Abstract: Existing three-dimensional map building algorithms emphasize the accuracy of map building, resulting in low efficiency and high cost of mapping. In order to improve the efficiency of building a map, an improved algorithm is proposed to recognize and extract the cylinder of a landmark object and to construct a simplified map with its axis features as landmarks. Based on random sampling consistency (RANSAC) algorithm, this algorithm generates and matches the cylinder model to be estimated in the point cloud model. By calculating the homography matrix and its error function, the optimum threshold in the iteration process is obtained to get the optimum matching cylinder model and improve the extraction efficiency. Then, the spatial position of the landmark is described by the extracted cylinder axis. Cylindrical radius describes the spatial geometric information of landmarks. Compared with the traditional RANSAC method, the simulation results show that this method can effectively simplify the map and lay the foundation for the subsequent path planning of landmark recognition.

Key words: point clouds, three-dimensional map, feature extraction, RANSAC