基于机器视觉的果园机器人导航路径自动识别

基于机器视觉的果园机器人导航路径自动识别(中文4900字,英文3900字)
摘要：提出了一种基于机器视觉的收获机器人果园导航路径生成算法。根据特征作为图像，水平投影，采用动态调整主干面积的方法。通过对树干区域的扫描，检测树木与土壤之间的过境点，并将这些点划分为两个区域。然后采用最小二乘拟合，提取两条边界线，通过这两条线得到了中心星团，这条直线被视为航行路线。 仿真结果表明，该算法能有效地提取复杂果园环境下的导航路径，识别正确率为91.7%。证明了该方法是稳定的。 结果表明，与人工识别角度相比，仿真导航角的偏差率约为2%。
关键词：导航路径;机器视觉;果园环境;图像分割;最小二乘拟合

Auto Recognition of Navigation Path for Harvest Robot Based on Machine Vision
Abstract：An algorithm of generating navigation path in orchard for harvesting robot based on machine vision was presented. According to the features of or-chard images, a horizontal projection method was adopted to dynamically rec-ognize the main trunks area. Border crossing points between the tree and the earth were detected by scanning the trunks areas, and these points were divided into two clusters on both sides. Resorting to least-square fitting, two border lines were extracted. The central clusters were gained by the two lines and this straight line was regarded as the navigation path.Matlab simulation result shows that the algorithm could effectively extract navigation path in complex orchard environment, and correct recognition rate was 91.7%. The method is proved to be stable and reliable, and with the deviation rate of simulation navigation angle compared with the artificial recognition angle is around 2%.

Keywords: Navigation path, Machine vision, Orchard environment, Image segmentation, Least square-fitting.