Aiming at the shortcomings of traditional ant colony algorithm, such as easy to fall into local optimum and low precision of solution, this paper proposes an improved particle swarm optimization and ant colony algorithm to calculate the optimal path. In this algorithm, particle swarm optimization algorithm with linear decreasing inertia weight coefficient is used for path pre-planning, so as to obtain the initial pheromone distribution of ant colony algorithm. At the same time, by introducing new heuristic function, linear decreasing volatility coefficient and pheromone increment coefficient arranged according to path length into ant colony algorithm, the convergence speed of the algorithm is improved. Experimental results show that the path length error of the algorithm in two environments is 0% and 0.9297% respectively. Compared with the traditional algorithm, this algorithm has higher accuracy.