Non-contact detection of trench quality by UAV-LiDAR system

W. Xiao, Heqing Li, Deying Liu, Yi Zuo, Weiren Zhu, Yuning Yin
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Abstract

In order to promote the innovation of agricultural science and technology and the development of smart agriculture, a non-contact trench quality inspection system, UAV-LiDAR, is developed in this paper. The system uses the unmanned aerial vehicle (UAV) as the mobile flight platform, which can realize the non-contact trench quality data acquisition and automatic evaluation of the trench quality by carrying LiDAR, IMU, router and microcomputer. First of all, point cloud data sets of different areas of the whole farmland were acquired by UAV-LiDAR. Secondly. according to the normal deviation matching algorithm, appropriate frames were chosen to match the point cloud data of furrows in different regions, and the point clouds of each region were registered to the unified coordinate system to obtain the complete point cloud data of the whole farmland furrows. In the endusing the poisson surface reconstruction to realize the reconstruction surface of the complete furrow point cloudmeasuring the trench surface width, trench bottom width and trench depth of the furrow. The experimental results showed that the method proposed in this paper can effectively detect the working performance of the ditching machine. Compared with the manual measurement results, the identification time reduced by $15\sim 20$ minutes, and the detection efficiency and accuracy are improved by $50\%\sim 66.67\%$ and $22.96\% \sim 29.37\%$, respectively. It realizes the visual remote appraisal of the performance of the trench machine, and provides an intelligent appraisal means for the performance of agricultural machinery.
基于无人机-激光雷达系统的沟槽质量非接触检测
为了促进农业科技创新和智慧农业的发展,本文开发了一种非接触式沟槽质量检测系统——无人机-激光雷达。该系统以无人机(UAV)为移动飞行平台,通过携带激光雷达、IMU、路由器和微机,实现非接触式沟槽质量数据采集和沟槽质量自动评估。首先,利用无人机-激光雷达获取整个农田不同区域的点云数据集。其次。根据正态偏差匹配算法,选择合适的帧对不同区域的犁沟点云数据进行匹配,并将每个区域的点云配准到统一的坐标系中,得到整个农田犁沟的完整点云数据。最后利用泊松曲面重建实现全沟点云重建曲面,测量沟面宽度、沟底宽度和沟深。实验结果表明,本文提出的方法可以有效地检测开沟机的工作性能。与人工测量结果相比,识别时间缩短了15 ~ 20分钟,检测效率和准确率分别提高了50 ~ 50%、66.67%和22.96%。实现了对挖沟机性能的可视化远程评价,为农业机械性能的智能化评价提供了一种手段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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