Floorplan-based Localization and Map Update Using LiDAR Sensor

In this paper, we propose a novel localization and map update method for indoor using the LIDAR sensor and floorplan. Existing indoor localization algorithms need a previously generated 3D map and match those maps to the actual structure to get the precise location because there is no position reference like GPS. To solve this problem, the localization and map update method based on the floorplan, which generally exists, is proposed. For this, 3D LiDAR point clouds are accumulated, and ceiling parts are extracted, which is less sensitive to environmental changes such as furniture. Thereafter, the lines are extracted from the border of the ceiling parts, and the position is estimated through the Monte Carlo Localization algorithm using the comparison with floorplan lines. Even the ceiling parts are less sensitive to environmental changes, the floorplan and the actual environment may be different due to modification of the structure like added walls. Therefore, if the estimated position is determined to be accurate, extracted lines are merged with the previous floorplan line map. The proposed algorithm is tested in the actual environment, and through the results, the performance of the algorithm has been verified.