Multiple point cloud registration and global consistency condition

Point cloud registration is a central problem in many mapping and monitoring applications such as 3D model reconstruction, computer vision, autonomous driving, and others. Generating maps of the environment is often referred to as the Simultaneous Localization and Mapping (SLAM) problem. Note that some point clouds from the considered set may not have intersections. In this paper, we propose an algorithm to align the multiple point clouds based on an effective pairwise registration and a global refinement algorithm. The global refinement algorithm is non-iterative. Computer simulation results are provided to illustrate the performance of the proposed method.