通过分析参数影响，预测双足系统前向稳定所需最小步频。
Estimation of Minimum Stride Frequency for the Frontal Plane Stability of Bipedal Systems
- 基于腿长、质量、刚度等参数建模，预测最小稳定步频。
- 预测值与随机模型实测值匹配良好，验证方法有效性。
- 适合机器人步态设计与低能耗控制研究者参考。
双足系统在前向平面的稳定性受髋部偏移影响显著，通过前馈式收展腿部可实现无需反馈控制的稳定振荡。这种前馈稳定机制能降低控制难度与能耗，提升运动鲁棒性。然而，质量、刚度、腿长、髋宽等关键参数如何影响稳定性及维持稳定的最小步频仍缺乏深入理解。本研究通过分析各参数及系统固有频率对最小步频的影响，提出一种预测方法，并对随机生成的模型进行预测值与实际值对比。结果深化了对前向平面稳定机制的认识，证实前馈稳定可有效减少控制开销。
原文摘要 · Abstract (English)
Stability of bipedal systems in frontal plane is affected by the hip offset, to the extent that adjusting stride time using feedforward retraction and extension of the legs can lead to stable oscillations without feedback control. This feedforward stabilization can be leveraged to reduce the control effort and energy expenditure and increase the locomotion robustness. However, there is limited understanding of how key parameters, such as mass, stiffness, leg length, and hip width, affect stability and the minimum stride frequency needed to maintain it. This study aims to address these gaps through analyzing how individual model parameters and the system's natural frequency influence the minimum stride frequency required to maintain a stable cycle. We propose a method to predict the minimum stride frequency, and compare the predicted stride frequencies with actual values for randomly generated models. The findings of this work provide a better understanding of the frontal plane stability mechanisms and how feedforward stabilization can be leveraged to reduce the control effort.
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