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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.04311 |
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| _version_ | 1866909689212567552 |
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| author | Dong, Yan Xu, Enci Qiu, Shaoqiang Li, Wenxuan Liu, Yang Han, Bin |
| author_facet | Dong, Yan Xu, Enci Qiu, Shaoqiang Li, Wenxuan Liu, Yang Han, Bin |
| contents | High-speed ground robots moving on unstructured terrains generate intense high-frequency vibrations, leading to LiDAR scan distortions in Lidar-inertial odometry (LIO). Accurate and efficient undistortion is extremely challenging due to (1) rapid and non-smooth state changes during intense vibrations and (2) unpredictable IMU noise coupled with a limited IMU sampling frequency. To address this issue, this paper introduces post-undistortion uncertainty. First, we model the undistortion errors caused by linear and angular vibrations and assign post-undistortion uncertainty to each point. We then leverage this uncertainty to guide point-to-map matching, compute uncertainty-aware residuals, and update the odometry states using an iterated Kalman filter. We conduct vibration-platform and mobile-platform experiments on multiple public datasets as well as our own recordings, demonstrating that our method achieves better performance than other methods when LiDAR undergoes intense vibration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_04311 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Vibration-aware Lidar-Inertial Odometry based on Point-wise Post-Undistortion Uncertainty Dong, Yan Xu, Enci Qiu, Shaoqiang Li, Wenxuan Liu, Yang Han, Bin Robotics High-speed ground robots moving on unstructured terrains generate intense high-frequency vibrations, leading to LiDAR scan distortions in Lidar-inertial odometry (LIO). Accurate and efficient undistortion is extremely challenging due to (1) rapid and non-smooth state changes during intense vibrations and (2) unpredictable IMU noise coupled with a limited IMU sampling frequency. To address this issue, this paper introduces post-undistortion uncertainty. First, we model the undistortion errors caused by linear and angular vibrations and assign post-undistortion uncertainty to each point. We then leverage this uncertainty to guide point-to-map matching, compute uncertainty-aware residuals, and update the odometry states using an iterated Kalman filter. We conduct vibration-platform and mobile-platform experiments on multiple public datasets as well as our own recordings, demonstrating that our method achieves better performance than other methods when LiDAR undergoes intense vibration. |
| title | Vibration-aware Lidar-Inertial Odometry based on Point-wise Post-Undistortion Uncertainty |
| topic | Robotics |
| url | https://arxiv.org/abs/2507.04311 |