下肢外骨骼机器人交互力激励估计与稳定性分析

Interaction Force Excitation Estimation and Stability Analysis on Lower-limb Exoskeleton Robot

  • 摘要: 为解决下肢外骨骼助行稳定性判据忽略人机交互需求的问题,提出了一种考虑人机交互力的助行稳定性判别和助行速度优化方法。首先,建立并分析了人行走和人-机协同行走的倒立摆模型,并融合质心加速度和足底压力信息来间接表达难以测量的人机交互力,进而给出了CoM-CoP-CoA(质心-足压中心-加速度合成点)数学表达式,探究了人机交互力对外骨骼助行稳定性的影响。其次,在上述数学表达式的基础上,采用区域比较法,提出了基于矩阵不等式的外骨骼助行稳定性判据。再次,为探究助行速度与稳定裕度的关联关系,通过改进的稳定裕度描述法,提出了一种稳定裕度评价函数,用以优化外骨骼的助行速度。最后,开展了3种助行速度下的人机协同行走对比实验,分析了实验结果,并优化了人机协同行走时的速度。实验结果表明,所提出的稳定性判据和评价函数能够实现对外骨骼助行稳定性的判别及助行速度的优化。

     

    Abstract: An assisted-walking stability identification and speed optimization method considering the human-robot interaction force is proposed, aiming to address the issue of neglecting of human-robot interaction requirements in the lower-limb exoskeleton walking stability criterion. Firstly, the inverted pendulum models for human walking and human-robot cooperative walking are established and analyzed, and the human-robot interaction force which is difficult to measure is indirectly expressed by integrating the centroid acceleration and plantar pressure information, and further the mathematical expression of CoM-CoP-CoA (center of mass-center of pressure-composition of acceleration) is given. Here the influence of human-robot interaction on the stability of exoskeleton walking is explored. Secondly, an exoskeleton walking stability criterion based on matrix inequality is proposed by using the above mathematical expression and the regional comparison method. Furthermore, a stability margin evaluation function is proposed by the improved stability margin description, in order to examine the relationship between the walking speed and the stability margin, and to optimize the walking speed of exoskeleton. Finally, comparative experiments of human-robot cooperative walking at three walking speeds are conducted, the experimental results are analyzed, and the optimal walking speed of human-robot cooperative walking is given. Experimental results demonstrate that the proposed stability criterion and evaluation function can effectively discriminate the stability of exoskeleton walking and optimize the walking speed.

     

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