Voxel‐SLAM: A Complete, Accurate, and Versatile Light Detection and Ranging‐Inertial Simultaneous Localization and Mapping System

In this work, Voxel‐SLAM (simultaneous localization and mapping) is introduced: a complete, accurate, and versatile LiDAR (light detection and ranging) ‐inertial SLAM system consisting of five modules: initialization, odometry, local mapping (LM), loop closure (LC), and global mapping (GM), all employing the same map representation, an adaptive voxel map. The Voxel‐SLAM effectively utilizes short‐term, mid‐term, long‐term, and multimap data associations to achieve real‐time state estimation and high‐precision mapping. The odometry leverages short‐term data association and estimates current state with minimal latency. The LM, utilizing the mid‐term data association, designs an efficient LiDAR‐inertial bundle adjustment (BA) to refine the local map and states within a sliding window, which can run on an onboard computer in real time. The LC, exploiting the long‐term and multisession data association, can detect loops and support multisession mapping (up to five sessions in the experiments). To further capitalize these two data associations, the GM introduces an efficient global BA method and can even run on an onboard computer. Moreover, Voxel‐SLAM designs a robust initialization module to make the system start normally even under aggressive initial motion. In the presence of severe scene degeneracy or tracking loss, the system can automatically restart and relocalize to the previous tracking‐loss session when revisiting.