# Stereo Visual Inertial LiDAR Simultaneous Localization and Mapping

arXiv: https://arxiv.org/abs/1902.10741 · HTML: https://mlsanity.com/paper/1902.10741/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Feb 2019.

## Built on by (most cited first, 8 of 8)

- [R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package](https://mlsanity.com/paper/2109.07982/) (2021)
- [FAST-LIVO2: Fast, Direct LiDAR-Inertial-Visual Odometry](https://mlsanity.com/paper/2408.14035/) (2024)
- [Milestones in Autonomous Driving and Intelligent Vehicles Part II: Perception and Planning](https://mlsanity.com/paper/2306.01980/) (2023)
- [SR-LIVO: LiDAR-Inertial-Visual Odometry and Mapping with Sweep Reconstruction](https://mlsanity.com/paper/2312.16800/) (2023)
- [Edge Robotics: Edge-Computing-Accelerated Multi-Robot Simultaneous Localization and Mapping](https://mlsanity.com/paper/2112.13222/) (2021)
- [R3LIVE++: A Robust, Real-time, Radiance reconstruction package with a tightly-coupled LiDAR-Inertial-Visual state Estimator](https://mlsanity.com/paper/2209.03666/) (2022)
- [LiVisSfM: Accurate and Robust Structure-from-Motion with LiDAR and Visual Cues](https://mlsanity.com/paper/2410.22213/) (2024)
- [SmartDepthSync: Open Source Synchronized Video Recording System of Smartphone RGB and Depth Camera Range Image Frames with Sub-millisecond Precision](https://mlsanity.com/paper/2111.03552/) (2021)

## Abstract (arXiv)

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.