Research on compliance control strategy of elbow–wrist rehabilitation robot based on information fusion

Abstract. Compliance control is the key to human–robot physical interaction, which can improve the safety and comfort of robot-assisted rehabilitation. Aiming to address the problems of the large time delay and low compliance of the system caused by the slow speed of motion intention recognition based on the force signal, this paper integrates the force signal and the surface electromyography (sEMG) signal as the input of the elbow–wrist rehabilitation robot, which improves the responsiveness of the system. To further enhance the trajectory-tracking performance of the system, a sliding-mode controller based on the double exponential reaching law (DE-SMC) is designed. Then, the force and sEMG signal fusion experiment and the compliance control experiment were carried out. The former showed that the fused force signal would judge the subject's motion intention 102.5 ms in advance, while the latter confirmed that the compliance control strategy based on the DE-SMC controller effectively improved the compliance of elbow and radioulnar joint movement.