Aiming at the problems of long and unsmooth paths in the path planning of mobile robots traversing multiple target points, this paper proposes a multi-point traversal path planning method based on improved SMA. Firstly, the standard slime mold algorithm (SMA) is improved by combining Singer mapping and small hole imaging reverse learning strategy. Then, the map is preliminarily constructed, and the improved SMA is used to plan the path to determine the optimal value of the maximum side length of the triangular mesh. Finally, the triangular grid map is reconstructed based on the optimal value of the maximum edge length of the triangular mesh, the improved SMA is used to generate the path, and the path is smoothed by the B spline function to improve the smoothness of the path. The benchmark function test results show that the improved SMA converges faster and has higher optimization accuracy. Path planning experiments on triangular grid maps show that the path length and smoothness of improved SMA planning are significantly better than those of SMA, SSA and WOA, and compared with SMA, SSA and WOA, the length of the improved SMA generated path in complex scene is reduced by 6. 31%, 18. 76% and 19. 74%, which verifies the effectiveness of the improved SMA method.