Georgia Tech's AI-fueled exoskeleton adapts to every step, helping patients relearn to walk with less effort and more confidence. Traditional robotic exoskeleton models require extensive manual calibration, but Aaron Young, associate professor in the George W. Woodruff School of Mechanical Engineering, and his team developed AI-driven software that automatically adapts to each user’s gait. By using a neural network, the system continuously monitors and adjusts support with each step, gradually syncing with the wearer’s unique movement. In this study, the team used a hip exoskeleton that delivers torque at the hip joint to help stroke survivors walk more easily.