Aiming at the problems of slow convergence and easy to fall into local optimum in three-dimensional path planning of Unmanned Aerial Vehicles (UAVs), this paper propeses an ant colony algorithm with improved artificial potential field, constructs a gravitational potential field, and initializes pheromones in the preliminary searchable area with the resultant force of improved artificial potential field as a coefficient.A random pheromone volatilization factor updating mechanism is proposed, which improves the heuristic function and pheromone updating rules of ant colony algorithm, introduces gravitational potential energy to simulate UAV flying at high altitude, and applies it to pheromone updating.Finally, two groups of comparative experiments are set up to compare the four algorithms.The comparison results show that the improved algorithm can effectively solve the problems existing in the ant colony algorithm, improve the efficiency and ability of the algorithm to search the path, and converge to the optimal value in different environments, which proves the adaptability and effectiveness of the algorithm.