Zeng Guoqi, Bai Yu, Liu Chunlei, Cui Kai, and Yue Huanyin
PSO, swarming UAVs, multitask assignment, roulette method
As a form of multi-unmanned aerial vehicle (UAV) cooperation, swarming UAVs have become a popular UAV research. Given the large number of UAVs in a swarm and the limited loading resources of each UAV, a reasonable task allocation scheme is the premise and key of task execution. This work proposed an online task assignment method using roulette with the weight vector analysis to realize the discretization, reduce the probability of invalid solution and improve the efficiency of particle swarm optimization (PSO). The characteristics of task assignment in swarming UAVs and the uncertainty factors were studied. Experiments showed that the proposed algorithm had faster iteration speed and higher algorithm precision than the normal PSO method and was suitable for the task assignment of swarming UAVs.
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