Collaborative Research: Socially Assistive Robots

社会辅助机器人领导PI/机构：Brian Scassellati，耶鲁大学这次考察将开发基本的计算技术，使机器人的设计、实现和评估能够促进儿童的社会、情感和认知发展，包括那些有社会或认知缺陷的儿童。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，以补充教育工作者、家长和临床医生的努力。例如，临床医生和家庭努力为有社会和认知缺陷的儿童提供个性化的教育服务，仅在过去十年中，美国的这一数字就翻了两番。在许多学校，教育工作者努力为在非英语家庭中长大的孩子（超过20%）提供语言教学，这是学龄人口中增长最快的一部分。这次探险的目的是支持这些孩子的个人需求，通过社交辅助机器人来帮助引导孩子实现长期的行为目标，这些机器人是根据每个孩子的特殊需求定制的，并且随着孩子的发展和变化而发展。为了实现这一愿景，这次考察将推动社会辅助人机交互的最新技术，从结构化环境中的短期交互到适应性强、吸引人且有效的长期交互。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的计算研究。首先，探险队将开发社会互动动态的计算模型，这样机器人就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、社交和认知差异来适应和个性化交互，使机器人能够以适合每个人的需求、偏好和能力的方式来教授和塑造行为。第三，探险队将开发系统，引导孩子们在数周或数月的时间内实现特定的学习目标，从而实现真正的长期指导和支持。这三个领域的研究将被整合到社会辅助机器人中，这些机器人将在学校和家庭中部署长达一年的时间。这次考察有可能对儿童教育和保健的有效性产生重大影响，所开发的技术工具将作为改善儿童和其他需要专门支持和干预的群体生活的基础。拟议的计算研究与一个全面的学生培训计划联系在一起，通过校内和课外活动，为K-12学生带来引人注目、引人入胜和接地气的STEM体验。它还建立了一个年度培训峰会，为本科生提供多学科背景，以便在研究生院从事这一有前途的研究领域。最后，通过建立社会辅助机器人的品牌，这一努力将为高质量的同行评审信息的分发创造一个中央权威，为加强推广和教育提供一个连贯的焦点。更多信息请访问www.yale.edu/SAR

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