Background: In recent years, exoskeleton robot technology has developed rapidly. Exoskeleton robots that can be worn on a human body and provide additional strength, speed or other abilities. Exoskeleton robots have a wide range of applications, such as medical rehabilitation, logistics and disaster relief and other fields.
Objective: The study goal is to propose a lower limb assistive exoskeleton robot to provide extra power for wearers.
Methods: The mechanical structure of the exoskeleton robot was designed by using bionics principle to imitate human body shape, so as to satisfy the coordination of man-machine movement and the comfort of wearing. Then a gait prediction method based on neural network was designed. In addition, a control strategy according to iterative learning control was designed.
Results: The experiment results showed that the proposed exoskeleton robot can produce effective assistance and reduce the wearer's muscle force output.
Conclusion: A lower limb assistive exoskeleton robot was introduced in this paper. The kinematics model and dynamic model of the exoskeleton robot were established. Tracking effects of joint angle displacement and velocity were analyzed to verify feasibility of the control strategy. The learning error of joint angle can be improved with increase of the number of iterations. The error of trajectory tracking is acceptable.
Keywords: Assistive exoskeleton robot; dynamic analysis; gait prediction method; kinematics analysis; lower limb exoskeleton robot.