Stereo Visual Inertial LiDAR Simultaneous Localization and Mapping
This addresses a specific limitation in mobile and aerial robotics by enhancing SLAM reliability in challenging environments, though it appears incremental as it combines existing components.
The paper tackles the problem of LiDAR-based SLAM failing in degenerate cases like tunnels by proposing Stereo Visual Inertial LiDAR (VIL) SLAM, which achieves improved accuracy and robustness compared to state-of-the-art LiDAR methods, generating loop-closure corrected 6-DOF LiDAR poses in real-time and 1cm voxel dense maps near real-time.
Simultaneous Localization and Mapping (SLAM) is a fundamental task to mobile and aerial robotics. LiDAR based systems have proven to be superior compared to vision based systems due to its accuracy and robustness. In spite of its superiority, pure LiDAR based systems fail in certain degenerate cases like traveling through a tunnel. We propose Stereo Visual Inertial LiDAR (VIL) SLAM that performs better on these degenerate cases and has comparable performance on all other cases. VIL-SLAM accomplishes this by incorporating tightly-coupled stereo visual inertial odometry (VIO) with LiDAR mapping and LiDAR enhanced visual loop closure. The system generates loop-closure corrected 6-DOF LiDAR poses in real-time and 1cm voxel dense maps near real-time. VIL-SLAM demonstrates improved accuracy and robustness compared to state-of-the-art LiDAR methods.