AM-Align: Globally Optimal Estimation of Accelerometer-Magnetometer Misalignment

AM-Align is a globally optimal method for solving the accelerometer-magnetometer(AM) alignment problem. The package provides a complete set of algorithms, including intrinsic calibration, making it a convenient solution for improving the accuracy and robustness of inertial navigation systems.

Intrinsic calibration	AM-Align

News

• 2024/03/22: Submitted as a Journal paper.
• 2024/03/20: Submitted to ICRA 2024 Workshop on Filed Robotics.

Features

• Globally optimal solution for accelerometer-magnetometer alignment
• Robust to insufficient and outlier-corrupted data
• Requires only four pairs of measurements for complete calibration
• Efficient and accurate computation using the polynomial eigenvalue technique

Prerequisites

• C++11 or newer
• CMake 3.10 or newer
• Eigen3

Installation

1. Clone the repository:

git clone https://github.com/JokerJohn/AM_Align

2. Build the project:

cd AM-Align
mkdir build && cd build
cmake ..
make

Usage

1. Prepare your accelerometer and magnetometer data in the required format.

2. Run the intrinsic calibration:

./am_align_calibration --acc_data /path/to/acc_data --mag_data /path/to/mag_data

3. Run the AM-Align alignment estimation:

./am_align --acc_data /path/to/calibrated_acc_data --mag_data /path/to/calibrated_mag_data

4. Integrate the estimated alignment into your LIO initialization process.

For more detailed usage instructions and examples, please refer to the documentation.

Contributing

We welcome contributions to AM-Align! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request. For major changes, please discuss them with the authors first.

Before contributing, please read our contributing guidelines and code of conduct.

License

AM-Align is released under the MIT License.

Citation

If you use AM-Align in your research, please cite our paper:

@article{xhu2024amalign,
  title={AM-Align: Globally Optimal Accelerometer-Magnetometer Alignment},
  author={Xiangcheng Hu*, Jin Wu*, Bohuan Xue, Yilong Zhu, Mingkai Jia, Yuhua Qi, Yi Jiang, Ping Tan and Wei Zhang},
  journal={arxiv},
  year={2024},
  publisher={arxiv}
}

Acknowledgments

We would like to thank the following authors for their contributions and support.

Contact

For questions, comments, or suggestions, please contact xhubd@connect.ust.hk.