徐铃辉, 杨巍, 杨灿军, 张继宇, 王天. 基于运动预测的髋关节外骨骼实时助力控制[J]. 机器人, 2021, 43(4): 473-483. DOI: 10.13973/j.cnki.robot.200557
引用本文: 徐铃辉, 杨巍, 杨灿军, 张继宇, 王天. 基于运动预测的髋关节外骨骼实时助力控制[J]. 机器人, 2021, 43(4): 473-483. DOI: 10.13973/j.cnki.robot.200557
XU Linghui, YANG Wei, YANG Canjun, ZHANG Jiyu, WANG Tian. Real-time Assistance Control of Hip Exoskeleton Based on Motion Prediction[J]. ROBOT, 2021, 43(4): 473-483. DOI: 10.13973/j.cnki.robot.200557
Citation: XU Linghui, YANG Wei, YANG Canjun, ZHANG Jiyu, WANG Tian. Real-time Assistance Control of Hip Exoskeleton Based on Motion Prediction[J]. ROBOT, 2021, 43(4): 473-483. DOI: 10.13973/j.cnki.robot.200557

基于运动预测的髋关节外骨骼实时助力控制

Real-time Assistance Control of Hip Exoskeleton Based on Motion Prediction

  • 摘要: 针对下肢肌力衰退群体日常出行需求,设计了可穿戴的髋关节外骨骼,实现对人体日常步行意图的精准感知,并对髋关节的屈曲/伸展动作提供实时助力.为了实现频繁走停条件下的助力时机准确性和规律步行条件下的助力无延时,提出了一种基于混合振荡器的运动预测模型,将步态数据从时域转化为相角域,实现人体步行步态的预测和步态周期的分割,通过相角在线计算助力矩,对髋关节外骨骼进行助力控制.为了消除大助力矩下产生的抖动,对大腿杆上的惯性测量单元进行了解耦布置设计.通过跑台步行实验和自由步行实验,分别验证了髋关节外骨骼对于瞬时速度变化、均匀速度变化的适应性,以及在走停切换、自由随意步行时的适应性和有效性.同时检测和对比人机交互力,验证了带预测能力的自适应振荡器模式能提供更好的助力体验.实验结果表明,基于混合振荡器模型的助力控制策略能够兼顾走停切换条件下非周期步态的助力和规律步行条件下的类周期无延时助力.

     

    Abstract: To satisfy the daily walking needs of the individuals with weak muscle strength in lower limbs, a wearable hip exoskeleton is designed to realize accurate perception of the human daily walking intentions and real-time assistance of hip flexion/extension. A motion prediction model based on hybrid oscillators is proposed to realize accurate assistance timing in the frequent stop-and-go condition and no-delay assistance for regular walking gait. Based on the motion prediction model, human walking gait prediction and gait cycle segmentation are realized by converting gait data from the time domain to the phase domain. The phase angle is used to calculate the assistance torque online, and thus the assistance control of hip exoskeleton is implemented. To eliminate the jitter caused by large assistance torque, the rigid connection between the inertial measurement unit and the hip exoskeleton thigh link is decoupled. Treadmill experiments and free walking experiments are conducted to verify the adaptability of the hip exoskeleton to sudden or uniform speed changes, and the effectiveness in stop-and-go switching or free walking conditions respectively. Meanwhile, the human-machine interaction force is detected and compared to verify that the adaptive oscillator mode with prediction ability can provide more compliant walking assistance. The experimental results show that the real-time assistance control based on the hybrid oscillators model can generate the assistance for non-periodic gaits in stop-and-go condition and no-delay assistance for quasi-periodic gait in regular walking condition.

     

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