Abstract: Path planning is one of the important contents of research on coal mine rescue robots. A path planning method for coal mine rescue robots based on improved A^* algorithm is proposed to address the unstructured features of post disaster coal mine environments and the problems of non-shortest path length, multiple turns, and poor smoothness of path planned by traditional A^* algorithm. The method constructs raster maps by binarizing map information in real environments, determines the relative position between the current point and the target point, and uses the improved A^* algorithm for path planning. Then a path from the current point to the target point is obtained. Douglas-Pucker (D-P) algorithm is used to extract key nodes on the path, and cubic spline interpolation function is used to fit the key nodes, thereby completing the smooth processing of the path. The improved A^* algorithm expands the traditional A^* algorithm's 8 neighborhood search to a purposeful 13 neighborhood search. When conducting path search, the position relationship between the current point and the target point is first determined, thereby reducing path nodes and length, and improving path smoothness. The Matlab simulation results show that compared with the 8 neighborhood A^* algorithm, 24 neighborhood A^* algorithm, and 48 neighborhood A^* algorithm, the improved A^* algorithm has certain optimizations in path length, number of turns and smoothness. It is more suitable for path planning of coal mine rescue robots. Compared with the Fuzzy algorithm, the improved A^* algorithm achieve shorter path planning time, shorter planned path length, and fewer turns.