ICP Variants

Iterative Closest Point (ICP) variants are methods used to align two 3D datasets, like point clouds, by iteratively refining their fit. Different variants modify the original algorithm to improve accuracy, speed, or robustness. Some variants handle noisy data better, while others work faster or align more complex shapes. For example, some use alternative ways to match points, incorporate additional information, or optimize the process for specific applications like robotics or medical imaging. Overall, these variants aim to find the best possible alignment between datasets efficiently and reliably, adapting the core ICP approach to different challenges.