Modular Multi-Sensor Fusion for Underwater Localization for Autonomous ROV Operations

Authors:
Martin Scheiber, Alexandre Cardaillac, Christian Brommer, Stephan Weiss and Martin Ludvigsen
Publisher:
IEEE OCEANS22
Year:

This article discusses the challenges of localization filters for underwater vehicles and presents the Modular and Robust Sensor-Fusion Framework (MaRS) as a solution. MaRS is extended to work with underwater vehicles and their environment and allows efficient use of asynchronous sensors, handles measurement outliers and outages, and includes sensor-frame initialization and online extrinsic calibration methods. Tests using a small remotely operated vehicle (ROV) show improved handling of sensors and state estimation results in real harbor-like environments.

Citation

Citation key:
Scheiber2022Oceans

BibTeX

@inproceedings{Scheiber2022Oceans,
  title = {Modular Multi-Sensor Fusion for Underwater Localization for Autonomous ROV Operations},
  url = {http://dx.doi.org/10.1109/OCEANS47191.2022.9977298},
  DOI = {10.1109/oceans47191.2022.9977298},
  booktitle = {OCEANS 2022, Hampton Roads},
  publisher = {IEEE},
  author = {Scheiber, Martin and Cardaillac, Alexandre and Brommer, Christian and Weiss, Stephan and Ludvigsen, Martin},
  year = {2022},
  month = Oct,
  pages = {1–5}
}