融合激光三维探测与IMU姿态角实时矫正的喷雾靶标检测
发布时间：2018-08-12 09:58
【摘要】：基于高精度激光传感器的喷雾靶标特征检测是精准施药变量决策的重要依据。为了改善复杂地形条件对车载激光靶标检测的影响,进行了车载激光喷雾靶标检测与矫正研究。该文基于惯性测量单元(inertial measurement unit,IMU)与UTM-30LX型激光传感器搭建靶标检测试验车,IMU实时获取车体姿态角的偏航角、俯仰角及侧倾角信息,车载激光传感器实时获取目标切面轮廓的极坐标数据。将获取的目标切面轮廓的极坐标数据与试验车姿态角信息相匹配,通过矫正算法获取精确的目标外形尺寸信息并重构目标三维图像。试验设计首先对长方体柜子与仿真树进行车体单一动态俯仰角的检测试验,然后以仿真树为试验目标,进行车体存在复合动态俯仰角与侧倾角的检测试验,最后在未知地形条件下对长方体柜子以及仿真树进行动态姿态角检测与矫正试验。利用MATLAB软件对数据矫正分析,对矫正后的目标尺寸信息进行误差分析并重构目标三维图像。试验结果显示矫正后长方体柜子的高度、宽度最大相对误差分别为8.89%和8.00%,仿真树的高度、宽度以及树冠高度最大相对误差分别为5.63%、10.00%和5.00%,矫正效果良好,验证了矫正算法的有效性。
[Abstract]:The feature detection of spray target based on high precision laser sensor is an important basis for variable decision of precision application. In order to improve the influence of complex terrain conditions on vehicle laser target detection, vehicle laser spray target detection and correction were studied. Based on the inertial measurement unit (inertial measurement) and the UTM-30LX laser sensor, the information of yaw angle, pitch angle and sideslip angle of the body attitude angle are obtained in real time. The vehicle laser sensor can obtain the polar coordinate data of the target profile in real time. The polar coordinate data of the target profile are matched with the attitude angle information of the vehicle, and the accurate shape dimension information of the target is obtained by the correction algorithm and the 3D image of the target is reconstructed. The test design firstly tests the single dynamic pitching angle of the car body on the cuboid cabinet and the simulation tree, and then takes the simulation tree as the test object to test the existence of compound dynamic pitch angle and roll angle of the car body. Finally, the dynamic attitude angle detection and correction experiments are carried out on cuboid cabinets and simulation trees under unknown terrain conditions. The data correction is analyzed by using MATLAB software, and the error of the corrected target size information is analyzed and the 3D image of the target is reconstructed. The test results show that the maximum relative errors of the height and width of the cuboid cabinet after correction are 8.89% and 8.00, respectively. The maximum relative errors of the height, width and crown height of the simulation tree are 5.6310.00% and 5.00%, respectively. The validity of the correction algorithm is verified.
【作者单位】： 江苏大学电气信息工程学院;
【基金】：国家自然科学基金项目(51505195) 江苏高校优势学科(PAPD)
【分类号】：S49;TP212
，
本文编号：2178710
[Abstract]:The feature detection of spray target based on high precision laser sensor is an important basis for variable decision of precision application. In order to improve the influence of complex terrain conditions on vehicle laser target detection, vehicle laser spray target detection and correction were studied. Based on the inertial measurement unit (inertial measurement) and the UTM-30LX laser sensor, the information of yaw angle, pitch angle and sideslip angle of the body attitude angle are obtained in real time. The vehicle laser sensor can obtain the polar coordinate data of the target profile in real time. The polar coordinate data of the target profile are matched with the attitude angle information of the vehicle, and the accurate shape dimension information of the target is obtained by the correction algorithm and the 3D image of the target is reconstructed. The test design firstly tests the single dynamic pitching angle of the car body on the cuboid cabinet and the simulation tree, and then takes the simulation tree as the test object to test the existence of compound dynamic pitch angle and roll angle of the car body. Finally, the dynamic attitude angle detection and correction experiments are carried out on cuboid cabinets and simulation trees under unknown terrain conditions. The data correction is analyzed by using MATLAB software, and the error of the corrected target size information is analyzed and the 3D image of the target is reconstructed. The test results show that the maximum relative errors of the height and width of the cuboid cabinet after correction are 8.89% and 8.00, respectively. The maximum relative errors of the height, width and crown height of the simulation tree are 5.6310.00% and 5.00%, respectively. The validity of the correction algorithm is verified.
【作者单位】： 江苏大学电气信息工程学院;
【基金】：国家自然科学基金项目(51505195) 江苏高校优势学科(PAPD)
【分类号】：S49;TP212
，
本文编号：2178710
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