Global path planning for unmanned ground vehicle based on road map images

In automatic navigation of mobile systems, first, they require providing a path network for robot/vehicle motion. Therefore, path planning is an important task of autonomous vehicle systems. To deal with the problem, this paper presents a method for constructing the shortest path, which support for vehicle auto-navigation in outdoor environments. The method using online road map images to estimate not only the shape of road network but also the directed road network, which could not be estimated by the use of only aerial/satellite images. The proposed method to solve this problem includes three stages. First, a raw network of path for motion is detected using the road map images. Second, the path network is converted to the Global coordinates, which provides a convenience for online auto-navigation task. Third, the shortest path for motion is estimated based on the A* algorithm. The experimental results demonstrate robustness and effectiveness of the method for path networks estimation under the large scene of outdoor environments.