Dr. Damiano Zanotto, assistant professor in the Department of Mechanical Engineering, was recently awarded a National Science Foundation (NSF) CAREER Award in the amount of $597,471. His project, entitled “Reinforcement-Learning Assist-as-Needed Control for Robot-Assisted Gait Training” will develop adaptive, assist-as-needed controllers for a powered ankle brace. Such systems may promote the learning of desired gait patterns during physical rehabilitation. Reinforcement learning will be used to shape person-specific control policies that balance movement error and user effort.
There are two main research objectives in this project. The first will establish new reinforcement learning control strategies capable of self-adapting the control policy of a robotic orthosis to optimally balance the tradeoff between movement error and user effort, with the goal of promoting human learning of target gait trajectories. The second objective will extend these novel control strategies to situations wherein the desired target motion is unknown to the controller and must be computed on-line. The research promises to advance a fundamental understanding of the bidirectional adaptations that can arise when adaptive human and machine intelligences interact through physical channels, here in the context of gait rehabilitation.
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