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

社交辅助机器人首席 PI/机构：布莱恩·斯卡塞拉蒂 (Brian Scassellati)，耶鲁大学 这次探险将开发基本的计算技术，从而实现机器人的设计、实施和评估，从而鼓励儿童（包括那些有社交或认知缺陷的儿童）的社交、情感和认知成长。 对这项技术的需求是由关键的社会问题驱动的，这些问题需要持续的、个性化的支持来补充教育工作者、家长和临床医生的努力。 例如，临床医生和家庭很难为有社交和认知缺陷的儿童提供个性化的教育服务，仅在过去十年里，美国此类儿童的数量就增加了四倍。 在许多学校，教育工作者很难为那些在非英语家庭长大的儿童（超过 20%）提供语言教学，而这些儿童是学龄人口中增长最快的群体。 这次探险旨在通过社交辅助机器人来支持这些孩子的个人需求，这些机器人有助于引导孩子们实现长期行为目标，这些目标是根据每个孩子的特定需求定制的，并随着孩子的发展和变化而变化。 为了实现这一愿景，本次探险将推动社交辅助人机交互的最先进水平，从结构化环境中的短期交互发展为适应性强、有吸引力且有效的长期交互。这一进展将需要在三个广泛且自然相关的研究领域进行变革性计算研究。首先，Expedition 将开发社交互动动态的计算模型，以便机器人能够自动检测、分析和影响动态环境中的代理、意图和其他社交互动原语。其次，探险队将开发机器学习算法，根据个人的身体、社交和认知差异调整和个性化交互，使机器人能够根据每个人的需求、偏好和能力量身定制教学和塑造行为。第三，探险队将开发系统，引导儿童在数周和数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。这三个领域的研究将被整合到社交辅助机器人中，这些机器人将部署在学校和家庭中，持续时间长达一年。 这次探险有可能对儿童教育和医疗保健的有效性产生重大影响，所开发的技术工具将成为改善儿童和其他需要专门支持和干预的群体的生活的基础。拟议的计算研究与综合学生培训计划紧密结合，通过校内和课外活动为 K-12 学生带来引人入胜、引人入胜且扎实的 STEM 体验。它还设立了年度培训峰会，为本科生提供多学科背景，让他们能够在研究生院从事这一有前景的研究领域。最后，通过建立社交辅助机器人的品牌，这项工作将创建一个中央权威机构来分发高质量、经过同行评审的信息，为加强推广和教育提供一致的焦点。如需了解更多信息，请访问 www.yale.edu/SAR