HCC-Medium: Personalized Socially-Assistive Human-Robot Interaction: Applications to Autism Spectrum Disorder

机器人技术目前处于技术的最前沿，具有影响人类生活质量的公认潜力。为了满足日益增长的老年人和具有特殊认知和社会需求的人对个性化一对一护理的大量需求，必须在人机交互（HRI）领域取得巨大进步，以便将机器人技术带入人类日常生活中的应用领域。这个跨学科的项目确定了一组特定的社会辅助机器人的HRI研究问题，能够通过社会而不是物理互动提供帮助的机器人系统的研究。研究的重点是两个关键问题：（1）机器人的物理体现在交互中的作用;（2）使用表达性体现的通信和用户建模个性化的时间延长的辅助交互。一个具体的考虑是在社会沟通的异质性和赤字的挑战下的互动。一种新的辅助机器人控制体系结构的开发，基于多模态感知，体现的表达和通信，和在线用户建模，在三种不同类型的现实世界中的社会辅助系统实现。为了给研究提供一个现实的背景，对来自典型人群和自闭症谱系障碍（ASD）人群的儿童进行了实验测试和评估，ASD是一种已经被确定为适合技术，特别是机器人干预和治疗的疾病家族。该研究的一个关键贡献在于统一和紧密集成的端到端方法，该方法共同研究了具体化和多模态表达性通信，基于假设驱动的实验数据，以及开发和使用新颖的信号处理和用户建模方法进行人机交互设计。这个项目，就其本质而言，旨在影响受自闭症谱系障碍影响的庞大且不断增长的人口。在将收集和分析的大量独特数据库的支持下，预期的科学影响将远远超出新的见解，以更好地理解HRI的基本原理及其与不同用户群体和自闭症谱系障碍儿童社交的相关性。除了基础研究，两个互补的教育推广计划扩大了工作的影响：（1）一个新颖的K-12推广和教师培训计划，专门针对特殊教育，通过使用机器人技术教授STEM主题;和（2）本科研究培训和管道角色建模从大学预科到本科到研究生。教育方案与研究计划相吻合，导致研究团队所有参与者参与的综合活动。

Robotics is currently at the forefront of technologies with recognized potential for impacting quality of human life. In response to the large need for personalized one-on-one care for the growing populations of elderly individuals and those with special cognitive and social needs throughout life, great strides must be made in the domain of human-robot interaction (HRI) in order to bring robotics into such application domains in human everyday life. This interdisciplinary project identifies a specific set of HRI research questions in socially assistive robotics, the study of robotic systems capable of providing help through social rather than physical interaction. The research focus is on two key issues: (1) the role of the robot's physical embodiment in the interaction; and (2) the use of expressive embodied communication and user modeling toward personalized time-extended assistive interaction. A specific consideration is given to interactions under the challenges of socio-communicative heterogeneity and deficits. A novel assistive robot control architecture is developed, based on multi-modal perception, embodied expression and communication, and on-line user modeling, implemented in three different types of real-world socially assistive systems. To give a realistic context to the research, the experimental testing and evaluation are performed with children drawn from a typical population and a population with Autism Spectrum Disorders (ASD), a family of disorders that have already been identified as amenable to technological, and in particular robotic, intervention and therapy. A key contribution of the research lies in the unified and tightly integrated end-to-end approach that jointly studies embodiment and multimodal expressive communication, grounded in data from hypothesis-driven experiments, and the development and use of novel signal processing and user modeling methods for human-machine interaction design. This project, by its very nature, aims to impact the large and growing population affected by Autism Spectrum Disorders. With the support of the large and unique corpus of data that will be collected and analyzed, the expected scientific impact will go well beyond novel insights toward a better understanding of the fundamentals of HRI and its relevance for diverse user populations and for socialization of children with ASD. In addition to the basic research, two complementary educational outreach programs broaden the impact of the work: (1) a novel K-12 outreach and teacher training program specifically aimed at special education through the use of robotics for teaching STEM topics; and (2) undergraduate research training and pipelined role-modeling from pre-university to undergraduate to graduate students. The education programs dovetail with the research plan, resulting in integrated activities involving all participants in the research team.