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首页> 外文期刊>Biological Cybernetics >Analysis of the gait generation principle by a simulated quadruped model with a CPG incorporating vestibular modulation
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Analysis of the gait generation principle by a simulated quadruped model with a CPG incorporating vestibular modulation

机译:通过带有前庭调制的CPG的模拟四足动物模型分析步态产生原理

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摘要

This study aims to understand the principles of gait generation in a quadrupedal model. It is difficult to determine the essence of gait generation simply by observation of the movement of complicated animals composed of brains, nerves, muscles, etc. Therefore, we build a planar quadruped model with simplified nervous system and mechanisms, in order to observe its gaits under simulation. The model is equipped with a mathematical central pattern generator (CPG), consisting of four coupled neural oscillators, basically producing a trot pattern. The model also contains sensory feedback to the CPG, measuring the body tilt (vestibular modulation). This spontaneously gives rise to an unprogrammed lateral walk at low speeds, a transverse gallop while running, in addition to trotting at a medium speed. This is because the body oscillation exhibits a double peak per leg frequency at low speeds, no peak (little oscillation) at medium speeds, and a single peak while running. The body oscillation autonomously adjusts the phase differences between the neural oscillators via the feedback. We assume that the oscillations of the four legs produced by the CPG and the body oscillation varying according to the current speed are synchronized along with the varied phase differences to keep balance during locomotion through postural adaptation via the vestibular modulation, resulting in each gait. We succeeded in determining a single simple principle that accounts for gait transition from walking to trotting to galloping, even without brain control, complicated leg mechanisms, or a flexible trunk.
机译:本研究旨在了解四足动物模型中步态产生的原理。仅通过观察由大脑,神经,肌肉等组成的复杂动物的运动很难确定步态生成的本质。因此,我们建立了一个简化的神经系统和机制的平面四足动物模型,以观察其步态在模拟之下。该模型配备了数学中央模式生成器(CPG),该模式由四个耦合的神经振荡器组成,基本上会产生小跑模式。该模型还包含对CPG的感觉反馈,可测量身体倾斜度(前庭调制)。这会自发地导致低速下的未编程横向行走,跑步时的横向疾驰以及中速小跑。这是因为,在低速下,身体振动在每条腿的频率上显示出一个双峰值,在中速下没有峰(小的振荡),而在跑步时显示出一个单峰。身体振荡通过反馈自动调整神经振荡器之间的相位差。我们假设CPG产生的四条腿的振动和根据当前速度变化的身体振动与变化的相位差同步,以在运动过程中通过前庭调制通过姿势适应保持平衡,从而实现每次步态。我们成功地确定了一个简单的原理,即使没有大脑控制,复杂的腿部机制或灵活的躯干,也能说明步态从步行到小跑再到疾驰。

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