Path Planning of Multi-AUVs Based on Multi-ant Colony Cooperative Search Algorithm

To solve the cooperative search problem of multiple autonomous undersea vehicles(AUVs) in an unknown en-vironment without considering the sonar detection distance and single optimization index, a collaborative path planning algorithm for multi-ant colonies based on prior information is proposed based on the comprehensive effect of detection distance on target discovery probability, AUV turning, and collision avoidance threat. First, based on the prior information of the target distribution, a target probability distribution map based on the grid of the search area is established. Subsequently, the pheromone concentration is initialized based on the probability distribution of the target, and the prior information is used to guide ant searches. State transition rules are designed based on the target probability size to maximize the probability of finding the target. Finally, the pheromone concentration is updated based on the advantages and disadvantages of the search path solution, and the effectiveness of the search strategy is verified by simulation.