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# GVINS

GVINS: Tightly Coupled GNSS-Visual-Inertial Fusion for Smooth and Consistent State Estimation. [paper link]( Shaozu CAO, Xiuyuan LU and Shaojie SHEN


**GVINS** is a non-linear optimization based system that tightly fuses GNSS raw measurements with visual and inertial information for real-time and drift-free state estimation. By incorporating GNSS pseudorange and Doppler shift measurements, GVINS is capable to provide smooth and consistent 6-DoF global localization in complex environment. The system framework and VIO part are adapted from [VINS-Mono]( Our system contains the following features:

- global 6-DoF estimation in ECEF frame;

- multi-constellation support (GPS, GLONASS, Galileo, BeiDou);

- online local-ENU frame alignment;

- global pose recovery in GNSS-unfriendly or even GNSS-denied area.

**Video:**

[![GVINS Video]( "GVINS Video")

## 1. Prerequisites

### 1.1 C++11 Compiler

This package requires some features of C++11.

### 1.2 ROS

This package is developed under [ROS Kinetic]( environment.

### 1.3 Eigen

Our code uses [Eigen 3.3.3]( for matrix manipulation.

### 1.4 Ceres

We use [ceres]( 1.12.0 to solve the non-linear optimization problem.

### 1.5 gnss_comm

This package also requires [gnss_comm]( for ROS message definitions and some utility functions. Follow [those instructions]( to build the *gnss_comm* package.

## 2. Build GVINS

Clone the repository to your catkin workspace (for example `~/catkin_ws/`):

```

cd ~/catkin_ws/src/

git clone build the package with:

```

cd ~/catkin_ws/

catkin_make

source ~/catkin_ws/devel/setup.bash

```

If you encounter any problem during the building of GVINS, we recommend you to [try docker](#docker_section) first.

## 3. <a name="docker_section"></a>Docker Support

To simplify the building process, we add docker in our code. Docker is like a sandbox so it can isolate our code from your local environment. To run with docker, first make sure [ros]( and [docker]( are installed on your machine. Then add your account to `docker` group by `sudo usermod -aG docker $USER`. **Logout and re-login to avoid the *Permission denied* error**, then type:

```

cd ~/catkin_ws/src/GVINS/docker

make build

```

The docker image `gvins:latest` should be successfully built after a while. Then you can run GVINS with:

```

./run.sh LAUNCH_FILE

``` 

(for example `./run.sh visensor_f9p.launch`). Open another terminal and play your rosbag file, then you should be able to see the result. If you modify the code, simply re-run `./run.sh LAUNCH_FILE` to update.

## 4. Run GVINS with our dataset

Download our [GVINS-Dataset]( and launch GVINS via:

```

roslaunch gvins visensor_f9p.launch

```

Open another terminal and launch the rviz by:

```

rviz -d ~/catkin_ws/src/GVINS/config/gvins_rviz_config.rviz

```

Then play the bag:

```

rosbag play sports_field.bag

```

## 5. Run GVINS with your device

1. Setup the visual-inertial sensor suit according to [these instructions]( Configure your GNSS receiver to output raw measurement and ephemeris and convert them as ros messages. If you are using u-blox receiver, please checkout our [ublox_driver]( package;

3. Deal with the synchronization between visual-inertial sensor and GNSS receiver. A coarse synchronization can be done via [ublox_driver]( but the accuracy is not guaranteed. For better performance, we recommend hardware synchronization via receiver's PPS signal;

4. Change the topic name in the config file and create a launch file pointing to the corresponding config file. Launch the GVINS with `roslaunch gvins YOUR_LAUNCH_FILE.launch`.

## 6. Acknowledgements

The system framework and VIO part are adapted from [VINS-Mono]( We use [camodocal]( for camera modelling and [ceres]( to solve the optimization problem.

## 7. Licence

The source code is released under [GPLv3]( license.