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Inverse Reinforcement Learning

AR3n: A Reinforcement Learning-Based Assist-as-Needed Controller for Robotic Rehabilitation

September 16, 2024 by Shrey Pareek, Harris J Nisar, Thenkurussi Kesavadas

In this article, we present AR3n (pronounced as Aaron), an assist-as-needed (AAN) controller that utilizes reinforcement learning (RL), to supply adaptive assistance during a robot-assisted handwriting rehabilitation task. Unlike previous AAN controllers, our method does not rely on patient-specific controller parameters or physical models. We propose the use of a virtual … [Read more...] about AR3n: A Reinforcement Learning-Based Assist-as-Needed Controller for Robotic Rehabilitation

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As the flagship magazine of the IEEE Robotics and Automation Society, IEEE Robotics and Automation Magazine (RAM) covers the latest developments in robotics and automation. Its scope ranges from cutting-edge technological advances to emerging social, economic, ethical, and policy issues shaping the field.  Published quarterly (March, June, September, and December), RAM features both high-impact original research articles written in an engaging and accessible style, as well as reviews, columns and opinion pieces addressing a wide range of timely topics.

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IEEE Robotics & Automation Magazine  publishes four issues per year: March, June, September and December.