CAREER: Towards Programmable Social Robots for Everyone: A Teacher-in-the-Loop Learning from Demonstration Framework

职业生涯：面向所有人的可编程社交机器人：教师在演示框架中进行循环学习

• 批准号: 2238088
• 负责人: Wing-Yue Louie
• 金额: $ 58.68万
• 依托单位: Oakland University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2028-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2238088&HistoricalAwards=false
• 关键词: CAREER; Towards; Programmable; Social; Robots

Social robots have demonstrated significant positive impacts across a range of application areas including delivering K-12 education, therapy for autism spectrum disorder, and older adult care. Although they are intended to provide much needed support in these areas, social robots remain inaccessible to individuals (e.g., healthcare professionals, educators, and service industry workers) who could best use the technology to produce the greatest impact to our society. This is because social robots still require significant technical expertise to be deployed and there is currently no clear pathway for laypeople to utilize social robots for their desired applications. This research will bridge the gap between social robots and individuals with no robotics/programming experience so that social robots can be made accessible to everyone. This will be accomplished by developing approaches and technologies that empower laypeople to teach and customize social robots for their desired applications, thereby transforming our emerging healthcare and education workforce by increasing their capacity for delivering services previously not possible. Project outcomes will also broadly impact education by supporting interdisciplinary workforce development and broadening participation in STEM for individuals from diverse backgrounds. To address these goals, this project will investigate fundamental approaches and techniques that enable a layperson to teach a social robot via demonstration. Teaching is often an iterative process that requires a teacher and learner to coordinate their efforts towards the mutual goal of knowledge transfer but there currently is minimal effort in engaging a layperson during the robot teaching process beyond providing data or examples the robot can learn from. This research will keep teachers-in-the-loop throughout the entire robot learning process by: 1) developing interfaces that enable a teacher to prepare high-quality demonstrations, 2) developing approaches that improve a teacher's understanding of models learned by a robot, and 3) developing approaches that enable teachers to integrate domain knowledge while they teach a robot. Project outcomes will both advance knowledge on enabling laypeople to independently teach a social robot and our fundamental understanding on how humans transfer social knowledge to machines.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

社交机器人已经在一系列应用领域表现出显著的积极影响，包括提供K-12教育，自闭症谱系障碍治疗和老年人护理。尽管它们旨在为这些领域提供急需的支持，但社交机器人仍然无法为个人所用（例如，医疗保健专业人员，教育工作者和服务业工人）谁可以最好地利用技术，以产生最大的影响，我们的社会。这是因为社交机器人仍然需要大量的技术专业知识来部署，并且目前外行还没有明确的途径来利用社交机器人来实现他们想要的应用。这项研究将弥合社交机器人和没有机器人/编程经验的个人之间的差距，使每个人都可以使用社交机器人。这将通过开发方法和技术来实现，使外行能够为他们所需的应用程序教授和定制社交机器人，从而通过提高他们提供服务的能力来改变我们新兴的医疗保健和教育劳动力。项目成果还将通过支持跨学科劳动力发展和扩大来自不同背景的个人对STEM的参与，对教育产生广泛影响。为了实现这些目标，该项目将研究基本的方法和技术，使外行通过演示教社交机器人。教学通常是一个迭代的过程，需要教师和学习者协调他们的努力，以实现知识转移的共同目标，但目前在机器人教学过程中，除了提供机器人可以学习的数据或示例之外，参与外行的努力很少。这项研究将保持教师在整个机器人学习过程中的循环：1）开发界面，使教师能够准备高质量的演示，2）开发方法，提高教师对机器人学习模型的理解，以及3）开发方法，使教师能够在教机器人的同时整合领域知识。该项目的成果将促进人们对社会机器人的独立教学的认识，以及我们对人类如何将社会知识转移到机器上的基本理解。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。