Data-Efficient Reinforcement Learning Control of Robotic Lower-Limb Prosthesis With Human in the Loop

Robotic lower limb prostheses provide new opportunities to help transfemoral amputees regain mobility. However, their application is impeded by that the impedance control parameters need to be tuned and optimized manually by prosthetists for each individual user in different task environments.