For complex working environments, traditional path planning algorithms for mobile robots are inefficient and difficult to get the optimal path. To better solve this problem, this paper introduces the fuzzy model for modeling and analysis. On the basis of elaborating the logical relationship between the T-S fuzzy model and the Kripke structure, the basic model of the robot’s moving path is designed and the map representation of the moving path is constructed. Based on the minimal repair algorithm of the fuzzy model, the virtual path fuzzy rule of the robot movement is established, and the hierarchical fuzzy control system is constructed by combining the robot kinematics movement model, and simulation experiments are carried out to verify the effectiveness of the above method. The state response x1, x2 of the hierarchical fuzzy control system realizes zero convergence at 5.12s and 3.91s, respectively, and the zero convergence time of the fuzzy control input is 79.23% lower than that of the Takagi-Sugeno fuzzy system. The lateral error of the hierarchical fuzzy control robot movement is approximately 0.05m, and the path length decreases from 1.38% to 4.37% with the map scale increasing. The use of a fuzzy model minimal repair algorithm can improve the efficiency of robot movement and obtain a relatively optimal path in a shorter time.