基于激光雷达的作物收获导航线实时提取方法研究
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国家重点研发计划项目(2021YFD2000601)


Real-time Extraction of Navigation Line Based on LiDAR
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    摘要:

    为提高联合收获机无人驾驶导航路径的精度,本文提出一种基于激光雷达的作物收获导航线实时提取方法。搭建点云数据采集系统,利用平面拟合法确定激光雷达安装高度和安装角度。利用三维激光雷达扫描收获机前方作物的点云数据,结合IMU惯性传感器反馈的姿态信息,实现作物点云数据从激光雷达坐标系到车体坐标系的变换。基于激光雷达扫描视场角、安装高度和安装角度获取感兴趣区域(ROI)的坐标,并对感兴趣区域进行直通滤波和统计滤波,去除灰尘、秸秆粉末等噪声的影响,以实现点云数据无效点和离群点的剔除。提出一种基于栅格八邻域高程差的作物收获导航线快速识别算法,以点云栅格化后在Z轴方向上的坐标值作为检测依据,定义某一栅格与其8个相邻栅格在Z轴坐标上的差值为高程差,遍历栅格并根据设定阈值进行比较判断,实现收获边界点的有效提取。采用最小二乘算法进行收获边界点的拟合,实现田间作业过程中作物收获导航线动态提取。田间试验表明,该方法具有较好的鲁棒性,能在作物稀缺、杂草较多等情况下保持较高的准确性,其中前进方向偏差角平均值为0.872°,割台横向偏差为0.104m,收获导航线准确率为93.5%,可为联合收获机工作提供辅助导航,提高无人驾驶的准确率。

    Abstract:

    In order to improve the precision of unmanned navigation path of combine harvester, a real-time extraction method of crop harvesting navigation line was proposed based on LiDAR. A point cloud data acquisition system was built, and the installation height and angle of LiDAR were obtained by plane fitting method. The transformation of point cloud data from LiDAR coordinate system to vehicle coordinate system was realized by using three-dimensional LiDAR to scan the crop point cloud data in front of the harvester and combining the attitude information fed back by IMU inertial sensor. The coordinates of the ROI were obtained based on the scanning field angle, installation height and installation angle of LiDAR, and the ROI was filtered through and statistically to remove impurities such as dust and straw powder, so as to eliminate invalid points and outliers in point cloud data. A fast recognition algorithm of navigation line based on the elevation difference of eight neighboring grids was proposed. The coordinate value in the Z-axis direction after the point cloud rasterized was taken as the detection basis, and the difference between grid and its eight neighboring grids in the Z-axis coordinate was defined as the elevation difference. The grid was traversed and compared according to the set threshold, so as to effectively extract the harvesting boundary points. The least square algorithm was used to fit the harvesting boundary points, and the harvesting navigation line was obtained. Experiments showed that the algorithm had good robustness, and can maintain high accuracy when crops were scarce and there were many weeds, among which the average error angle of forward direction was 0.872°, the lateral deviation of header was 0.104m, and the correct rate of harvesting navigation line was 93.5%, which can provide auxiliary navigation for combine harvester and improve the accuracy of unmanned driving.

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周海燕,杨悦,刘阳春,马若飞,张峰硕,张启帆.基于激光雷达的作物收获导航线实时提取方法研究[J].农业机械学报,2023,54(s1):9-17. ZHOU Haiyan, YANG Yue, LIU Yangchun, MA Ruofei, ZHANG Fengshuo, ZHANG Qifan. Real-time Extraction of Navigation Line Based on LiDAR[J]. Transactions of the Chinese Society for Agricultural Machinery,2023,54(s1):9-17.

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  • 收稿日期:2023-06-20
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  • 在线发布日期: 2023-12-10
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