CAREER: End-User Robot Programming by Multimodal Instruction

职业：通过多模式指令进行最终用户机器人编程

• 批准号: 2143704
• 负责人: Chien-Ming Huang
• 金额: $ 60万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2143704&HistoricalAwards=false
• 关键词: CAREER; End; User; Robot; Programming

This research will bring assistive robots within reach of average people by enabling such users to easily instruct them to help complete useful daily tasks, so that ultimately many lay people, especially older adults who wish to continue living independently, will be better able to benefit from the technology. It is projected that by 2060, the percent of the U.S. population aged 65 years or older will reach 23.5%. Consequently, the demand for healthcare resources and societal support are growing substantially. Our society, however, is presently experiencing a shortage of caregivers, and current caregivers are at increased risk for burnout. Project outcomes will allow users with little or no knowledge of coding or engineering to easily customize their robots through a variety of means (e.g., demonstrations) to perform tasks that meet their needs, such as organizing their shoes or cleaning the bathroom. Additional broad impact of the work will derive from educational activities that broaden participation in computing by mentoring students with diverse backgrounds and dissemination of research findings to a wide age range of learners. To achieve these goals, this project will investigate the science of and fundamental technologies for robot programming by natural multimodal instruction. Human instructions are inherently multimodal, but the rich information embedded in them is not always adequately captured and utilized by robot systems. The research will computationally model multimodal instructional cues to characterize demonstration quality for improved learning, assist lay people in their task demonstrations, and enhance the user experience in the face of instructional difficulties. The work will create open-source systems for robot programming by multimodal demonstration, and produce quantitative and qualitative knowledge of how older adults naturally instruct robots and how they may use programmable robotic assistance to support them in their daily tasks at home.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.

这项研究将通过使这些用户能够轻松地指导他们帮助完成有用的日常任务，使普通人能够接触到辅助机器人，因此最终许多非专业人士，特别是希望继续独立生活的老年人，将能够更好地受益于这项技术。 据预测，到2060年，美国65岁以上人口的比例将达到23.5%。因此，对医疗资源和社会支持的需求大幅增长。然而，我们的社会目前正经历着护理人员短缺，目前的护理人员面临着职业倦怠的风险增加。项目成果将允许很少或根本不了解编码或工程的用户通过各种手段轻松定制他们的机器人（例如，演示）来执行满足他们需求的任务，例如整理鞋子或清洁浴室。这项工作的其他广泛影响将来自教育活动，这些活动通过指导具有不同背景的学生和向广泛年龄段的学习者传播研究成果来扩大对计算的参与。为了实现这些目标，本项目将研究自然多模态指令机器人编程的科学和基础技术。 人类指令本质上是多模态的，但嵌入其中的丰富信息并不总是被机器人系统充分捕获和利用。 该研究将计算建模多模态教学线索，以表征演示质量，以提高学习，协助外行人在他们的任务演示，并提高用户体验，在面对教学困难。 这项工作将通过多模态演示创建机器人编程的开源系统，并产生老年人如何自然地指导机器人以及他们如何使用可编程机器人辅助来支持他们在家中的日常任务的定量和定性知识。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而被认为值得支持。

项目成果

Co-Designing with Older Adults, for Older Adults: Robots to Promote Physical Activity

与老年人共同设计，为老年人服务：促进身体活动的机器人

• DOI: 10.1145/3568162.3576995
• 发表时间: 2023
• 期刊: Proceedings of 2023 ACM/IEEE International Conference on Human-Robot Interaction
• 作者: Antony, Victor Nikhil;Cho, Sue Min;Huang, Chien-Ming
• 通讯作者: Huang, Chien-Ming

Modeling Human Response to Robot Errors for Timely Error Detection

模拟人类对机器人错误的反应，以便及时检测错误

• DOI: 10.1109/iros47612.2022.9981726
• 发表时间: 2022
• 期刊: Proceedings of 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems
• 作者: Stiber, Maia;Taylor, Russell;Huang, Chien-Ming
• 通讯作者: Huang, Chien-Ming

On Using Social Signals to Enable Flexible Error-Aware HRI

• DOI: 10.1145/3568162.3576990
• 发表时间: 2023-03
• 期刊: Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction
• 作者: Maia Stiber;R. Taylor;Chien-Ming Huang

Older Adults' Task Preferences for Robot Assistance in the Home

老年人对家庭机器人辅助的任务偏好

• 发表时间: 2023
• 期刊: 2023 AAAI Workshop on User-Centric Artificial Intelligence for Assistance in At-Home Tasks
• 作者: Ajaykumar, Gopika;Haung, Chien-Ming
• 通讯作者: Haung, Chien-Ming