An improved A* algorithm is proposed to address the issues of low search efficiency, path diagonally crossing obstacle vertices, and excessive turns in mobile robot path planning. Firstly, a strategy is introduced to avoid diagonally crossing obstacle vertices during the neighborhood expansion in the A* algorithm. Secondly, an exponential weight is applied to the evaluation function based on obstacle factors to reduce unnecessary search and improve the efficiency and adaptability of the A* algorithm, favoring paths with fewer obstacles. Finally, a three-phase optimization strategy is employed, considering the obstacle safety distance, to minimize redundant nodes and turns in the path. MATLAB simulations are conducted in grid maps of sizes 20×20 m, 40×40 m, and 60×60 m. The results demonstrate that the improved A* algorithm significantly reduces search time by 70.12%, 84.31%, and 91.44%, respectively, and reduces the number of expanded nodes by 53.77%, 71.20%, and 74.30%, respectively. Moreover, the accumulated turning angles in the path are reduced by 70.48%, 76.31%, and 82.18%, respectively. The improved A* algorithm effectively enhances the efficiency of mobile robot path planning, resulting in smoother and safer paths, especially in complex environments.