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Control of the hopping height in a biologically inspired robot leg.

机译:受到生物启发的机器人腿中跳跃高度的控制。

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摘要

Artificial legged locomotion may one day be superior to wheeled or tracked vehicles, especially for very rough terrain. Applications include unmanned ocean floor, planet, and volcano explorations. Also, the development of artificial legged locomotion may help in further understanding the control structure of animal locomotor systems. It has been shown that the rhythmic motions in animals are generated and controlled by networks of coupled nonlinear neuronal oscillators. This thesis was inspired by these observations.;During the past few years researchers have considered various locomotory control models with marginal success, warranting the need for more research at the most basic levels. As an initial step in the analysis of a quadruped robot, a simple biologically-inspired leg model with two degrees of freedom was considered. Poincare return maps were used to analyze three schemes for hopping height control: reflex control which involves energy pumping of the ankle joint, periodic forcing of the joint, and an adaptive periodic forcing scheme. Analytical approximations to the maps based on perturbation methods were derived. For all three approaches, explicit formulas for the hopping height and conditions for stability were obtained. In terms of stability, hopping height, and bandwidth requirements, the adaptive periodic forcing approach was shown to combine the best features of the other two approaches. A novel, experimental robot leg was designed and constructed, and experimental data supporting the analysis was obtained. Finally, a control scheme to potentially extend these results to forward hopping, and eventually to four legged robotic locomotion, was considered.;Both experimental and theoretical results demonstrated the advantages of incorporating an oscillator in the system to control the hopping height of a legged robot. In addition, the results obtained showed the usefulness of Poincare return map analysis, together with perturbation methods, of hopping gaits.
机译:有一天,人工腿式运动可能会优于轮式或履带式车辆,尤其是在非常崎terrain的地形上。应用包括无人海底,行星和火山勘探。同样,人工腿运动的发展可能有助于进一步了解动物运动系统的控制结构。已经表明,动物的节律运动是由耦合的非线性神经元振荡器的网络产生和控制的。这些观点启发了本论文。在过去的几年中,研究人员已经考虑了各种运动控制模型,但都取得了微弱的成功,因此有必要在最基本的水平上进行更多的研究。作为四足机器人分析的第一步,我们考虑了一个具有两个自由度的简单的受生物启发的腿部模型。 Poincare返回图用于分析跳跃高度控制的三种方案:反射控制,其中涉及踝关节的能量泵送,关节的周期性施力和自适应的周期性施力方案。推导了基于扰动方法的地图解析近似值。对于这三种方法,都获得了有关跳跃高度和稳定性条件的明确公式。在稳定性,跳变高度和带宽要求方面,自适应周期性强制方法显示出结合了其他两种方法的最佳功能。设计并构造了一种新型的实验机器人腿,并获得了支持该分析的实验数据。最后,考虑了一种将这些结果潜在地扩展到向前跳跃并最终扩展到四足机器人运动的控制方案。实验和理论结果都证明了在系统中集成一个振荡器来控制有腿机器人跳跃高度的优势。 。此外,获得的结果表明,庞加莱返回图分析以及微动方法对于跳跃步态很有用。

著录项

  • 作者

    Desai, Kamal V.;

  • 作者单位

    Boston University.;

  • 授予单位 Boston University.;
  • 学科 Engineering Electronics and Electrical.;Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 1999
  • 页码 127 p.
  • 总页数 127
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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