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 instrument, while ignoring 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 degenerate environment, which solves degenerate problem on LiDAR SLAM in the way of segment-based optimization. The degenerate segments are identified using 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 as well as inertial odometry residuals, through a dual sliding window approach. Finally, considering the pose nodes within degenerate segment as individual fixed node, a pose graph in back end is applied to merge segments for final pose estimation. The experiments with ablation study on both simulation and real-world data are implemented, and the result demonstrates robustness of proposed method, compared against state-of-the-art algorithms.