Whole-body Control Based Lifting Assistance Simulation for Exoskeletons

Abstract

Exoskeletons can help humans in a variety of ways in performing tasks. In particular, during the lifting operation, a human places a great burden on the knee or waist joint, and the exoskeleton can reduce the risks of this task. However, due to the weight of the exoskeleton itself and the movement of the overall center of gravity, balance ability and efficiency may decrease. Therefore, an appropriate assistance torque distribution strategy is required to achieve high performance with the exoskeleton. In order to solve the aforementioned problem, we propose an assistance method based on whole-body control. The proposed algorithm is meaningful because it is different from other simple model-based controllers. The controller fully utilize the dynamics to achieve a high performance. In addition, by adding a straight leg cost term, the singularity problem in the fully extended configuration was solved. This method finds the optimal solution that satisfies various constraints and minimizes the objective functions. Each objective is composed of a balancing-related term that minimizes the variation in the center of gravity, a term that supports the weight of the human and exoskeleton, a term that solves the singularity problem and a term related to efficiency. In this paper, first, a motion capture experiment is performed to analyze a human's lifting motion. Through this experiment, the trajectory of each joint angle is obtained. With PD (proportional-derivative) feedback from the joint trajectories, the exoskeleton generates human torque in the simulation and implements a lifting operation. Second, a simulation is performed with the proposed controller. As a result, it is confirmed that the proposed method reduces the amount of human joint torque and increases stability and efficiency.