果园自主导航兼自动对靶喷雾机器人  

Autonomous Navigation and Automatic Target Spraying Robot for Orchards

作　　者：刘理民 何雄奎[1,2] 刘伟洪 刘紫嫣 韩虎 李扬帆 LIU Limin;HE Xiongkui;LIU Weihong;LIU Ziyan;HAN Hu;LI Yangfan(College of Science,China Agricultural University,Beijing 100193,China;College of Agricultural Unmanned System,China Agricultural University,Beijing 100193,China;College of Engineering,China Agricultural University,Beijing 100083,China)

机构地区：[1]中国农业大学理学院,北京100193 [2]中国农业大学农业无人机系统研究院,北京100193 [3]中国农业大学工学院,北京100083

出　　处：《智慧农业（中英文）》2022年第3期63-74,共12页Smart Agriculture

基　　金：国家梨产业体系(CARS-28);国家自然科学基金资助项目(31761133019);中国农业大学2115人才培育发展支持计划;三亚中国农业大学研究院引导资金项目(SYND-2021-06)。

摘　　要：为同时实现果园智能植保机自主导航及自动对靶喷雾,研制了一种果园自主导航兼自动对靶喷雾机器人。首先采用单个3D LiDAR(Light Detection and Ranging)采集果树信息确定兴趣区(Region of Inter⁃est,ROI),对ROI内点云进行2D化处理得到果树质心坐标,通过随机一致性(Random Sample Consensus,RANSAC)算法得到果树行线,并确定果树行中间线(导航线),进而控制机器人沿导航线行驶。通过编码器及惯性测量单元(Inertial Measurement Unit,IMU)确定机体速度及位置,IMU矫正采集到的果树分区冠层信息,最后通过程序判断分区冠层的有无控制喷头是否喷雾。结果表明,机器人自主导航时最大横向定位偏差为21.8 cm,最大航向偏角为4.02°,相比于传统连续喷雾机施药液量、空中漂移量及地面流失量分别减少20.06%、38.68%及51.40%。本研究通过单个3D LiDAR、编码器及IMU在保证喷雾效果的前提下,实现了喷雾机器人自主导航及自动对靶喷雾,降低了农药使用量及飘失量。To realize the autonomous navigation and automatic target spraying of intelligent plant protect machinery in orchard,in this study,an autonomous navigation and automatic target spraying robot for orchards was developed.Firstly,a single 3D light detection and ranging(LiDAR)was used to collect fruit trees and other information around the robot.The region of interest(ROI)was determined using information on the fruit trees in the orchard(plant spacing,plant height,and row spacing),as well as the fundamental LiDAR parameters.Additionally,it must be ensured that LiDAR was used to detect the canopy information of a whole fruit tree in the ROI.Secondly,the point clouds within the ROI was two-dimension processing to obtain the fruit tree center of mass coordinates.The coordinate was the location of the fruit trees.Based on the location of the fruit trees,the row lines of fruit tree were obtained by random sample consensus(RANSAC)algorithm.The center line(navigation line)of the fruit tree row within ROI was obtained through the fruit tree row lines.The robot was controlled to drive along the center line by the angular velocity signal transmitted from the computer.Next,the ATRS's body speed and position were determined by encoders and the inertial measurement unit(IMU).And the collected fruit tree zoned canopy information was corrected by IMU.The presence or absence of fruit tree zoned canopy was judged by the logical algorithm designed.Finally,the nozzles were controlled to spray or not according to the presence or absence of corresponding zoned canopy.The conclusions were obtained.The maximum lateral deviation of the robot during autonomous navigation was 21.8 cm,and the maximum course deviation angle was 4.02°.Compared with traditional spraying,the automatic target spraying designed in this study reduced pesticide volume,air drift and ground loss by 20.06%,38.68% and 51.40%,respectively.There was no significant difference between the automatic target spraying and the traditional spraying in terms of the percentage of ai

关 键 词：自主导航 对靶喷雾 LIDAR 随机一致性算法 机器人 惯性测量单元 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] S224.3[自动化与计算机技术—控制科学与工程]