再生稻头季低碾压收获作业路径规划技术研究  

Path Planning Technical Research of Low-rolling Compaction Harvesting Operation for the First Season of Ratoon Rice

作　　者：胡炼[1,2] 张鸿 何杰 满忠贤[1] 岳孟东 屈高凯 唐启源 黄培奎 罗锡文 HU Lian;ZHANG Hong;HE Jie;MAN Zhongxian;YUE Mengdong;QU Gaokai;TANG Qiyuan;HUANG Peikui;LUO Xiwen(Key Laboratory of Key Technology on Agricultural Machine and Equipment,Ministry of Education,South China Agricultural University,Guangzhou 510642,China;State Key Laboratory of Agricultural Equipment Technology,Guangzhou 510642,China;Hunan Hongshuo Biotechnology Co.,Ltd.,Yiyang 413119,China;College of Agronomy,Hunan Agricultural University,Changsha 410128,China)

机构地区：[1]华南农业大学南方农业机械与装备关键技术教育部重点实验室,广州510642 [2]农业装备技术全国重点实验室,广州510642 [3]湖南宏硕生物科技有限公司,益阳413119 [4]湖南农业大学农学院,长沙410128

出　　处：《农业机械学报》2025年第2期19-27,共9页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家重点研发计划项目(2021YFD2000600、2022YFD2301003)。

摘　　要：路径规划是决定再生稻头季收获作业效率和质量的关键因素之一。目前,无人农机在作业区域内的全覆盖路径规划技术研究中,较少有考虑收获机在田间收获时对再生稻的碾压问题,为此本文开展减少碾压的再生稻收获路径规划研究。通过分析农田信息、待作业区域和卸粮等,将再生稻收获卸粮路径规划问题转化为带有容量约束的车辆路径问题(CVRP)。以收获机最小碾压面积和最短总路径为目标,构建再生稻收获路径数学模型。提出再生稻少碾压路径规划混合算法,采用传统蚁群算法(ACO)和2-opt算法获得最优路径。以再生稻无人驾驶收获机为对象,设计直线路径规划田间试验、地头转向路径以及卸粮路径规划田间试验和全环节田间作业试验,采用自动驾驶系统进行田间试验,考察收获机田间碾压率。结果表明,直线跟踪平均绝对误差为3.51 cm,最大偏差为8.24 cm,直线段作业碾压率为17.55%。地头区域碾压率下降52.2%。本研究设计的路径规划全田碾压率为27.42%,满足再生稻特殊的作业要求。Path planning is one of the key factors determining the efficiency and quality of the first season harvest operation for regenerated rice.At present,there are many studies on the full coverage path planning technology of unmanned agricultural machinery in the operating area,but little consideration is given to the problem of the harvester crushing the regenerated rice during field harvesting.Therefore,research on the path planning of regenerated rice harvesting was conducted with reduced crushing.By analyzing farmland information,waiting areas,and unloading of grain,the problem of harvesting and unloading path planning for regenerated rice was transformed into a vehicle routing problem with capacity constraints(CVRP).A mathematical model for the harvesting path of regenerated rice was constructed with the goal of minimizing the rolling area and minimizing the total path of the harvester.A hybrid algorithm for path planning of regenerated rice with less compaction was proposed,using traditional ant colony algorithm(ACO)and 2-opt algorithm to obtain the optimal path.Taking the driverless harvester of ratooning rice as the object,the field experiments of straight path planning,headland turning,grain unloading planning and full link field operation were designed.The field experiments were conducted with the auto drive system to investigate the field compaction rate of the harvester.The results showed that the average absolute error of linear tracking was 3.51 cm,the maximum deviation was 8.24 cm,and the compaction rate of the linear segment was 17.55%.The compaction rate in the head area was decreased by 52.2%.The path planning designed had a total field compaction rate of 27.42%,which met the special operational requirements for regenerated rice.The research result can provide theoretical and technical support for reducing the crushing area of unmanned harvesting machines for regenerated rice.

关 键 词：再生稻 收获机 无人驾驶 路径规划 蚁群算法 2-opt算法 

分 类 号：S220[农业科学—农业机械化工程] S24[农业科学—农业工程]