基于WebGIS的农机多机协同导航服务平台设计

Design of Agricultural Machinery Multi-machine Cooperative Navigation Service Platform Based on WebGIS

为向多台农业机械协同作业应用场景提供地图和导航服务支持,设计并开发了基于WebGIS的农机多机协同导航服务平台,该平台由GIS服务和农机调度2个功能模块组成。GIS模块基于GeoServer和JavaWeb提供网页端地图服务,在显示农场地图、实时标注农机位置的同时,也提供多农机导航结果的可视化显示功能;农机调度模块以路径规划算法和任务分配算法为核心,负责提供导航服务,在用户输入任务列表并调用服务的情况下,以GeoJSON格式返回各农机的任务分配以及路径规划结果。此外,为了筛选出满足平台需求且性能最优的算法,针对路径规划算法设计了算法性能对比实验,在导航距离近、中、远的3条路径上分别测试了基于A^(*)、Bellman-Ford、Dijkstra、Floyd和SPFA 5种算法的路径规划算法,并对不同算法的执行时间和最优路径长度进行了对比;针对任务分配算法设计了不同任务数量场景下的仿真对比实验,在任务数量为8、10、14、18的场景下分别测试了基于蚁群算法和遗传算法的任务分配算法,并对两者的执行速度和最优路径长度进行了对比。结果表明:基于Dijkstra算法的路径规划算法在结果最优的前提下执行速度最快,平均单次执行时间为0.25 ms。基于遗传算法的任务分配算法可以有效降低多机协同的路径代价,相较于随机生成的工作序列,路径代价减少50%~54%;相较于基于蚁群算法的任务分配算法,农机最佳路径长度减少19%~36%,执行时间减少51%~66%,平均执行时间在1 s以内。开发的多机协同导航服务平台通过使用Dijkstra算法和遗传算法分别进行路径规划和任务分配,能够基本满足多机协同作业的实时性需求。

In order to provide map and navigation service support for multi-agricultural machinery cooperative operation application scenarios,a multi-machine cooperative navigation service platform based on WebGIS was designed and developed.The platform consisted of two functional modules:GIS service and agricultural machinery scheduling.The GIS module provided web-side map services based on GeoServer and JavaWeb.While displaying the farm map and marking the location of agricultural machinery in real time,it also provided the visual display function of the navigation results of multiple agricultural machinery;the agricultural machinery scheduling module took the path planning algorithm and task allocation algorithm as the core,and responsible for providing navigation services.When the user provided the task list and invoked the service,it returned the task assignment and path planning results of each agricultural machine in GeoJSON format.In addition,in order to screen out the algorithm that met the platform requirements and had the best performance,algorithm performance comparison experiment were designed.The path planning algorithms based on A^(*),Bellman-Ford,Dijkstra,Floyd and SPFA were tested on three paths with short,medium and far navigation distances respectively,and the execution time and optimal path length were recorded and compared;for the task allocation algorithm,simulation comparison experiments under different task number scenarios were designed.The task allocation algorithms based on ant colony optimization and genetic algorithm were tested under the scenarios of 8,10,14 and 18 tasks respectively,and the execution speed and optimal path length of the algorithms were recorded and compared.The results showed that the path planning algorithm based on Dijkstra algorithm had the fastest execution speed under the premise of optimal results,and the average single execution time was 0.25 ms.The task assignment algorithm based on genetic algorithm can effectively reduce the path cost of multi-machine collaboration.Compared with the randomly generated work sequence,the path cost was reduced by 50%~54%;compared with the algorithm based on ant colony optimization,the optimal path length was reduced by 19%~36%,the execution time was reduced by 51%~66%,and the average running time was within 1 s.The developed multi-machine cooperative navigation service platform can basically meet the real-time requirements of multi-machine cooperative operation by using Dijkstra algorithm and genetic algorithm for path planning and task allocation.