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Fast and accurate mobile robot control using a cerebellar model in a sensory delayed environment

机译:在感觉延迟环境中使用小脑模型快速准确的移动机器人控制

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Fast and accurate control of a system exhibiting significant feedback delay is traditionally a difficult problem to solve. In biological systems, it is thought that a part of the brain called the cerebellum overcomes such difficulties. This paper outlines the use of a cerebellar model in the control of a mobile robot. The model is based around Albus's CMAC neural network (1971, 1975), and uses the response of a nondelayed teaching module as a basis for learning. The model was able to produce results comparable to the teacher despite being subjected to severe sensory latency.
机译:快速准确地控制表现出显着反馈延迟的系统是传统上解决的难题。在生物系统中,据认为,叫细胞的大脑的一部分克服了这样的困难。本文概述了在移动机器人控制中使用小脑模型。该模型基于Albus的CMAC神经网络(1971,1975),并使用Nondelay教学模块的响应作为学习的基础。尽管受到严重的感官潜伏期,但该模型能够产生与老师相当的结果。

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