To further improve the efficiency of material transportation intelligent vehicles and address the problem of unreasonable task allocation in multi-agent collaboration,a task allocation strategy for multi vehicle collaborative control based on regional partitioning auction algorithm is proposed.Firstly,the known environment is divided into regions based on the density of tasks to achieve task processing in the global environment.Secondly,different processing methods are divided according to task types.Local tasks are processed using optimized auction algorithms to improve the efficiency of multi vehicle collaboration.Global cross regional tasks use a two-layer framework to complete point-to-point task processing.Finally,further simulate the algorithm in a globally known environment and compare the task allocation algorithm for strike type unmanned aerial vehicles.The results show that the performance of this algorithm is more efficient in the use of intelligent vehicles,with stronger task carrying capacity and more reasonable task allocation strategies.It can be efficiently implemented in solving task allocation problems for multi vehicle collaborative control,simplifying complex task allocation processes.
维普
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