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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 0.25ms. 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 1s. 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.