基于图象视觉导航的AGVS与传统的、在地下埋设电磁感应电缆引导的AGVS相比,前者能更好地适应现代柔性生产的要求.该文研究了图象识别白线路标的边缘检测算法,并采用了最大方差法来设定路标图象的灰度阈值,可得到较准确的图象边缘.针对所研究的AGVS特点,提出了机器视觉的图象变形校正算法,以获得正确的路标图象信息.在此基础上,用改进的数字图象模板匹配法识别数字,再用数字标识符区分柔性生产线中的分支路径,来引导AGVS在正确的分支路径上行进.实验表明,该方法具有良好的实用效果.

A vision-based auto-guided vehicle system (AGVS) is introduced in the paper. Compares to the traditional cable guided vehicle, vision-based vehicle can adapt better to modern FMS (Flexible Manufacturing System). A white line marker-detecting algorithm, in which the maximum square error method is used to calculate the white line marker gray level threshold, is introduced in the paper. The vision system of the AGVS used in the paper gives deformation in the white line image, so it needs to rectify the white line image deformation before we get correct information about the white line from the image. An algorithm is proposed for this purpose. On the crossroad, the line is numbered to differentiate the different roads. Image templates matching method is used to recognize the different numbers, which represent the different roads at the crossroad. Then AGVS can use the road numbers to decide which road the car should go along.