Ant colony algorithm plays an important role when intelligent underwater robots carry out path planning in areas such as ocean development, underwater operation, submarine exploration, submarine rescue and life assistance. Because the ant colony algorithm has a certain randomness, together with the large number of ant colonys, it is not only slow to find the optimal solution of the algorithm, but also has interference with problems such as local optimal solutions. In this paper, a co-evolution algorithm is proposed to optimize the three-dimensional path planning problem of the underwater vehicle.By comparing the ant colony algorithm with the particle swarm algorithm and the ant colony algorithm of dynamic pheromone, the efficiency and stability of the algorithm are improved, and the population can select a better path faster to reach the target node.