Precise and Robust Color Point Cloud Registration with Correntropy-Based ICP Algorithm

The paper proposes a variant of the Iterative Closest Point (ICP) algorithm for point cloud registration that addresses two main issues with existing ICP-based algorithms: the lack of precise and complete color information and the lack of robustness to noise and outliers. The proposed algorithm introduces a color distance metric based on the L*a*b* color space and a correntropy-based objective function to enhance the accuracy and robustness of the algorithm. Simulation experiments on an RGB-D object dataset show that the proposed algorithm outperforms existing ICP-based methods in terms of accuracy and robustness.