Evolving composite robot behaviour - a modular architecture

Tobias Larsen, S. Hansen
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引用次数: 20

Abstract

We have developed a composite control system for solving complex tasks with autonomous robots. The control system is evolved using artificial evolution and can be regarded as a modular decision tree where every node is a neural network. We show that the control system is robust to noise, is reactive, is extendable and can be set up to be configured automatically. Furthermore we show that robots in the real world work using this control system.
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进化复合机器人行为——模块化架构
我们开发了一种复合控制系统,用于解决自主机器人的复杂任务。控制系统采用人工进化的方法进行进化,可以看作是一个模块化的决策树,每个节点都是一个神经网络。结果表明,该控制系统对噪声具有鲁棒性、无功性、可扩展性和可自动设置组态。此外,我们还展示了现实世界中的机器人使用该控制系统工作。
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