双向型单目视觉自动导引车路径识别及测量

Path identification and measurement of bi-directional AGV based on monocular vision

为了提高双向型自动导引车的视觉导引精度,通过处理彩色图像提取导引路径中心线;根据测量目标对自动导引车的导引精度,提出一种基于平均斜率差及拐点分辨指数估计的路径模型分类方法,将路径分为直线、圆弧拐弯和非圆弧拐弯3种模型,并采用最小均方差法对直线模型参数进行回归,用Levenberg-Marquardt法对圆弧模型进行拟合,根据拐点位置将非圆弧拐弯进行分段拟合。实验结果表明,该方法对基于单目视觉的路径识别有很好的效果,同时测量精度也达到目标要求。

In order to improve visual navigation accuracy of bi-directional automatic guided vehicles, it extracts the cen-terline of guide path by processing color images. According to measurement accuracy between the target and automated guided vehicles, a method of path model classification based on the average slope difference and cornerity distinguish index estimation is proposed, which divides path into lines, arcs and non-circular turning three kinds of models, and it uses MMSE method for parametric regression to linear model, uses the Levenberg-Marquardt method to fit the arc model, according to the position of cornerity point, it divides non-circular turning model into sections and fits these sections respectively. Experimental results show that this method not only has a good performance on path identification which is based on monocular vision, but also achieves the measurement accuracy requirements of target.