被动动态步行与神经进化控制躯干

A. Mahmoudi, R. A. Moghadam, Hooman Misaghi, I. Rafati
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引用次数: 0

摘要

被动动态步行是最简单、最有效的两足运动形式。被动动态步行器的步态虽然简单,但与人类在斜坡上行走非常相似。这些机器人最重要的缺点是它们对初始条件的敏感性和它们可以稳定行走周期的斜坡范围有限。这项工作的目的是通过添加一个类似躯干的链接并使用神经进化算法控制它来缓解这些问题。为了实现这一目标,首先提取了控制该机器人的动力学方程。然后应用控制算法。使用这种控制策略的原因是模仿自然进化如何在强健的两足行走中发挥作用。据观察,这种策略改善了被动动态步行者的缺点,有趣的是,机器人在面对陡坡或零坡时表现出与人类相似的躯干运动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Passive Dynamic Walking with Neuroevolutionary Controlled Torso
Passive dynamic walking is the simplest and the most efficient form of biped locomotion. Albeit the simplicity, the walking gait of passive dynamic walkers resembles human walking in slops very well. The most important drawbacks of these robots is their sensitivity on initial conditions and the limited range of slopes they can have a stable walking cycle on. The aim of this work is to alleviate these problems by adding a link that resembles a torso and controlling it using a Neuroevolutionary algorithm. To achieve this goal, initially the dynamical equations governing this robot was extracted. Then the control algorithm is applied. The reason to use this control strategy is to mimic how natural evolution could play a role in robust biped walking. It was observed that this strategy improved both shortcomings associated with passive dynamic walkers and interestingly the robot shows torso movements familiar to that of humans when facing steep slopes or zero slope.
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