A team of researchers have demonstrated a new method that leverages AI and computer simulations to train robotic exoskeletons that can help users save energy while walking, running, and climbing stairs. Described in a study published in Nature, the novel method rapidly develops exoskeleton controllers to assist locomotion without relying on lengthy human-involved experiments. Moreover, the method can apply to a wide variety of assistive devices beyond the hip exoskeleton demonstrated in this research.
“It can also apply to knee or ankle exoskeletons, or other multi-joint exoskeletons,” said Xianlian Zhou, associate professor and director of NJIT’s BioDynamics Lab. In addition, it can similarly be applied to above-the-knee or below-the-knee prosthesis, providing immediate benefits for millions of able-bodied and mobility-impaired individuals, he said. “Our approach marks a significant advancement in wearable robotics, as our exoskeleton controller is exclusively developed through AI-driven simulations,” Zhou explains. “Moreover, this controller seamlessly transitions to hardware without requiring further human subject testing, rendering it experiment-free.” To read the full story.