摘要
Lower-limb exoskeletons can provide paraplegics with the ability to restore gait function. In the community ambulation, the user would frequently meet different floors, doorsills, and other obstacles. Therefore, parametric gait generation is a significant issue for this kind of exoskeletons. In this paper, a parametric gait online generation approach is proposed, which combines a parametric gait control method with a torque compensation control strategy, based on the state machine. In the torque compensation control, the reference tra- jectories of joint positions are obtained through compensating gravity, inertia, and friction, which is intent on the natural and well-directed source data. Based on the reference trajectories, the parametric gait control method is established, in which the gait can be controlled via three parameters： velocity, step-length, and step-height. Two test cases are performed on three healthy subjects. The results demonstrate that the parametric gait can be online generated smoothly and correctly, meanwhile every variable step can be triggered as users expect. The effectiveness and practicability of the gait generation approach proposed in this paper are validated. In addition, this research is the foundation of autonomous gait planning.
Lower-limb exoskeletons can provide paraplegics with the ability to restore gait function. In the community ambulation, the user would frequently meet different floors, doorsills, and other obstacles. Therefore, parametric gait generation is a significant issue for this kind of exoskeletons. In this paper, a parametric gait online generation approach is proposed, which combines a parametric gait control method with a torque compensation control strategy, based on the state machine. In the torque compensation control, the reference tra- jectories of joint positions are obtained through compensating gravity, inertia, and friction, which is intent on the natural and well-directed source data. Based on the reference trajectories, the parametric gait control method is established, in which the gait can be controlled via three parameters： velocity, step-length, and step-height. Two test cases are performed on three healthy subjects. The results demonstrate that the parametric gait can be online generated smoothly and correctly, meanwhile every variable step can be triggered as users expect. The effectiveness and practicability of the gait generation approach proposed in this paper are validated. In addition, this research is the foundation of autonomous gait planning.
基金
This work is supported by the National Key R＆D Program of China （Grant 2017YFB1302301）, and the Joint Research Fund （U1613219） between the National Nature Science Foundation of China （NSFC） and Shen Zhen.
