Air-ground cooperative autonomous task allocation method for dynamic target search and strike
For the task of moving target search and strike in a complicated urban environment,the single-domain unmanned platform is limited by its field of vision and movement capability,which is easy to cause problems of the target omission and the low task completion rate.To solve these problems,an air-ground cooperative autonomous task allocation method for dynamic target search and strike is proposed.It aims to improve the efficiency of task execution and regional coverage of air-ground unmanned systems by combining the characteristics of the wide field of vision of unmanned aerial vehicles and the strong mobility of unmanned ground vehicles.For unknown moving targets,a target search model based on digital pheromones is proposed,which takes platform cooperation income and regional coverage as optimization metrics to ensure that all targets in the region can be found in the shortest possible time period.In addition,for the dynamic arrival strike task,a task allocation model based on feasible path planning is proposed,which takes the platform energy consumption and task completion time as the objective function to ensure the task completion rate and improve the resource utilization of the air-ground cooperative system.Compared with the existing methods,the proposed method can find all targets in the shortest time.The regional coverage rate can reach more than 55％.And the resource utilization rate is 84.4％.Experimental results show that the proposed method has excellent capabilities for target search and task execution.
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