small_gicp: Efficient and parallel algorithms for pointcloud registration

Point cloud registration is a task of aligning two point clouds measured by 3D ranging sensors, for example, LiDARs and range cameras.Iterative point cloud registration, also known as fine registration or local registration, iteratively refines the transformation between point clouds starting from an initial guess.Each iteration involves a proximity-based point correspondence search and the minimization of the distance between corresponding points, continuing until convergence.Iterative closest point (ICP) and its variants, such as Generalized ICP, are representative iterative point cloud registration algorithms.They are widely used in applications like autonomous vehicle localization (Kim et al., 2022), place recognition (Wang et al., 2020), and object classification (Izadinia & Seitz, 2020).Since these applications often require real-time or near-real-time processing, speed is a critical factor in point cloud registration routines.