Admittance Control of Powered Exoskeletons Based on Joint Torque Estimation

In recent years, exoskeletons have been widely accepted as rehabilitative and walking assistive devices for either healthy persons or patients with mobility impairment. Depending on mobility of the wearers, the control strategies for exoskeletons may differ significantly. This paper aims at developing an admittance control framework for exoskeletons to assist healthy persons in safer, faster, or more energy-efficient walking. A crucial step to accomplish assistive walking for healthy persons is to detect their intention. Direct sensing of the wearer's biological signals, such as electromyography (EMG) and electroencephalography (EEG), requires additional sensors, which increases the cost and makes it inconvenient for the wearer to put on and take off the exoskeleton. Instead, we propose to detect the wearer's intention by estimating the total torques applied from the wearer to the human-exoskeleton system based on the motor current and joint angles. Then the velocity commands to the joint motors are generated according to the estimated torque and a predefined mechanical admittance function of each joint. Consequently, the exoskeleton complies with the wearer's intention. Rigorous theoretical analysis is performed on robust stability of the closed-loop system. Then experiments are carried out to verify the accuracy and robustness of the proposed torque estimation algorithm. In addition, experimental data show that the wearer's gait can be shaped in a desired way by choosing an appropriate admittance function in the proposed admittance control loop.