Parameter Synthesis of Coupled Nonlinear Oscillators for CPG-Based Robotic Locomotion
Parameter Synthesis of Coupled Nonlinear Oscillators for CPG-Based Robotic Locomotion
复制标题
基于 CPG 的机器人运动耦合非线性振荡器的参数综合
DOI：
10.1109/tie.2014.2308150
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发表时间：
2014-11-01
影响因子：
7.7
通讯作者：
Wang, Tianmiao
中科院分区：
文献类型：
--
作者：
Hu, Yonghui;Liang, Jianhong;Wang, Tianmiao
本文提出了一种数值方法的参数综合的中央模式发生器（CPG）网络，以获得所需的运动模式。CPG网络被建模为一个链的单向或双向耦合的霍普夫振荡器与一种新的耦合方案，消除了传入信号的影响上的振荡器的振幅。该方法将相关的CPG参数转换成动态系统，该动态系统作为CPG网络动态的一部分而演化。利用所提出的学习规则，CPG网络可以对示教信号的频率、幅度和相位关系进行编码。仿真结果证明了该方法学习指令运动模式的能力。应用所提出的方法在线步态综合的机器鱼。
This paper presents a numerical method for parameter synthesis of a central pattern generator (CPG) network to acquire desired locomotor patterns. The CPG network is modeled as a chain of unidirectionally or bidirectionally coupled Hopf oscillators with a novel coupling scheme that eliminates the influence of afferent signals on amplitude of the oscillator. The method converts the related CPG parameters into dynamic systems that evolve as part of the CPG network dynamics. The frequency, amplitude, and phase relations of teaching signals can be encoded by the CPG network with the proposed learning rules. The ability of the method to learn instructed locomotor pattern is proven with simulations. Application of the proposed method to online gait synthesis of a robotic fish is also presented.