复杂环境下自动导引车路径识别算法

Guidance Line Identification Algorithm for AGV in Complex Environment

摘要:

为了快速准确提取复杂环境下的自动导引车(AGV)引导路标参数，提出一种基于先验知识的直线识别算法。根据视野和引导线结构特征将全图划分为若干子区域，确定子区域自适应阈值，利用前帧图像中的直线参数信息选择行列扫描方式，剔除干扰点并获得中线点集，然后采用带搜索角度限制和分区域非均匀采样的改进Hough变换得到直线参数，最后用交比定理对参数加以校正。试验表明本算法能在不同光照、反光、阴影下对路径进行有效识别，具有较好鲁棒性，处理分辨率为576×768的图像，每帧平均用时不超过90 ms，满足运行需要。

Abstract:

In order to quickly and accurately identify the guidance line in complex environment, a line recognition algorithm based on prior knowledge was proposed. Images were divided into several regions by field range and line characteristic. Both means of full image and region were used to make adaptive threshold of each region. Scanning mode was decided by information of previous image, then noises were filtered and intermediate points were acquired. An improved Hough transformation with search angle limitation and nonuniform sampling was applied to localize guidance line. Finally cross ratio theorem was used to calibrate the parameters. The experimental result showed the method was characterized by robustness and real-time, the average computing time was about 90ms for each image.