Abstract: When planning the traveling path of a mobile robot using the traditional A^* algorithm, there are problems such as longer path finding time, higher number of traversed nodes and path transitions, for this reason, an improved A^* algorithm is proposed. First of all, the proportion of obstacles in the surroundings of the mobile robot is calculated, and the environmental obstacle rate is utilized to change the weight of the heuristic function in different environments. Afterwards, redundant nodes and turning points in the path are removed by the critical point of the chosen solution. In addition, the number of nodes in the open table is optimized by removing the nodes that were added earlier in the table and those with larger valuations. Finally, simulation experiments in Matlab indicate that, for both experimental environments, in comparison with the traditional A^* algorithm, the improved A^* algorithm has a reduction in path planning time by 57.14% and 55.56%, the number of transitions by 37.5% and 50%, the number of nodes traversed by 57.46% and 76.19%, and the length of the paths by 0.003% and 0.04%, respectively. According to the experimental outcomes, the proposed improved A^* algorithm can effectively minimize the time of path planning, the number of turning points of the path and the number of nodes traversed by the algorithm.