Collaborative Research: Socially Assistive Robots

合作研究：社交辅助机器人

• 批准号: 1139161
• 负责人: Pamela Hinds
• 金额: $ 132.5万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1139161&HistoricalAwards=false
• 关键词: Collaborative; Research; Socially; Assistive; Robots

Socially Assistive RobotsLead PI/Institution: Brian Scassellati, Yale UniversityThis Expedition will develop the fundamental computational techniques that will enable the design, implementation, and evaluation of robots that encourage social, emotional, and cognitive growth in children, including those with social or cognitive deficits. The need for this technology is driven by critical societal problems that require sustained, personalized support that supplements the efforts of educators, parents, and clinicians. For example, clinicians and families struggle to provide individualized educational services to children with social and cognitive deficits, whose numbers have quadrupled in the US in the last decade alone. In many schools, educators struggle to provide language instruction for children raised in homes where a language other than English is spoken (over 20%), the fastest-growing segment of the school-age population. This Expedition aims to support the individual needs of these children with socially assistive robots that help to guide the children toward long-term behavioral goals, that are customized to the particular needs of each child, and that develop and change as the child does. To achieve this vision, this Expedition will advance the state-of-the-art in socially assistive human-robot interaction from short-term interactions in structured environments to long-term interactions that are adaptive, engaging, and effective. This progress will require transformative computing research in three broad and naturally interrelated research areas. First, the Expedition will develop computational models of the dynamics of social interaction, so that robots can automatically detect, analyze, and influence agency, intention, and other social interaction primitives in dynamic environments. Second, the Expedition will develop machine learning algorithms that adapt and personalize interactions to individual physical, social, and cognitive differences, enabling robots to teach and shape behavior in ways that are tailored to the needs, preferences, and capabilities of each individual. Third, the Expedition will develop systems that guide children toward specific learning goals over periods of weeks and months, allowing for truly long-term guidance and support. Research in these three areas will be integrated into socially assistive robots that are deployed in schools and homes for durations of up to one year. This Expedition has the potential to substantially impact the effectiveness of education and healthcare for children, and the technological tools developed will serve as the basis for enhancing the lives of children and other groups that require specialized support and intervention. The proposed computing research is tied to a comprehensive student training program, bringing a compelling, engaging, and grounded STEM experience to K-12 students through in-school and after-school activities. It also establishes an annual training summit to provide undergraduates with the multi-disciplinary background to engage in this promising research area in graduate school. Finally, by establishing a brand name for socially assistive robotics, this effort will create a central authority for the distribution of high-quality, peer-reviewed information, providing a coherent focal point for enhancing outreach and education.For more information visit www.yale.edu/SAR

社会辅助机器人lead PI/机构：Brian Scassellati，耶鲁大学探险队将开发基本的计算技术，这些技术将对包括社交或认知赤字在内的儿童的社会，情感和认知增长的机器人进行设计，实施和评估。 对这项技术的需求是由需要持续，个性化支持的关键社会问题驱动的，以补充教育者，父母和临床医生的努力。 例如，临床医生和家庭努力为具有社会和认知缺陷的儿童提供个性化的教育服务，仅在过去的十年中，他们的人数在美国的数字就达到了三倍。 在许多学校中，教育工作者努力为在说英语以外的其他语言（超过20％）（超过20％）的家庭中，这是学院年龄人口中增长最快的人的语言教学。 这次探险旨在支持这些儿童具有社会辅助机器人的个人需求，这些机器人有助于指导儿童实现长期行为目标，这些目标是根据每个孩子的特定需求来定制的，并且像孩子一样发展和改变。 为了实现这一愿景，这次探险将使社会辅助人类互动的最先进从结构化环境的短期相互作用到自适应，引人入胜且有效的长期相互作用。这一进展将需要在三个广泛且自然相互关联的研究领域的变革性计算研究。首先，探险将开发社会互动动力学的计算模型，以便机器人可以在动态环境中自动检测，分析和影响代理，意图和其他社会互动原始图。其次，探险将开发机器学习算法，这些算法适应和个性化相互作用，以适应个人的身体，社会和认知差异，使机器人能够以根据每个人的需求，偏好和能力来量身定制的方式来教授和塑造行为。第三，探险将开发系统，以指导儿童在数周和几个月的时间内实现特定的学习目标，从而提供真正的长期指导和支持。在这三个领域的研究将被整合到社会辅助机器人中，这些机器人在学校和房屋中部署了长达一年的时间。 这次探险有可能实质上影响儿童的教育和医疗保健的有效性，而开发的技术工具将成为增强需要专门支持和干预的儿童和其他团体生活的基础。拟议的计算研究与一项全面的学生培训计划有关，通过学校和课后活动为K-12学生带来了引人入胜，引人入胜且扎根的STEM经验。它还建立了一个年度培训峰会，以向本科生提供多学科背景，以在研究生院参与这个有前途的研究领域。最后，通过为社会辅助机器人技术建立品牌名称，这项工作将创建一个中央权威，以分发高质量的，同行评审的信息，为增强外展和教育提供一个连贯的焦点。有关更多信息，请访问www.yale.edu/sar/sar