# SR-LIO: LiDAR-Inertial Odometry with Sweep Reconstruction

arXiv: https://arxiv.org/abs/2210.10424 · HTML: https://mlsanity.com/paper/2210.10424/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Oct 2022.

## Built on by (most cited first, 7 of 7)

- [SR-LIVO: LiDAR-Inertial-Visual Odometry and Mapping with Sweep Reconstruction](https://mlsanity.com/paper/2312.16800/) (2023)
- [SVDC: Consistent Direct Time-of-Flight Video Depth Completion with Frequency Selective Fusion](https://mlsanity.com/paper/2503.01257/) (2025)
- [PriOr-Flow: Enhancing Primitive Panoramic Optical Flow with Orthogonal View](https://mlsanity.com/paper/2506.23897/) (2025)
- [Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual Odometry](https://mlsanity.com/paper/2412.16923/) (2024)
- [DEPTHOR: Depth Enhancement from a Practical Light-Weight dToF Sensor and RGB Image](https://mlsanity.com/paper/2504.01596/) (2025)
- [DEPTHOR++: Robust Depth Enhancement from a Real-World Lightweight dToF and RGB Guidance](https://mlsanity.com/paper/2509.26498/) (2025)
- [IFTD: Image Feature Triangle Descriptor for Loop Detection in Driving Scenes](https://mlsanity.com/paper/2406.07937/) (2024)

## Abstract (arXiv)

This paper proposes a novel LiDAR-Inertial odometry (LIO), named SR-LIO, based on an iterated extended Kalman filter (iEKF) framework. We adapt the sweep reconstruction method, which segments and reconstructs raw input sweeps from spinning LiDAR to obtain reconstructed sweeps with higher frequency. We found that such method can effectively reduce the time interval for each iterated state update, improving the state estimation accuracy and enabling the usage of iEKF framework for fusing high-frequency IMU and low-frequency LiDAR. To prevent inaccurate trajectory caused by multiple distortion correction to a particular point, we further propose to perform distortion correction for each segment. Experimental results on four public datasets demonstrate that our SR-LIO outperforms all existing state-of-the-art methods on accuracy, and reducing the time interval of iterated state update via the proposed sweep reconstruction can improve the accuracy and frequency of estimated states. The source code of SR-LIO is publicly available for the development of the community.