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Evaluates localization and mapping performance in dynamic environments, indicating significant improvements.
In dynamic environments, Simultaneous Localization and Mapping (SLAM) systems often struggle with the challenges posed by moving objects. To address these issues, we propose Dynamic-Object-Elimination LiDAR-Visual-Inertial SLAM (DOE-LVI), an advanced tightly coupled LiDAR-Visual-Inertial SLAM system. DOE-LVI integrates two primary subsystems: the Visual-Inertial System (VIS) and the LiDAR-Inertial System (LIS). The VIS component extracts depth information from LiDAR scans and correlates it with visual features, providing accurate pose estimation by minimizing both visual and IMU residuals. The LIS uses this initial estimate to generate range images and perform preliminary removal of dynamic points. Misclassified points are then corrected through ground fitting and precise scan matching with the submap. For enhanced loop closure detection, DOE-LVI employs global LiDAR descriptors, which significantly improve both localization robustness and accuracy. Experimental evaluations on the KITTI and UrbanNav datasets demonstrate that DOE-LVI achieves robust localization and mapping performance, particularly in highly dynamic environments.
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Li et al. (2026) studied this question.
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