GT-ICP: A General Temporal ICP algorithm for simultaneous frame-to-frame registration and motion compensation

Rigid registration of 3D point clouds is a fundamental process in computer graphics, computer vision and robotics. A widely used approach for registering two point clouds is the Iterative Corresponding Point (ICP). Over the years, ICP algorithms have been intensively studied for improving their robustness and versatility. With modern acquisition devices, it becomes common to acquire geometries with fast motion while most of the acquisition systems rely on a rolling shutters technology: within a frame, acquisition is performed at different times for each location. In case of fast motion or relatively-low frame-rate, this leads to motion distortions that are not directly handled by classical frame-to-frame registration. Our contribution is a new formulation of the ICP, denoted General Temporal Iterative Closest Point ( GT-ICP ), that simultaneously solves the registration and the motion compensation problems between successive LiDAR frames. In contrast to previous work, we explicitly take into account the acquisition time of each individual point in the ICP frame-to-frame optimization. We demonstrate and compare our reformulation on several variants of the ICP algorithm and motion distortion correction techniques, applied both on simulated and acquired data.