A multi-layer optimization method for mobile robot path planning is proposed for the problems of map environment modeling and ant colony algorithm. In this method, firstly, the U-trap raster region is convexized to avoid the pre-search confusion, a new state transfer rule is designed to solve the problem that the path of conventional ant colony planning is too close to the obstacles, the distance heuristic function is improved to effectively improve the convergence speed of the algorithm, the smoothing heuristic function is designed to increase the chance of ants going straight when local exploration is performed to improve the initial path smoothing, the update principle is proposed to allocate pheromones according to the distance length and The update principle of pheromone assignment by distance and smoothness is proposed to further improve the convergence speed of the algorithm by using high-quality ants for global pheromone update, the maximum-minimum ant strategy is used to prevent the ant colony from falling into local optimum, the redundant points are removed by the secondary path optimization strategy to further improve the path smoothness. Simulation and experimental results show that the method can plan a safe and comprehensive path for the mobile robot, which provides a practical method for the solution of path planning.