Iterative Closest Point

Iterative Closest Point (ICP) is a widely used algorithm for aligning 3D point clouds, crucial for tasks like 3D mapping, robot localization, and object registration. Current research focuses on improving ICP's robustness and accuracy, particularly in challenging environments or with noisy data, through techniques such as incorporating additional sensor data (e.g., altimeters, Doppler velocity), employing Bayesian optimization for improved initialization, and developing weighted or manifold-aware variants. These advancements enhance the reliability and efficiency of ICP across diverse applications, including autonomous navigation, medical imaging, and smart space management.