Trajectory generation and control of a knee exoskeleton based on dynamic movement primitives for sit to stand assistance
Abstract This paper presents a novel control approach for a knee exoskeleton to assist individuals with lower extremity weakness during sit to stand motion. The proposed method consists of a trajectory generator and an impedance controller. The trajectory generator uses a library of sample trajectories as the training data and the initial joint angles as the input to predict the user's intended sit to stand trajectory. Utilizing the dynamic movement primitives theory, the trajectory generator represents the predicted trajectory in a time normalized and rather a flexible framework. The impedance controller is then employed to provide assistance by guiding the knee joint to move along the predicted trajectory. Moreover, the human exoskeleton interaction force is used as the feedback for on line adaptation of the trajectory speed. The proposed control strategy was tested on a healthy adult who wore the knee exoskeleton on his leg. The subject was asked to perform a number of sit to stand movements from different sitting positions. Next, the measured data and the inverse dynamic model of the human exoskeleton system are used to calculate the knee power and torque profiles. The results reveal that average muscle activity decreases when the subject is assisted by the exoskeleton.
Adv. Robotics