Some reusable components of the system are available as a separate [header-only library](https://gitlab.com/VladyslavUsenko/basalt-headers) ([Documentation](https://vladyslavusenko.gitlab.io/basalt-headers/)).
* **Visual-Inertial Mapping with Non-Linear Factor Recovery**, V. Usenko, N. Demmel, D. Schubert, J. Stückler, D. Cremers, In IEEE Robotics and Automation Letters (RA-L) [[DOI:10.1109/LRA.2019.2961227]](https://doi.org/10.1109/LRA.2019.2961227) [[arXiv:1904.06504]](https://arxiv.org/abs/1904.06504).
* **The Double Sphere Camera Model**, V. Usenko and N. Demmel and D. Cremers, In 2018 International Conference on 3D Vision (3DV), [[DOI:10.1109/3DV.2018.00069]](https://doi.org/10.1109/3DV.2018.00069), [[arXiv:1807.08957]](https://arxiv.org/abs/1807.08957).
Calibration (demonstrates how these tools can be used for dataset calibration):
* **The TUM VI Benchmark for Evaluating Visual-Inertial Odometry**, D. Schubert, T. Goll, N. Demmel, V. Usenko, J. Stückler, D. Cremers, In 2018 International Conference on Intelligent Robots and Systems (IROS), [[DOI:10.1109/IROS.2018.8593419]](https://doi.org/10.1109/IROS.2018.8593419), [[arXiv:1804.06120]](https://arxiv.org/abs/1804.06120).
* **Efficient Derivative Computation for Cumulative B-Splines on Lie Groups**, C. Sommer, V. Usenko, D. Schubert, N. Demmel, D. Cremers, In 2020 Conference on Computer Vision and Pattern Recognition (CVPR), [[DOI:10.1109/CVPR42600.2020.01116]](https://doi.org/10.1109/CVPR42600.2020.01116), [[arXiv:1911.08860]](https://arxiv.org/abs/1911.08860).
Optimization (describes square-root optimization and marginalization used in VIO/VO):
* **Square Root Marginalization for Sliding-Window Bundle Adjustment**, N. Demmel, D. Schubert, C. Sommer, D. Cremers, V. Usenko, In 2021 International Conference on Computer Vision (ICCV), [[arXiv:2109.02182]](https://arxiv.org/abs/2109.02182)