AUG Mapping: Ice and Bathymetric Mapping with an Autonomous Underwater Glider

preview photo with ice
Code Data

Abstract

Georeferenced subsurface survey is primarily conducted by autonomous underwater vehicles and remotely operated vehicles that require power-intensive navigation suites, acoustic beacons, and surface support vessels with attendant operations teams onboard. The significant infrastructure required to operate vehicles conducting surveys in remote regions (e.g., under ice) poses increased challenges and remains prohibitively costly, leading to sparse coverage. Unattended operations using autonomous underwater gliders (AUGs) with low power, high-resolution onboard navigation holds promise in scaling up coverage while significantly reducing the operational costs of georeferenced surveys. In this work, we present a modified AUG equipped with a low power embedded navigation process and results of unattended sonar acoustic surveys using this experimental platform.



[1] (PDF) Phung, A., Billings, G., Burgess, G., & Camilli, R. (2025). An autonomous underwater glider with improved onboard navigation for unattended mapping. IEEE Journal of Oceanic Engineering.

[2] (PDF) Phung, A., Billings, G., Maksym, T., & Camilli, R. (2025, June). Automated Ice Detection for Autonomous Underwater Gliders. In OCEANS 2025 Brest (pp. 1-5). IEEE.

[3] (PDF) Billings, G., Phung, A., & Camilli, R. (2025, June). DVL Integration with Autonomous Underwater Gliders for Navigation in Arctic Marginal Ice Zones. In OCEANS 2025 Brest (pp. 1-6). IEEE.

[4] (PDF) Billings, G., Phung, A., & Camilli, R. (2023, October). DVL-based odometry for autonomous underwater gliders. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 9910-9917). IEEE.



This work aims to enable small, low-power autonomous underwater gliders (AUGs) to complete unattended georeferenced surveys which are typically conducted by larger, power-intensive AUVs with surface support vessels.

vision

[3-4] Focuses on the development of a DVL-odometry method to improve subsurface localization. This method uses the bottom-lock velocity estimates and water column current velocity estimates to improve localization over dead reckoning alone.

dvl-odo visualization

[1] Focuses on the development of a frontseat-backseat onboard architecture to improve vehicle navigation, which enables the DVL-odometry localization estimate to steer the glider's frontseat computer towards waypoints.

waypoint following visualization

[1] Field deployments in Puerto Rico were used to validate our subsurface localization estimates. Our measured bathymetry aligns with aerial LiDAR data, which is available in the region due to its shallow and optically clear waters.

puerto rico dataset overview puerto rico results

[2] A mechanically scanned imaging sonar (MSIS) mounted in the glider's nosecone enabled ice detection capabilities, which improves robustness when operating in ice-covered regions.

ice detection method visualization

[1-2] During field deployments in the Arctic marginal ice zone, the frontseat-backseat architecture and DVL-Odometry method enabled simultaneous ice and bathymetric mapping.

alaska dataset overview alaska dataset overview

BibTeX

@article{phung2025autonomous,
  title={An autonomous underwater glider with improved onboard navigation for unattended mapping},
  author={Phung, Amy and Billings, Gideon and Burgess, Gregory and Camilli, Richard},
  journal={IEEE Journal of Oceanic Engineering},
  year={2025},
  publisher={IEEE}
}

@inproceedings{phung2025automated,
  title={Automated Ice Detection for Autonomous Underwater Gliders},
  author={Phung, Amy and Billings, Gideon and Maksym, Ted and Camilli, Richard},
  booktitle={OCEANS 2025 Brest},
  pages={1--5},
  year={2025},
  organization={IEEE}
}

@inproceedings{billings2025dvl,
  title={DVL Integration with Autonomous Underwater Gliders for Navigation in Arctic Marginal Ice Zones},
  author={Billings, Gideon and Phung, Amy and Camilli, Richard},
  booktitle={OCEANS 2025 Brest},
  pages={1--6},
  year={2025},
  organization={IEEE}
}

@inproceedings{billings2023dvl,
  title={Dvl-based odometry for autonomous underwater gliders},
  author={Billings, Gideon and Phung, Amy and Camilli, Richard},
  booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages={9910--9917},
  year={2023},
  organization={IEEE}
}