Cooperative Search Algorithm for UAVs Based on Multi-ant Colony

The cooperative search problem of multiple unmanned aerial vehicles (UAVs) in unknown sea environment is studied. Considering the influence of detection distance on target detection probability, UAV steering and collision avoidance threat, a multi ant colony cooperative search algorithm based on prior information is proposed. Firstly, according to the prior information of target distribution, the probability distribution map of target based on searching region is established. Then, the pheromone concentration is initialized according to the target probability distribution, and the prior information is used to guide various ant colony searches. According to the target probability, the state transition rules are designed to maximize the target discovery probability. Finally, the pheromone concentration is updated according to the advantages and disadvantages of the search path solution, and the effectiveness of the search strategy is verified by simulation.