期刊
INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS
卷 30, 期 4, 页码 441-458出版社
JOHN WILEY & SONS LTD
DOI: 10.1002/cta.186
关键词
cellular neural network; central pattern generator; artificial locomotion; bio-inspired robotics; non-linear circuits
Biologically inspired control of artificial locomotion often makes use of the concept of central pattern generator (CPG), a network of neurons establishing the locomotion pattern within a lattice of neural activity. In this paper a new approach, based on cellular neural networks (CNNs), for the design of CPGs is presented. From a biological point of view this new approach includes an approximated chemical synapse realized and implemented in a CNN structure. This allows to extend the results, previously obtained with a reaction-diffusion-CNN (RD-CNN) for the locomotion control of a hexapod robot, to a more general class of artificial CPGs in which the desired locomotion pattern and the switching among patterns are realized by means of a spatio-temporal algorithm implemented in the same CNN structure. Copyright (C) 2002 John Wiley Sons, Ltd.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据