We open-source OB_GINS, an optimization-based GNSS/INS integrated navigation system. The main features of OB_GINS are as follows:
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A sliding-window optimizer for GNSS/INS integration;
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Abstract IMU-preintegration implementation, including:
- The normal IMU preintegration without the Earth's rotation consideration;
- The normal IMU/ODO preintegration;
- The refined IMU preintegration with the Earth's rotation consideration;
- The refined IMU/ODO preintegration;
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Implementation of the marginalization;
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Tools for attitude parameterization and coordinate frames;
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Tools for file IO;
Authors: Hailiang Tang, Xiaoji Niu, and Tisheng Zhang from the Integrated and Intelligent Navigation (i2Nav) Group, Wuhan University.
Related Paper:
- Hailiang Tang, Xiaoji Niu, Tisheng Zhang, Jing Fan, and Jingnan Liu, “Exploring the Accuracy Potential of IMU Preintegration in Factor Graph Optimization,” Sep. 2021, Accessed: Sep. 08, 2021. [Online]. Available: https://arxiv.org/abs/2109.03010v1.
- Le Chang, Xiaoji Niu, and Tianyi Liu, “GNSS/IMU/ODO/LiDAR-SLAM Integrated Navigation System Using IMU/ODO Pre-Integration,” Sensors, vol. 20, no. 17, p. 4702, Aug. 2020, doi: 10.3390/s20174702.
- Junxiang Jiang, Xiaoji Niu, and Jingnan Liu, “Improved IMU Preintegration with Gravity Change and Earth Rotation for Optimization-Based GNSS/VINS,” Remote Sensing, vol. 12, no. 18, p. 3048, Sep. 2020, doi: 10.3390/rs12183048.
We recommend you use Ubuntu 18.04 or Ubuntu 20.04 with the newest compiler (gcc>=8.0 or clang>=6.0).
Follow Ceres installation instructions.
Follow abseil-cpp installation instructions.
sudo apt install libeigen3-dev
sudo apt install libyaml-cpp-dev
Once the prerequisites have been installed, you can clone this repository and build OB_GINS as follows:
# Clone the repository
git clone https://github.com/i2Nav-WHU/OB_GINS.git ~/
# Build OB_GINS
cd ~/OB_GINS
mkdir build && cd build
cmake ../ -DCAMKE_BUILD_TYPE=Release
make -j8
# Run demo dataset
cd ~/OB_GINS
./bin/ob_gins ./dataset/ob_gins.yaml
# Wait until the program finish
We offer a demo dataset with configuration file, which are located at dataset directory.
One can find our open-source datasets at awesome-gins-datasets.
The data formats used in OB_GINS are the same as the formats defined at awesome-gins-datasets. You can follow the formats to prepare your own datasets, or you can modify the source code as you need.
We thanks VINS-Fusion for providing a excellent platform for SLAM learners.
The source code is released under GPLv3 license.
We are still working on improving the code reliability. For any technical issues, please contact Hailiang Tang (thl@whu.edu.cn) or open an issue at this repository.
For commercial usage, please contact Prof. Xiaoji Niu (xjniu@whu.edu.cn).