四边形田块下油菜联合收获机全覆盖作业路径规划算法

为解决无人农场模式下油菜联合收获作业过程中自主导航作业路径自动规划及优化问题,该研究提出了两套完整的针对任意四边形边界田块的油菜联合收获全覆盖作业路径规划算法。采用"理论分析-算法设计及程序编码-算例测试与仿真评估"的技术路线及方法,首先分析油菜联合收获机的作业特点与机具特性,拟定油菜联合收获无人化作业过程对路径规划工作的基本要求,再通过等距偏置处理和扫描线填充算法生成全覆盖作业路径,并采用OR-Tools软件对方向平行路径进行调度优化。通过4块典型实际田块进行仿真计算和测试,结果表明,算法耗时在0.17～4.73 s之间,混合路径相对于目前生产中广泛使用的环形作业路径,在未经行调度优化时,倒车次数减少36.36%～40.00%;混合路径中,行调度优化后倒车次数相对于未调度优化时减少33.33%～60.87%,非作业路径长度减少7.20%～20.23%。该研究为长江中下游区域稻油轮作无人农场中油菜无人化联合收获提供了作业路径规划方面的理论与技术支撑。

Coverage operation path planning algorithms for the rape combine harvester in quadrilateral fields

To realize automatic planning and optimization of operation paths for the autonomous navigation of rape combine harvesters during the harvesting operation in unmanned farms, two sets of coverage path planning algorithms for arbitrary quadrilateral fields were proposed in this study through procedures including theoretical analysis, design of algorithms, programming, and simulation and evaluation using examples. First, the fundamental requirements of the coverage path planning problem for the unmanned operation process of the rape combine harvest were defined after analyzing the characteristics of the harvesting process (plant branches intertwined and required to be separated by vertical cutters to reduce harvest loss, and field boundaries generally not crossable in rice/rape rotation regions) and of the combine harvesters (small turning radii and strong mobility of crawler-type machines). Then, full coverage operation paths were generated based on an isometric offsetting process and the scanline filling algorithm, and scheduling optimization was performed using the OR-Tools. The two sets of global operation coverage path planning algorithms for rape harvesting in arbitrary quadrilateral fields included one for the "contour parallel" circular operation paths based on the one-sided vertical cutter header and the other for the "contour parallel + direction parallel" mixed operation paths based on the bilateral vertical cutter header. The latter algorithm first used contour parallel paths to harvest the field to make enough turning space for the machine, and then it used the direction parallel paths to complete the harvesting operation in the central area. Through the test and simulation using the data of four typical actual fields, the stability and reliability of the algorithms were verified, and the algorithm running time was between 0.17 s and 4.73 s, which meets the basic requirements of path planning of rape combine harvesting for unmanned farming. At the same time, compared with the circular operation paths, which are widely used in actual harvesting operation, the total operation length of mixed paths was smaller than that of the traditional circular paths when no optimization was performed and the turning radius was small, and the number of reverses in the operation process was reduced by 36.36%-40.00%. After optimization, the number of reverses was further reduced by 33.33%-60.87%, and the length of non-operation paths was reduced by 7.20%-20.23% compared with the path without any optimization. Results showed that the mixed paths resulted in a better operation effect than the traditional circular operation paths. This study could provide theoretical and technical support for the combined harvesting of winter rape in unmanned farming of rice/rape rotation in the middle and lower reaches of the Yangtze River in China.