To address the shortcomings of Rapidly-Exploring Random Tree algorithm (RRT) in the path planning of mobile robots, with many turning points and a large number of redundant points, an improved RRT algorithm based on cell decomposition method is proposed. Firstly, in the initial stage of the algorithm, the cell decomposition method is used to divide the map into feasible regions and obstacle regions; later, according to the neighboring relationship between regions, the selection of random sampling points is fixed in the neighboring regions until it is extended to the region where the target point is located; and the final path searched is optimized to improve the problem of too many path turning points. Simulation results show that the path generated by the improved RRT algorithm is shorter in length and consumes less time. Finally, the improved RRT algorithm is applied to the actual mobile robot to further prove the practicality and effectiveness of the improved algorithm.