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

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.