The Design and Application of an Assistive Hip Joint Exoskeleton for Tower Climbing

Abstract

In order to ensure the safety of maintenance personnel during tower climbing and improve the efficiency of power maintenance work, this study designed an assistive hip joint exoskeleton robot and analyzed the kinematic data obtained from tower climbers during the climbing process. A neural-network-based assistive control algorithm for tower climbing was created, and a tower climbing experiment was conducted with volunteers. The surface electromyographic (sEMG) signals of four muscles, namely the biceps femoris (BF), gluteus maximus (GM), semimembranosus (SM), and semitendinosus (ST), were collected to evaluate the performance of the robot. The experimental results show that the exoskeleton robot could reduce the root mean square (RMS) values of the sEMG signals of the main force-generating muscles related to the hip joint. This suggests that the robot can effectively assist personnel in tower climbing operations.