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Objective: Disasters and accidents often occur in remote areas that are inaccessible by common transportation. Common map navigation software also fails to provide a passable path. Therefore, only SUVs can be used in field rescue. However, ground vehicles have limited awareness of their surroundings, so we chose to set up an air-ground cooperative system to overcome vehicles’ shortcoming. In the air-ground cooperative system, the UAV can provide environmental images surrounding the SUV for the ground terminal to obtain the navigation path of the vehicle by quickly extracting the type of surface and terrain undulations in the images. Method To better meet the above application requirement, this paper improves the existing A* algorithm with three main innovations. First, we proposed a passability cost function that integrates surface type and surface elevation information considering the application characteristics of outdoor surface environment. Second, we proposed a fast path search algorithm based on grid cells given the scale relationship between the resolution of UAV images and the actual vehicle paths. Third, we chose the marginal feature points of the grid for the passability path search in view of the connected surface type distribution inside the grid cell, which improves the search efficiency of the algorithm while taking into account the terrain information inside the grid cell, so that the algorithm could make full use of the detailed information of the UAV images and optimize the calculation. Result The 3D visualization experiments show that the paths searched by Grid A* algorithm are more reliable and meet the needs of SUVs. Conclusion The Grid A* algorithm proposed in this paper, aiming at the high-resolution images obtained by UAV, synthesizes image classification, slope calculation and other methods to structure a passability cost function, so that the paths are more reliable. In addition, the time cost of the algorithm is reduced to 15% of the traditional A* algorithm, which improves the timeliness of emergency rescue in the field.