CNN based central pattern generators with sensory feedback

Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications Pub Date : 2002-07-22 DOI:10.1109/CNNA.2002.1035061

P. Arena, L. Fortuna, M. Frasca, L. Patané

引用次数: 11

Abstract

In this paper the topic of including feedback from sensors in the central pattern generator (CPG) for a hexapod robot realized through cellular neural networks (CNNs) is addressed. An approach based on local bifurcation of the CNN cells constituting the sub-units of the CPG network is introduced, allowing control of the direction of the robot. Suitable control can be realized by changing the value of the bias of the CNN cells. Moreover, inspired by the idea of Braitenberg creatures, purely reactive control of the hexapod direction is illustrated with an example of a robot able to avoid obstacles.

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带有感官反馈的基于CNN的中枢模式生成器

本文讨论了利用细胞神经网络(cnn)实现的六足机器人的中央模式发生器(CPG)中传感器反馈的问题。介绍了一种基于构成CPG网络子单元的CNN单元的局部分叉的方法，允许控制机器人的方向。通过改变CNN单元的偏置值可以实现适当的控制。此外，受布莱滕贝格生物概念的启发，用一个能够避开障碍物的机器人的例子来说明六足体方向的纯反应控制。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications

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