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Auto Recognition of Navigation Path for Harvest Robot Based on Machine Vision

机译:基于机器视觉的收获机器人导航路径自动识别

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An algorithm of generating navigation path in orchard for harvesting robot based on machine vision was presented. According to the features of orchard images, a horizontal projection method was adopted to dynamically recognize 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%.
机译:提出了一种基于机器视觉的收获机器人的果园中生成导航路径的算法。根据果园图像的特征,采用水平投影方法动态识别主树干区域。通过扫描树干区域检测树和地球之间的边界交叉点,并且这些点在两侧分为两个簇。诉诸最小二乘配件,提取了两个边界线。通过两条线获得中央簇,并且这种直线被视为导航路径.Matlab仿真结果表明,该算法可以有效地提取复杂果园环境中的导航路径,并且正确的识别率为91.7%。该方法被证明是稳定可靠的,与人工识别角相比的仿真导航角的偏差率约为2%。

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