摘要
在人机交互时,由于人体下肢外骨骼获取的传感器信号滞后于人体运动实际形式,从而导致外骨骼机器人无法实时跟随髋关节、膝关节的运动,出现不能提供助力的问题。设计了一种下肢外骨骼模型,在此基础上,通过力/力矩传感器来获取信号,利用基于卡尔曼滤波算法对获取到的信息进行运动预判,然后将预判信号输入到下肢外骨骼机器人模型简化后的二连杆运动学模型上,通过采用PD控制检验系统稳定性以及预判精确性。最后进行MATLAB仿真实验,结果表明:信号经过卡尔曼滤波后能够有效预判人体运动形式,外骨骼下肢摆动腿在人体运动时能够进行有效地跟随,从而弥补延时。
In the human-machine interaction(HMI), the sensor signal acquired by the lower extremity exoskeleton of the human body lags behind the actual form of the human body motion, thereby causing the exoskeleton robot to fail to follow the motion of the hip joint and the knee joint in real time, and there is a problem that no assistance can be provided. A lower extremity exoskeleton model is designed. Based on which, the force/torque sensor to obtain the signal, the use of Kalman filter algorithm to obtain the information obtained by the motion prediction, and then input the prediction signal to the lower extremity exoskeleton on the simplified two-link kinematics model of the robot model, the stability of the system and the accuracy of the prediction were checked by using Proportion-Derivative(PD) control. Finally, the MATLAB simulation experiment results show that the signal can be used to effectively predict the form of human movement after Kalman filtering. The exoskeleton leg swing can effectively follow when the human body is moving, thus making up for the delay.
作者
曹宇飞
樊军
CAO Yufei;FAN Jun(College of Mechanical Engineering, Xinjiang University, Urumqi Xinjiang 830047, China)Abstract: In the human-machine interaction (HMI)
出处
《机床与液压》
北大核心
2019年第15期16-20,共5页
Machine Tool & Hydraulics
基金
国家自然科学基金资助项目(11462021)
