# Super-LIO
**Repository Path**: chluck2008/Super-LIO
## Basic Information
- **Project Name**: Super-LIO
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: ros2
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 1
- **Created**: 2026-05-16
- **Last Updated**: 2026-05-16
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
⚡Super-LIO
Super-LIO: A Robust and Efficient LiDAR-Inertial Odometry System with a Compact Mapping Strategy
This work has been accepted to IEEE Robotics and Automation Letters (RA-L 2026).
[](https://github.com/Liansheng-Wang/Super-LIO.git) [](https://arxiv.org/abs/2509.05723) [](https://ieeexplore.ieee.org/document/11347459) [](https://www.bilibili.com/video/BV11wBeBYEp6) [](https://youtu.be/m9-hl8s5DDw)
## Overview
**Key Features: Efficient · Robust · Cross-Platform Compatible · Supports Both ROS1/ROS2 Versions**
Super-LIO is a robust and efficient LiDAR–Inertial Odometry (LIO) system designed for real-time and large-scale autonomous navigation. It introduces a compact and structured mapping strategy that enables predictable correspondence search and stable state estimation. The system is validated through extensive real-world experiments and comparisons with state-of-the-art methods, which demonstrates that Super-LIO not only achieves **excellent accuracy** but also maintains **lower resource consumption** and realizes a nearly **1.2–4× higher real-time processing speed**⚡.
**Contributors**: [Liansheng Wang](https://github.com/Liansheng-Wang), [Xinke Zhang](https://github.com/PSQzzzxk), [Chenhui Li](https://github.com/kermitLHH), [Dongjiao He](https://github.com/Joanna-HE), [Yihan pan](https://github.com/pyh3552), Jianjun Yi.
## Quickly Run
**For ROS1 Users**: Please switch to the **ros1** branch and follow the instructions at [ros1 branch](https://github.com/Liansheng-Wang/Super-LIO/tree/ros1)
### Requirements
Ubuntu 24(22).04 · C++20 · ROS Jazzy(Humble) · Eigen · PCL
### Dependencies
glog · TBB
```bash
sudo apt install libgoogle-glog-dev libtbb-dev
```
### Build & Run
```bash
git clone https://github.com/Liansheng-Wang/Super-LIO.git
cd Super-LIO
colcon build
source install/setup.bash
ros2 launch super_lio Livox_mid360.py
```
#### 🔁 Relocalization Mode
Super-LIO supports relocalization using a pre-built map, allowing the system to resume localization from a saved map without restarting the mapping process.
This mode is useful for long-term deployment, repeated missions, or recovery after tracking loss.
Before running relocalization, please make sure that:
- A map has been previously saved to disk.
```bash
cd PATH_2_Super-LIO
source install/setup.bash
ros2 launch super_lio relocation.py
```
## Datasets
Super-LIO is evaluated on multiple real-world datasets covering diverse environments,
including indoor, outdoor, and large-scale scenes.
> **TODO**: Dataset download links and detailed descriptions will be provided in the future.
---
## Publications
If your like our projects, please cite us and support us with a star 🌟.
We kindly recommend to cite [our paper](https://ieeexplore.ieee.org/document/11347459) if you find this library useful:
```latex
@article{wang2026superlio,
title = {Super-LIO: A Robust and Efficient LiDAR-Inertial Odometry System with a Compact Mapping Strategy},
author = {Wang, Liansheng and Zhang, Xinke and Li, Chenhui and He, Dongjiao and Pan, Yihan and Yi, Jianjun},
journal = {IEEE Robotics and Automation Letters},
year = {2026},
volume = {11},
number = {3},
pages = {2666--2673},
doi = {10.1109/LRA.2026.3653372}
}
```
## Update Logs
Click to expand Update Logs (click to collapse)
- 2026-01-04
- Separate ROS interface and algorithm.
- Refactor SuperLIOReLoc to inherit from SuperLIO.
- Code style aligned with ROS2 version.
- 2026-01-04
- The main branch is renamed to ros1
- add ros2 branch
- 2026-01-04 21:51
- release ROS2 version