NRI: Integrated Soft Wearable Robotics Technology to Assist Arm Movement of Infants with Physical Impairments

这个国家机器人计划（NRI-3.0）项目推进了软机器人技术，用于新一代可穿戴上肢（UE）设备，用于有运动障碍的婴儿。总体目标是推断婴儿的意图，评估援助的需要，并在适当的时候协同帮助探索性达到行动的表现。目前的儿童可穿戴辅助技术缺乏必要的功能和可访问性，以达到高效和适应用户。该项目通过发现和创建适当的传感和控制硬件和算法来解决这一差距，以实现有效的婴儿-机器人物理交互。该项目汇集了来自工程、计算机科学、化学和康复的专家，并提出了软机器人设计、动力学和控制、计算机视觉和嵌入式系统的跨学科研究问题。丰富的一套引人入胜的问题将提供丰富的研究机会，为不同的本科生队列。该项目整合了加州大学河滨分校（UCR）（一所西班牙裔服务机构）举办的K-12外展活动的现有努力，以扩大代表性不足的少数群体的参与。该项目研究了软可穿戴机器人的实时、基于传感器的闭环控制，目标是作为上肢辅助设备。该项目以三种方式推进基础工程知识。1)通过无镜头相机进行生物力学应用的视觉传感，这种相机可以采取任意形状，并且具有超薄的外形因素，可以与柔软材料和表面无缝集成。该项目开发了一类新的视觉对象识别和跟踪算法，用于在UE辅助设备中使用无镜头相机系统。2)软流体逻辑电路，以减少控制和操作气动驱动软机器人所需的刚性电子元件的数量。该技术已被证明在辅助技术应用中是有价值的，如果设备组件的尺寸和重量保持较低，则可以更好地实现与人类的物理交互。3)共享人机导纳控制，使用实时数据来估计设备的动态模型及其与人的交互。目标是通过在两种操作模式之间自主切换来提供所需的帮助：要么屈服于用户的意图，要么应用辅助力量帮助用户的手臂到达所需的物体。总的来说，这项研究将创造新的具身智能形式，以提高可穿戴辅助软机器人与人类用户合作感知和行动的能力。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This National Robotics Initiative (NRI-3.0) project advances soft robotics technology for a new generation of wearable upper extremity (UE) devices for infants with movement impairments. The overarching goal is to infer the infant's intent, evaluate the need for assistance, and when appropriate collaboratively aid the performance of explorative reaching actions. Current pediatric wearable assistive technology lacks the necessary functionality and accessibility to be efficient and adaptive to the user. The project addresses this gap through the discovery and creation of appropriate sensing and control hardware and algorithms for effective infant-robot physical interactions. The project brings together experts from Engineering, Computer Science, Chemistry, and Rehabilitation and poses cross-disciplinary research questions in soft robot design, dynamics and control, computer vision, and embedded systems. The rich set of engaging problems will provide abundant research opportunities for a diverse cohort of undergraduate students. The project integrates existing efforts in K-12 outreach events hosted at the University of California, Riverside (UCR) -- a Hispanic Serving Institution -- to broaden participation of under-represented minority groups.The project investigates real-time, sensor-based closed-loop control for soft wearable robotics targeted to serve as upper extremity (UE) assistive devices. The project advances fundamental engineering knowledge in three ways. 1) Visual sensing for biomechanical applications via lensless cameras, that can take arbitrary shapes and have an ultra-thin form factor that allows seamless integration with soft materials and surfaces. The project develops a new class of visual object recognition and tracking algorithms for use of lensless camera systems in UE assistive devices. 2) Soft fluidic logic circuits to reduce the amount of rigid electronic components required to control and operate pneumatically actuated soft robots. This technique has been shown to be valuable in assistive technology applications where physical interaction with humans is better achieved if the size and weight of the device components remain low. 3) Shared human-robot admittance control, that uses data in real-time to estimate dynamic models for the device and its interaction with the human. The goal is to provide as-needed assistance by autonomously switching between two operating modes: either yielding to the user’s intention, or applying assistive forces to help the user's arm reach the desired object. Overall, this research will create new forms of embodied intelligence to advance the capacity of wearable assistive soft robots to perceive and act in collaboration with a human user.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.