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针对植保施药多个作业区域的情况,研究了一种植保无人机全局航线规划算法,将整个算法分为单个区域航线规划、区域间作业顺序和区域间调度航线规划3部分。从作业路程、多余覆盖和遗漏覆盖的角度,分析了多种覆盖作业方式的优劣,确定了无人机在单区域内的覆盖方式。基于遗传算法与TSP问题得到区域间的优化作业顺序,并基于改进的二进制编码遗传算法进行区域间调度航线的规划,最终实现无人机多作业区域航线的全局规划。仿真结果表明,规划算法可以有效地实现全局航线的规划,缩短了无人机的作业距离与区域间调度飞行的距离,达到了能耗与工作时间的优化,节省了航线规划所需的人力成本,使作业管理更加便利。
Aiming at the situation of multiple cropping sites, a global route planning algorithm for plant protection UAV was studied. The algorithm was divided into three parts: route planning of single area, operation sequence of inter-area and route planning of inter-area. From the perspectives of work route, redundant coverage and omission coverage, the advantages and disadvantages of multiple coverage methods are analyzed, and the coverage of the UAV in a single area is determined. Based on the genetic algorithm and the TSP problem, the optimal job sequence between regions is obtained. Based on the improved binary-coded genetic algorithm, the scheduling of inter-region dispatching routes is completed, and finally the global route planning of multi-job routes in UAVs is realized. The simulation results show that the planning algorithm can effectively plan the global route, shorten the distance between the UAV and the inter-area dispatching flight, optimize the energy consumption and working time, and save the labor cost of route planning , So that job management more convenient.