The path planning of mobile robots is an optimization problem that is difficult to solve directly owing to its nonlinear characteristics. This letter proposes the “global–local” Coupling Two-Stage Path Planning (CTSP) method. First, the globally optimal solution in the configuration space is given by the global planner. Then, in the local planning stage, the optimal solution of the local environment is constantly searched, guided by the prior information of the globally optimal solution. The strategy used in the global planning stage is the iterative optimization method based on an initial solution. The local planning stage adopts the sampling-evaluation strategy, that is, sampling the candidate paths and then using the evaluation function to perform path selection. The proposed method has two innovations: 1) a novel global iterative optimization method is proposed and 2) a new cost function for evaluating the sampled paths is constructed, which improves the coupling of the global and local paths. We implement and test this method in a simulation environment, where the experimental results verify the effectiveness of the proposed method.