3D LiDAR sensing method and experiment of plant row information extraction

ZHAO Runmao; ZHU Zheng; CHEN Jianneng; FAN Guoshuai; WANG Qicheng; HUANG Peikui

doi:10.7671/j.issn.1001-411X.202208008

Journal of South China Agricultural University > 2023 > 44(4): 628-637. > DOI: 10.7671/j.issn.1001-411X.202208008

ZHAO Runmao, ZHU Zheng, CHEN Jianneng, et al. 3D LiDAR sensing method and experiment of plant row information extraction[J]. Journal of South China Agricultural University, 2023, 44(4): 628-637. DOI: 10.7671/j.issn.1001-411X.202208008

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3D LiDAR sensing method and experiment of plant row information extraction

1.
Faculty of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou 310018, China
2.
Zhejiang Key Laboratory of Planting Equipment Technology, Hangzhou 310018, China
3.
College of Engineering, South China Agruicultural University, Guangzhou 510642, China

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Received Date: August 02, 2022
Available Online: September 03, 2023
Published Date: May 24, 2023

Graphical Abstract

Abstract

Abstract

Objective
A low-cost 3D light detecting and ranging (LiDAR) point cloud information processing and plant row estimation method for environment perception in agricultural robot navigation is proposed for the areas where the satellite signal is seriously occluded in the forest or under the canopy.
Method
First, the pass through filter was used to filter out the target irrelevant points outside the area of interest. Secondly, the methods of mean shift clustering and scanning area adaptation were proposed to segment the trunk of each plant, and the vertical projection of the trunk point cloud was used to estimate the center point. Finally, the plant rows were estimated by determing the trunk centers with the least square fitting method. The simulation experiment and field experiment were carried out in the simulated orchard and metasequoia forest in the open field. The angle between the plant row vector and the due east was used as the index. The angle error between the plant row information identified by the proposed method and the true value of the plant row measured by GNSS satellite antenna positioning was calculated.
Result
Using the proposed method of 3D LiDAR point cloud information processing and plant row estimation, the average errors of plant row identification in simulation experiment and field experiment were 0.79° and 1.48°, the minimum errors were 0.12° and 0.88°, and the maximum errors were 1.49° and 2.33°, respectively.
Conclusion
The vehicle-mounted 3D LiDAR can effectively estimate the plant rows of metasequoia. This research enriches the ideas and methods of crop identification, and provides a theoretical basis for the map-free navigation of agricultural robots in areas without satellite signal coverage.
- Agricultural robot,
- 3D LiDAR,
- Point cloud processing,
- Plant row recognition,
- Field of view adaptation,
- Plant trunk division

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References (38)

References

[1]	刘建威. 中国工程院院士罗锡文在惠详解未来无人智慧农业[N/OL]. 惠州日报, 2020-11-20[2021-04-28]. https://new.qq.com/omn/20201120/20201120A023QU00.html.
[2]	刘成良, 林洪振, 李彦明, 等. 农业装备智能控制技术研究现状与发展趋势分析[J]. 农业机械学报, 2020, 51(1): 1-18. doi: 10.6041/j.issn.1000-1298.2020.01.001
[3]	魏爽, 李世超, 张漫, 等. 基于GNSS的农机自动导航路径搜索及转向控制[J]. 农业工程学报, 2017, 33(S1): 70-77. doi: 10.11975/j.issn.1002-6819.2017.z1.011
[4]	王辉, 王桂民, 罗锡文, 等. 基于预瞄追踪模型的农机导航路径跟踪控制方法[J]. 农业工程学报, 2019, 35(4): 11-19. doi: 10.11975/j.issn.1002-6819.2019.04.002
[5]	陈子文, 李伟, 张文强, 等. 基于自动Hough变换累加阈值的蔬菜作物行提取方法研究[J]. 农业工程学报, 2019, 35(22): 314-322. doi: 10.11975/j.issn.1002-6819.2019.22.037
[6]	杨洋, 张博立, 查家翼, 等. 玉米行间导航线实时提取[J]. 农业工程学报, 2020, 36(12): 162-171. doi: 10.11975/j.issn.1002-6819.2020.12.020
[7]	张漫, 季宇寒, 李世超, 等. 农业机械导航技术研究进展[J]. 农业机械学报, 2020, 51(4): 1-18. doi: 10.6041/j.issn.1000-1298.2020.04.001
[8]	师小波, 赵丁选, 孔志飞, 等. 基于多传感器信息融合的车辆高精度定位技术[J]. 中国机械工程, 2022, 33(19): 2381-2387.
[9]	徐筱龙, 徐国华. OutLand1000水下机器人的视觉定位研究[J]. 中国机械工程, 2010, 21(11): 1288-1292.
[10]	王殿君. 双目视觉在移动机器人定位中的应用[J]. 中国机械工程, 2013, 24(9): 1155-1158. doi: 10.3969/j.issn.1004-132X.2013.09.005
[11]	张雄楚, 陈兵旗, 李景彬, 等. 红枣收获机视觉导航路径检测[J]. 农业工程学报, 2020, 36(13): 133-140. doi: 10.11975/j.issn.1002-6819.2020.13.016
[12]	袁鹏成, 李秋洁, 邓贤, 等. 基于LiDAR的对靶喷雾实时控制系统设计与试验[J]. 农业机械学报, 2020, 51(S1): 273-280. doi: 10.6041/j.issn.1000-1298.2020.S1.032
[13]	赵腾. 基于激光扫描的联合收割机自动导航方法研究[D]. 杨凌: 西北农林科技大学, 2017.
[14]	张美娜, 吕晓兰, 邱威, 等. 基于三维激光点云的靶标叶面积密度计算方法[J]. 农业机械学报, 2017, 48(11): 172-178. doi: 10.6041/j.issn.1000-1298.2017.11.021
[15]	程曼, 蔡振江, WANG N, 等. 基于地面激光雷达的田间花生冠层高度测量系统研制[J]. 农业工程学报, 2019, 35(1): 180-187. doi: 10.11975/j.issn.1002-6819.2019.01.022
[16]	蔡吉晨. 基于二维激光雷达的果树在线探测方法及对靶变量喷药技术研究[D]. 北京: 中国农业大学, 2018.
[17]	薛秀云, 许旭锋, 李震, 等. 基于叶墙面积的果树施药量模型设计及试验[J]. 农业工程学报, 2020, 36(2): 16-22. doi: 10.11975/j.issn.1002-6819.2020.02.003
[18]	侯加林, 蒲文洋, 李天华, 等. 双激光雷达温室运输机器人导航系统研制[J]. 农业工程学报, 2020, 36(14): 80-88. doi: 10.11975/j.issn.1002-6819.2020.14.010
[19]	胡延平, 刘菲, 魏振亚, 等. 毫米波雷达与视觉传感器信息融合的车辆跟踪[J]. 中国机械工程, 2021, 32(18): 2181-2188. doi: 10.3969/j.issn.1004-132X.2021.18.006
[20]	ILCI V, TOTH C. High definition 3D map creation using GNSS/IMU/LiDAR sensor integration to support autonomous vehicle navigation[J]. Sensors, 2020, 20(3): 899. doi: 10.3390/s20030899
[21]	JAVANMARDI E, GU Y L, JAVANMARDI M, et al. Autonomous vehicle self-localization based on abstract map and multi-channel LiDAR in urban area[J]. IATSS Research, 2019, 43(1): 1-13. doi: 10.1016/j.iatssr.2018.05.001
[22]	侯德藻, 李克强, 连小珉, 等. 新型车载探测雷达系统技术研究[J]. 中国机械工程, 2004(21): 13-16. doi: 10.3321/j.issn:1004-132X.2004.21.003
[23]	管贤平, 刘宽, 邱白晶, 等. 基于机载三维激光扫描的大豆冠层几何参数提取[J]. 农业工程学报, 2019, 35(23): 96-103. doi: 10.11975/j.issn.1002-6819.2019.23.012
[24]	GUO T, FANG Y, CHENG T, et al. Detection of wheat height using optimized multi-scan mode of LiDAR during the entire growth stages[J]. Computers and Electronics in Agriculture, 2019, 165: 104959. doi: 10.1016/j.compag.2019.104959
[25]	刘守阳, 金时超, 郭庆华, 等. 基于数字化植物表型平台(D3P)的田间小麦冠层光截获算法开发[J]. 智慧农业(中英文), 2020, 2(1): 87-98.
[26]	陈莉. 玉米三维模型的重构及时序插值技术研究[D]. 成都: 电子科技大学, 2015.
[27]	苏伟, 蒋坤萍, 郭浩, 等. 地基激光雷达提取大田玉米植株表型信息[J]. 农业工程学报, 2019, 35(10): 125-130. doi: 10.11975/j.issn.1002-6819.2019.10.016
[28]	陈日强, 李长春, 杨贵军, 等. 无人机机载激光雷达提取果树单木树冠信息[J]. 农业工程学报, 2020, 36(22): 50-59. doi: 10.11975/j.issn.1002-6819.2020.22.006
[29]	刘路, 潘艳娟, 陈志健, 等. 高遮挡环境下玉米植保机器人作物行间导航研究[J]. 农业机械学报, 2020, 51(10): 11-17. doi: 10.6041/j.issn.1000-1298.2020.10.002
[30]	刘宽. LiDAR技术在农作物几何特征探测中的应用研究[D]. 镇江: 江苏大学, 2019.
[31]	GASPARINO M V, HIGUTI V A H, VELASQUEZ A E B, et al. Improved localization in a corn crop row using a rotated laser rangefinder for three-dimensional data acquisition[J]. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2020, 42(11): 592. doi: 10.1007/s40430-020-02673-z
[32]	孙意凡, 孙建桐, 赵然, 等. 果实采摘机器人设计与导航系统性能分析[J]. 农业机械学报, 2019, 50(S1): 8-14. doi: 10.6041/j.issn.1000-1298.2019.S0.002
[33]	史红霞, 王建民. 基于法向量区域聚类分割的点云特征线提取[J]. 中国机械工程, 2021, 32(21): 2552-2561. doi: 10.3969/j.issn.1004-132X.2021.21.004
[34]	王庆, 车荧璞, 柴宏红, 等. 基于无人机可见光与激光雷达的甜菜株高定量评估[J]. 农业机械学报, 2021, 52(3): 178-184. doi: 10.6041/j.issn.1000-1298.2021.03.019
[35]	张鹏鹏. 基于LiDAR数据的成熟水稻主要属性参数反演关键技术研究[D]. 镇江: 江苏大学, 2020.
[36]	管郡智. 基于激光雷达的三维点云目标检测算法研究[D]. 杭州: 浙江科技学院, 2020.
[37]	刘伟洪, 何雄奎, 刘亚佳, 等. 果园行间3D LiDAR导航方法[J]. 农业工程学报, 2021, 37(9): 165-174. doi: 10.11975/j.issn.1002-6819.2021.09.019
[38]	季宇寒, 徐弘祯, 张漫, 等. 基于激光雷达的农田环境点云采集系统设计[J]. 农业机械学报, 2019, 50(S1): 1-7. doi: 10.6041/j.issn.1000-1298.2019.S0.001

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3D LiDAR sensing method and experiment of plant row information extraction

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