I-Corps: Artificial Intelligence (AI)-Enabled and Digital Twin Interactive Robots for Facility Hygiene and Human Health

I-Corps：支持人工智能 (AI) 的数字孪生交互式机器人，用于设施卫生和人类健康

• 批准号: 2227108
• 负责人: Shuai Li
• 金额: $ 5万
• 依托单位: University of Tennessee Knoxville
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2227108&HistoricalAwards=false
• 关键词: Corps; Artificial; Intelligence; AI; Enabled

The broader impact/commercial potential of this I-Corps project is the development of a mobile disinfection device. The COVID-19 pandemic, seasonal epidemics of flu, and other infections placed heavy burdens on society. This proposed technology may improve current cleaning and disinfection practices with an intelligent robotic system. The proposed solution is designed to improve cleaning and disinfection efficacy, enhance personal hygiene and public health, and relieve the high workload and exposure risks facing cleaning and disinfection workers. These benefits may reduce the facility operational costs as well as opportunity costs from infection within facilities, and generate positive societal and economic impacts. The proposed service business model may facilitate the adoption of disinfection and service robots as a flexible choice, creating new opportunities and serving broader areas in the post-pandemic age.This I-Corps project is based on the development of an artificial intelligence (AI)-enabled and digital-twin interactive robot that adapts to ambient environments, social processes, and building dynamics for automated, continuous, precise, and socially-friendly disinfection. The key innovations include using a digital-twin based simulation and deep learning environment to train the robots to predict and perceive contaminated areas for precision disinfection at both the building and room levels. This research improves surface disinfection efficiency and effectiveness. Pathogen infection risks derived from data-driven modeling and simulation may provide a new stream of information for robot navigation to prioritize disinfection routes. In addition to the precision disinfection that specifically targets contaminated areas, the robots will learn to understand the social contexts (e.g., human activity and privacy within a room) to operate in the presence of humans without interrupting normal activities and exposing harmful substances such as ultraviolet lights to humans, enabling safe and socially-friendly disinfection. Augmented by high-fidelity virtual simulations, imitation learning will be developed to train the robots to learn the social and physical constraints and adapt their disinfection maneuvers with respect to the context and object geometry enabling complete, efficient, and safe disinfection. The technology may enable a single smart solution to maintain environmental hygiene and human health.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.

该 I-Corps 项目更广泛的影响/商业潜力是移动消毒设备的开发。 COVID-19大流行、季节性流感流行和其他感染给社会带来了沉重负担。这项提出的技术可以通过智能机器人系统改善当前的清洁和消毒实践。该解决方案旨在提高清洁和消毒效果，增强个人卫生和公共卫生，并减轻清洁和消毒人员面临的高工作量和暴露风险。这些好处可以降低设施运营成本以及设施内感染的机会成本，并产生积极的社会和经济影响。拟议的服务商业模式可能会促进采用消毒和服务机器人作为一种灵活的选择，从而在后流行病时代创造新的机会并服务更广泛的领域。这个I-Corps项目基于人工智能（AI）的开发-启用的数字孪生交互式机器人，可适应周围环境、社会流程和建筑动态，实现自动化、连续、精确和社会友好的消毒。关键创新包括使用基于数字孪生的模拟和深度学习环境来训练机器人预测和感知污染区域，以便在建筑物和房间层面进行精确消毒。这项研究提高了表面消毒的效率和效果。来自数据驱动的建模和模拟的病原体感染风险可以为机器人导航提供新的信息流，以确定消毒路线的优先顺序。除了专门针对污染区域的精准消毒外，机器人还将学习了解社会环境（例如房间内的人类活动和隐私），以便在人类存在的情况下进行操作，而不会中断正常活动并暴露紫外线等有害物质为人类提供照明，实现安全且对社会友好的消毒。通过高保真虚拟模拟的增强，将开发模仿学习来训练机器人学习社会和物理限制，并根据环境和物体几何形状调整其消毒操作，从而实现完整、高效和安全的消毒。该技术可以通过单一智能解决方案来维护环境卫生和人类健康。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。