Learning fish-like swimming with A CPG-based locomotion controller
Learning fish-like swimming with A CPG-based locomotion controller
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DOI：
10.1109/iros.2011.6094785
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发表时间：
2011-12
期刊：
影响因子：
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通讯作者：
Yonghui Hu;Weicheng Tian;Jianhong Liang;Tianmiao Wang
中科院分区：
文献类型：
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作者：
Yonghui Hu;Weicheng Tian;Jianhong Liang;Tianmiao Wang
本文提出了一种基于CPG的运动控制器的学习方法来获得鱼类喜欢的游泳。所提出的方法将相关的CPG参数转换为动态系统，作为CPG网络动态的一部分。根据鲤鱼游动的运动学模型，用轨迹逼近法求出了教学信号。提出了一种新的CPG网络耦合方案，将CPG网络建模为耦合的Hopf振子链，以消除传入信号对振子幅度的影响。利用振子的相空间表示，建立了固有频率、耦合权重和振幅的学习规则。通过自适应机制，CPG网络可以对示教信号的频率、幅度和相位关系进行编码。数值实验验证了所提出的学习规则的有效性。
This paper presents a learning method to acquire fish-liking swimming with a CPG-based locomotor controller. The proposed method converts the related CPG parameters into dynamical systems that evolve as part of the CPG network dynamics. The teaching signals are derived from the kinematic model of carangiform swimming with trajectory approximation method. A novel coupling scheme for the CPG network, which are modeled as a chain of coupled Hopf oscillators is proposed to eliminate the influence of afferent signals on amplitude of the oscillator. The learning rules of intrinsic frequency, coupling weight and amplitude are formulated with phase space representation of the oscillators. The frequency, amplitudes and phase relations of the teaching signals can be encoded by the CPG network with the adaptation mechanisms. Numerical experiments are carried out to validate the effectiveness of the proposed learning rules.