NRI: INT: Learning-Enabled Robot Support of Daily Activities for Successful Activity Completion

NRI：INT：支持学习的机器人支持日常活动以成功完成活动

• 批准号: 1734558
• 负责人: Diane Cook
• 金额: $ 100万
• 依托单位: Washington State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1734558&HistoricalAwards=false
• 关键词: NRI; INT; Learning; Enabled; Robot

The population is aging - the estimated number of individuals over the age of 85 will triple by 2050. Even in our current population an estimated 9% of adults age 65+ and 50% of adults age 85+ need assistance with everyday activities, and the annual cost for the United States is roughly $2 trillion. Given the economic and quality of life costs, there is a critical need to better use smart technologies so that individuals can live independently in their own homes, helping both individuals and society as a whole. This proposed work will create a novel multi-agent robot system, called Robotic Activity Support (RAS), that provides in-home activity support for older adults and others that need assistance to independently perform common activities of daily living. The system will rely on cooperation between a smart home and a mobile robot to learn activity routines for an individual. RAS will use this information to provide activity interventions that help smart home residents initiate and successfully complete important daily activities and improve functional independence. Rather than explore co-robot systems with multiple identical platforms, the system will represent a collaboration between a mobile robot, a smart home agent with multiple heterogeneous sensors and multiple humans with distinct roles. For this collaboration, the project team will employ a custom robot that will partner with the team's CASAS smart home architecture. RAS will incorporate caregiver-in-the-loop active learning to improve its models. the team will use an iterative user-centered development process to enhance the mobile robotic platform design. The RAS system will use active learning from both the resident and caregiver to learn common activities and how it can support such activities. For example, the robot may prompt a resident to eat breakfast if she does not initiate the task at the normal time, remind the resident where the cereal is, and notify a nearby caregiver if help is needed that is beyond the robot's capabilities. The team will evaluate RAS on historic smart home data (from their more than 100 deployments), in their on-campus smart home, and in a home with a healthy older adult caregiver, as well as an older adult exhibiting cognitive limitations.

人口正在老龄化——预计到 2050 年，85 岁以上的人数将增加两倍。即使在我们目前的人口中，估计也有 9% 的 65 岁以上成年人和 50% 的 85 岁以上成年人在日常活动中需要帮助，而美国每年的成本约为 2 万亿美元。考虑到经济和生活质量成本，迫切需要更好地使用智能技术，以便个人能够在自己的家中独立生活，从而帮助个人和整个社会。这项拟议的工作将创建一种新型多智能体机器人系统，称为机器人活动支持（RAS），为老年人和其他需要帮助独立执行日常生活活动的人提供家庭活动支持。该系统将依靠智能家居和移动机器人之间的合作来学习个人的活动习惯。 RAS 将利用这些信息提供活动干预措施，帮助智能家居居民启动并成功完成重要的日常活动并提高功能独立性。该系统不是探索具有多个相同平台的协作机器人系统，而是代表移动机器人、具有多个异构传感器的智能家居代理和具有不同角色的多个人之间的协作。对于此次合作，项目团队将采用一个定制机器人，与该团队的 CASAS 智能家居架构合作。 RAS 将结合护理人员在循环中的主动学习来改进其模型。该团队将使用以用户为中心的迭代开发流程来增强移动机器人平台的设计。 RAS 系统将利用住院医师和护理人员的主动学习来学习常见活动以及如何支持这些活动。例如，如果居民没有在正常时间启动任务，机器人可能会提示居民吃早餐，提醒居民麦片在哪里，并在需要超出机器人能力范围的帮助时通知附近的护理人员。该团队将根据历史智能家居数据（来自 100 多个部署）、校园智能家居以及有健康老年人护理人员以及表现出认知缺陷的老年人的家庭中评估 RAS。

项目成果

Robot-enabled support of daily activities in smart home environments

机器人支持智能家居环境中的日常活动

• DOI: 10.1016/j.cogsys.2018.10.032
• 发表时间: 2019-05-01
• 期刊: Cognitive Systems Research
• 影响因子: 3.9
• 作者: Garrett Wilson;Christopher Pereyda;N. Raghunath;G. V. D. L. Cruz;Shivam Goel;Sepehr Nesaei;B. Minor;M. Schmitter;Matthew E. Taylor;D. Cook
• 通讯作者: D. Cook

Learning Activity Predictors from Sensor Data: Algorithms, Evaluation, and Applications

从传感器数据学习活动预测：算法、评估和应用

• DOI: 10.1109/tkde.2017.2750669
• 发表时间: 2017-12-01
• 期刊: IEEE Transactions on Knowledge and Data Engineering
• 影响因子: 8.9
• 作者: Minor B;Doppa JR;Cook DJ
• 通讯作者: Cook DJ

Real-Time Change Point Detection with Application to Smart Home Time Series Data

实时变化点检测及其在智能家居时间序列数据中的应用

• DOI: 10.1109/tkde.2018.2850347
• 发表时间: 2019-05
• 期刊: IEEE Transactions on Knowledge and Data Engineering
• 影响因子: 8.9
• 作者: Aminikhanghahi, Samaneh;Wang, Tinghui;Cook, Diane J.
• 通讯作者: Cook, Diane J.

A Robot Activity Support (RAS) system for persons with memory impairment: Comparing older and younger adults' perceptions of the system

针对记忆障碍人士的机器人活动支持（RAS）系统：比较老年人和年轻人对该系统的看法

• DOI: 10.4017/gt.2020.19.003.07
• 发表时间: 2020-07-28
• 期刊: Gerontechnology
• 作者: Raghunath N;Pereyda C;Frow JF;Cook D;Schmitter-Edgecombe M
• 通讯作者: Schmitter-Edgecombe M

Context-Aware Delivery of Ecological Momentary Assessment

环境感知的生态瞬时评估交付

• DOI: 10.1109/jbhi.2019.2937116
• 发表时间: 2020-04
• 期刊: IEEE Journal of Biomedical and Health Informatics
• 影响因子: 7.7
• 作者: Aminikhanghahi S;Schmitter-Edgecombe M;Cook DJ
• 通讯作者: Cook DJ