基于动态阈值的AGV路径识别算法

针对基于视觉引导自动引导车(AGV)系统的引导路径识别技术,易受光照强度,路面反光,阴影等因素的影响的问题.采用了一种基于路径预判的图像动态阈值获取方法.它通过已识别的路径点,利用线性插值所得函数预估当前路径点所在图像区域,在此区域内找出最优阈值,依据阈值对当前区域内图像进行二值化,找出当前区域的引导线,依据引导线本身特征来判断此阈值是否有效,以获取到适应当前环境下的阈值,并根据此阈值提取出引导线.通过此种方法对路径信息进行采集、识别、处理,从而使AGV能在跑道上较快较稳的前行.

AGV path identification algorithm based on dynamic threshold

Aiming at the guidance path recognition technology based on vision guided automatic guided vehicle (AGV) system,it is vulnerable to the influence of light intensity,pavement reflection,shadow and other factors.To solve this problem,a method of image dynamic threshold acquisition based on path prediction is proposed.By identifying the path point,using linear interpolation income function estimates the current path point image region.Within this area find the optimal threshold.According to the thresholds of the image binarization,find out the current region of the guide line,according to the guide line of its own characteristics to determine the threshold is valid.To get to adapt to the current environment of threshold,and according to this threshold to extract the guide wire.Through this method,the path information is collected,identified and processed,so that the AGV can be faster and more stable on the runway.