Road following by artificial vision using neural network

M Mazo, F.J Rodriguez, E Santiso, M.A Sotelo
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引用次数: 4

Abstract

It has been developed, built and tested an artificial vision based system to follow roads, which provides control signals, in a short time, by means of a joint of artificial neural nets. The image is segmented in “road” or “not road.” The obtained segmentation is the input for two neural nets, a classic architecture net (NN), and a TDNN (Time Delay Neural Network) one. The outputs provided by both nets, with a trajectory estimation, are introduced to a decision-making block, which selects the alternative containing less error. The classifier parameters are updated according to the current segmentation.

基于神经网络的人工视觉道路跟踪
它已经开发、建造并测试了一个基于人工视觉的道路跟踪系统,该系统通过人工神经网络的联合在短时间内提供控制信号。图像被分割为“道路”或“非道路”。得到的分割是两个神经网络的输入,一个是经典结构网络(NN),另一个是时延神经网络(TDNN)。将两种网络提供的输出带轨迹估计引入决策块,决策块选择误差较小的备选方案。分类器参数根据当前分割更新。
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