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高钰清, 靳葳, 徐鉴, 方虹斌. 踝关节外骨骼人机耦合动力学与助力性能分析. 力学学报, 2022, 54(12): 3496-3512. DOI: 10.6052/0459-1879-22-472
引用本文: 高钰清, 靳葳, 徐鉴, 方虹斌. 踝关节外骨骼人机耦合动力学与助力性能分析. 力学学报, 2022, 54(12): 3496-3512. DOI: 10.6052/0459-1879-22-472
Gao Yuqing, Jin Wei, Xu Jian, Fang Hongbin. Human-machine coupling dynamics and assistance performance analysis of an ankle exoskeleton. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(12): 3496-3512. DOI: 10.6052/0459-1879-22-472
Citation: Gao Yuqing, Jin Wei, Xu Jian, Fang Hongbin. Human-machine coupling dynamics and assistance performance analysis of an ankle exoskeleton. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(12): 3496-3512. DOI: 10.6052/0459-1879-22-472

踝关节外骨骼人机耦合动力学与助力性能分析

HUMAN-MACHINE COUPLING DYNAMICS AND ASSISTANCE PERFORMANCE ANALYSIS OF AN ANKLE EXOSKELETON

  • 摘要: 踝关节在人体下肢运动过程中提供了最大的关节力矩, 因此在下肢增强型外骨骼的研究中, 踝关节外骨骼受到了重点关注. 穿戴外骨骼的人体的行走是典型的动力学问题, 但目前人机耦合动力学的相关研究还处于早期阶段. 本文以绳驱踝关节外骨骼为研究对象, 融合机器人正运动学方法和拉格朗日方程建立了考虑足−地交互力、人体关节力矩和外骨骼力矩的人−机耦合动力学模型. 模型中, 足−地交互力由Kelvin-Voigt模型结合库伦摩擦模型描述, 人体关节力矩由基于粒子群优化的PD控制生成, 外骨骼期望力矩由上层控制器依据人体步态周期确定. 通过基于模型的动力学仿真, 本文从人体踝关节角度、踝关节力矩、踝关节功率和踝关节做功多个角度系统分析了踝关节外骨骼对人体行走的助力效果. 研究表明, 在2.0 km/h到6.5 km/h的人体步行速度下, 穿戴外骨骼可以实现至少24.84%的人体踝关节平均力矩下降和至少24.69%的踝关节做功下降. 本文也开展了基于SCONE平台的肌肉骨骼建模和预测仿真. 仿真结果表明, 在3.6 km/h的步行速度下, 穿戴外骨骼可以有效降低比目鱼肌的激活度峰值, 并使肌电信号的RMS值下降了6.21%, 从而从生理学的角度证实了踝关节外骨骼的助力效果. 本文的结果进一步完善了人体下肢−外骨骼耦合系统的动力学建模和分析方法, 从动力学和生理学角度证实和解释了踝关节外骨骼对行走的助力机制, 也为今后下肢外骨骼的实验研究提供了理论支撑.

     

    Abstract: The ankle joint provides the largest joint torque during human lower limb motions. Therefore, ankle exoskeletons have received major attention in the research of lower limb augmented exoskeletons. Walking of a human equipped with an exoskeleton is a typical dynamics problem, while the research on human-exoskeleton coupling dynamics is still at an early stage. Concentrated on the cable-driven ankle exoskeleton, this paper developed a human-machine coupled dynamic model considering foot-ground interaction forces, human joint torques, and exoskeleton torques, by integrating the robot forward kinematics method and the Lagrange's equation, where the foot-ground interaction force was described by the Kelvin-Voigt model together with the Coulomb’s dry friction model, the human joint torque was generated by the PD control with the particle swarm optimization, and the assistive exoskeleton torque was determined by an upper-level controller in accordance with the human gait cycle. Through model-based dynamic simulations, this paper systematically analyzed the effect of the ankle exoskeleton assistance on human walking from the perspectives of the angle, torque, power, and work of the human ankle. It was demonstrated that when walking at a speed between 2.0 km/h and 6.5 km/h, human wearing the exoskeleton can achieve at least a 24.84% reduction in average ankle torque and at least a 24.69% reduction in ankle work. Musculoskeletal modeling and predictive simulations based on the SCONE were also performed in this paper. The simulation results showed that at a speed of 3.6km/h, wearing the exoskeleton can effectively reduce the peak level of soleus activation and the RMS value of the EMG signal by 6.21%, thereby validating the effect of the ankle exoskeleton assistance from a physiological perspective. Based on the results of this paper, the dynamic modeling and analysis method of human-exoskeleton coupled systems is further improved. The assistance mechanism of the ankle exoskeleton for walking is confirmed and interpreted from the perspectives of dynamics and physiology. This research also provides a theoretical basis for future experimental studies of lower-limb exoskeletons.

     

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