Reinforcement Learning System Automatically Trains Prosthetic Legs

Powered leg prostheses can give amputees the ability to walk for long periods of time and to do so briskly. The reality is that these devices are pretty clunky and programming them to operate smoothly to produce a natural gait takes hours, and the results are rarely perfect. Scientists at North Carolina State University, the University of North Carolina, and Arizona State University have now developed an automated tuning system that relies purely on a technique called reinforcement learning to do its job. This allows the patient to simply walk with a new prosthetic on a treadmill while guided by a therapist. The system monitors the intentions of the patient and movement of the prosthetic, and adjusts in real time based on the readings.