Vision-Assisted LiDAR-Inertial SLAM Based on Multiple Segments Under Degenerate Environment

To solve the issue that LiDAR simultaneous localization and mapping (SLAM) suffers from geometric degenerate environment, several works have sought supplementary measurement information from camera instruments, while ignoring the temporal consistency of degeneration and timing of vision information introduction. In the case of a continuously moving platform, degeneration typically manifests as segments, which can lead to significant issues for SLAM performance. To tackle this, we propose a vision-assisted LiDAR-inertial SLAM based on multiple segments under a degenerate environment, which solves the degenerate problem on LiDAR SLAM in the way of segment-based optimization. The degenerate segments are identified using an eigenvalue-based degenerate detection method with a buffer mechanism. In addition, the visual re-projection residuals are enforced within degenerate segments, together with LiDAR odometry residuals and inertial odometry residuals, through a dual sliding window approach. Finally, considering the pose nodes within the degenerate segment as individual fixed nodes, a pose graph in the back end is applied to merge segments for final pose estimation. The experiments with an ablation study on both simulation and real-world data are implemented, and the result demonstrates the robustness of the proposed method, compared against state-of-the-art algorithms.