AI and computer simulations help exoskeletons take the strain

The novel method is said to rapidly develop exoskeleton controllers to assist locomotion without relying on lengthy human-involved experiments. Detailed in Nature, the method can apply to a 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 the New Jersey Institute of Technology’s BioDynamics Lab. In addition, it can similarly be applied to above-the-knee or below-the-knee prosthesis, he said in a statement.

"Our approach marks a significant advancement in wearable robotics, as our exoskeleton controller is exclusively developed through AI-driven simulations," said Zhou.

According to NJIT, this breakthrough holds promise for aiding individuals with mobility challenges, including the elderly or stroke survivors, without necessitating their presence in a laboratory or clinical setting for extensive testing.

“This work proposes and demonstrates a new method that uses physics-informed and data-driven reinforcement learning to control wearable robots in order to directly benefit humans,” said Hao Su, corresponding author of a paper on the work and an associate professor of mechanical and aerospace engineering at North Carolina State University.