LIO-GVM: an accurate, tightly-coupled Lidar-inertial odometry with Gaussian voxel map
This letter presents a probabilistic voxel-based LiDAR Inertial Odometry framework for accurate and robust pose estimation. The framework addresses the correspondence mismatching issue by representing the LiDAR points as a set of Gaussian distributions and evaluating the divergence in variance for o...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/178008 |