Research on UAV Collaborative Task Planning Based on Ant Colony Algorithm
Drone search has the advantages of strong maneuverability and high positioning accuracy.Based on the actual situation,simulate the coordinated sea area planning problem of unmanned aerial vehicles from the red and blue sides,and solve two problems:One is the problem of collaborative search.Using the BFS algorithm to first visualize the heat map,and based on the ant colony algorithm to plan the optimal search route for the red drone,then using the K-means clustering algorithm to allocate multiple drones to multiple areas,can achieve collaborative search of drones.The second issue is the issue of full regional coverage.Calculate whether the roundness of the area is greater than 0.86 to determine whether to use the spiral method or the mowing method,which search method to achieve full area coverage.Finally,the hot spot area was segmented according to different search modes,and a maneuvering model of the blue search ship was established.
linear programmingBFS algorithmK-means clustering algorithmant colony algorithmgeometric analysis method
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