Researchers have demonstrated a new method that leverages artificial intelligence and computer simulations to train robotic exoskeletons to autonomously help users save energy while walking, running and climbing stairs.
"The key idea here is that the embodied AI in a portable exoskeleton is learning how to help people walk, run or climb in a computer simulation, without requiring any experiments," says Su. "We have developed a way to train and control wearable robots to directly benefit humans," says Shuzhen Luo, first author of the paper and a former postdoctoral researcher at NC State. Luo is now an assistant professor at Embry-Riddle Aeronautical University.
While this study focused on the researchers' work with able-bodied people, the new method also applies to robotic exoskeleton applications aimed at helping people with mobility impairments. This research was done with support from the National Science Foundation under awards 1944655 and 2026622; the National Institute on Disability, Independent Living, and Rehabilitation Research, under award 90DPGE0019 and Switzer Research Fellowship SFGE22000372; and the National Institutes of Health, under award 1R01EB035404.