自动导引车视觉导引路径的识别及精确测量

为了提高基于单目视觉导引的双向型自动导引车的视觉测量精度,首先通过导引车运动状态下的自标定降低系统误差,并通过彩色图像处理提取导引路径中心线;再根据测量目标精度,提出一种基于曲率角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前两种模型参数进行回归,采用基于曲率角估计的自适应加权拟合法对非圆弧拐弯模型参数进行回归.实验结果表明,文中方法的测量精度高,达到了目标要求.

Recognition and Accurate Measurement of Vision-Guided Path of Automatic Guided Vehicle

In order to improve the measurement accuracy of a monocular vision-based bidirectional automatic guided vehicle,a motion-based self-calibration method is used to reduce the system error,and a color image processing is performed to extract the centerline of the guided path.Then,a classification method of path models based on curvature estimation is proposed to meet the requirements of target accuracy.The path models are classified into three types,namely the straight line,the arc turning and the non-circular turning.Finally,the minimum mean-variance method is used for the parameter regression of the first two models,and the curvature estimation-based adaptive weighted fitting method is used for the parameter regression of the third model.Experimental results show that the proposed method is of high measurement accuracy and meets the requirement of vision navigation well.