Efficient SLAM Scheme–Based ICP Matching Algorithm Using Image and Laser Scan Information

This paper proposes a scan-matching simultaneous localisation and mapping (SLAM)-based Iterative Closest Point algorithm using laser scan information and images in an indoor environment. The ICP algorithm, which is one of the scan-matching methods calculates the closest position iteratively by adjusting the motion vector and rotation matrix of the model. The matching process requires a great deal of time, in accordance with the size of the point cloud model and repetitive execution. The proposed method uses part of the feature model and performs the matching by setting up the adjusting range of the motion vector and rotation matrix through the maximum velocity of a mobile robot. It then estimates the pose of the mobile robot using the relationship between the models. In order to evaluate the efficiency of the proposed algorithm, experiments driving the mobile robot were executed, such as estimating the pose of the mobile robot and building a map.