 学科 Engineering Electronics and Electrical.;Computer Science.;Engineering Robotics.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 127 p.
  • 总页数 127
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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