Abstract
This study investigates the problem of cooperative search path planning for multiple unmanned aerial vehicles. Firstly, we present a search probability map based environmental model, and formulate a multi-UAV cooperative search path optimization problem. Then, we propose a solution strategy based on an improved intelligent water drops (IWD) optimization algorithm. Compared with the traditional IWD algorithm, the proposed algorithm can simultaneously model the cooperation and competition among UAVs by introducing several heterogeneous water drop populations and a co-evolutionary mechanism. Water drops in the same population cooperate with each other, whereas water drops among different populations compete with each other to obtain the optimal path and reduce meaningless search effort. Meanwhile, the proposed algorithm can improve its search capability using a new soil update mechanism. Simulation results demonstrate the advantages of the proposed method over other baselines.
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