Impedance control based on the human gait data for lower limb rehabilitation robot

Abstract

The lower limb rehabilitation robots (LLRR) have brought significant support to patients with movement disorders, and the research of LLRR has also become one hot topic in robotic fields. However, how to reduce the contact force between the rehabilitation robot and the human is becoming a challenge. Therefore, in order to make robots and humans form a most concerted whole, this paper designs a novel controller based on real human gait data. In detail, the Nokov motion capture system (NMCS) is used to collect human gait data, and then the collected data is fed to the designed control system as reference control signals. That is, the controller can simulate the interaction between the lower limbs of the human body and the environment to provide human-like abilities for the LLRR. To confirm the effectiveness of the proposed method, the simulation results based experimental date is given. The results show a satisfactory trajectory tracking effect, and the stability can be guaranteed.