# Rover-SLAM

**Repository Path**: haithink/rover-slam

## Basic Information

- **Project Name**: Rover-SLAM
- **Description**: 单独Rover-SLAM中的lightGlue模型
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 2
- **Forks**: 0
- **Created**: 2025-03-19
- **Last Updated**: 2025-10-27

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# A real-time, robust and versatile visual-SLAM framework based on deep learning networks

# Prerequisites
We have tested the library in **Ubuntu 20.04**, with the following hardware and software configurations:

- **CPU**: Intel Core i7-10700K
- **GPU**: NVIDIA GeForce RTX 3080
- **CUDA Version**: 11.8



## Pangolin
We use [Pangolin](https://github.com/stevenlovegrove/Pangolin) for visualization and user interface. Dowload and install instructions can be found at: https://github.com/stevenlovegrove/Pangolin.

## OpenCV
**Required at leat 3.0. Tested with OpenCV 3.4.1**.

## Eigen3
Required by g2o (see below). Download and install instructions can be found at: http://eigen.tuxfamily.org. **Required at least 3.1.0**.

## ONNXRuntime
**Required onnxruntime-linux-x64-gpu-1.16.3** and Modify line 63 of the CmakeLists.txt to the current location of ONNXRuntime library.


## ROS (optional)

We provide some examples to process input of a monocular, monocular-inertial, stereo, stereo-inertial or RGB-D camera using ROS. Building these examples is optional. These have been tested with ROS Melodic under Ubuntu 18.04.



## Download Examples Folder
Download ["Examples" ](https://pan.baidu.com/s/1dd6k_Gf8mEjbiyli31_Yeg?pwd=p5y8) and unzip in ROVER-SLAM/ .

## Download Dbow File
Download ["voc_binary_tartan_8u_6.zip"](https://pan.baidu.com/s/1dd6k_Gf8mEjbiyli31_Yeg?pwd=p5y8), and unzip in ROVER-SLAM/Vocabulary/ .

# Building Rover-SLAM library and examples

Clone the repository:
```
git clone https://github.com/zzzzxxxx111/Rover-SLAM.git
```


```
cd Rover-slam
mkdir build
cd build
cmake ..
make -j12
```


# Running 

## Euroc-Monocluar:
```
./Examples/Monocular/mono_euroc  Vocabulary/voc_binary_tartan_8u_6.yml.gz Examples/Monocular/EuRoC.yaml /media/xiao/data3/slamdataset/euroc/V202 /media/xiao/data3/learning-slam/Rover-slam/Examples/Monocular/EuRoC_TimeStamps/V202.txt
```

## Euroc-Monocluar-Inerial:

```
./Examples/Monocular-Inertial/mono_inertial_euroc  Vocabulary/voc_binary_tartan_8u_6.yml.gz Examples/Monocular-Inertial/EuRoC.yaml /media/xiao/data3/slamdataset/euroc/V203 media/xiao/data3/learning-slam/Rover-slam/Examples/Monocular-Inertial/EuRoC_TimeStamps/V203.txt
```



## TUM-Monocular-Inertial

```
./Examples/Monocular-Inertial/mono_inertial_tum_vi Vocabulary/voc_binary_tartan_8u_6.yml.gz Examples/Monocular-Inertial/TUM_512.yaml /media/xiao/data3/slamdataset/dataset-corridor3_512_16/mav0/cam0/data Examples/Monocular-Inertial/TUM_TimeStamps/dataset-corridor3_512.txt Examples/Monocular-Inertial/TUM_IMU/dataset-corridor3_512.txt dataset-corridor3_512_monoi
```
## Euroc-Stereo-Inertial

```
 ./Examples/Stereo-Inertial/stereo_inertial_euroc /media/xiao/data3/learning-slam/ORB_SLAM3_detailed_comments/Vocabulary/voc_binary_tartan_8u_6.yml.gz Examples/Stereo-Inertial/EuRoC.yaml /media/xiao/data3/slamdataset/euroc/V203 /media/xiao/data3/learning-slam/ORB_SLAM3_detailed_comments/Examples/Stereo/EuRoC_TimeStamps/V203.txt V203_si
```      
The rest of the operations are the same as ORB-SLAM3



# Acknowledgments

The completion of this project would not have been possible without the support and contributions of the following open-source projects and tools. We extend our sincere gratitude to:

1. **ORB-SLAM3**  
   

2. **AIRVO**  
  

3. **SP-Loop**  

4. **ORB_SLAM3_detailed_comments**  

5. **SuperPoint_SLAM**