PeRL STUDIES AUTONOMOUS NAVIGATION & MAPPING FOR MOBILE ROBOTS IN A PRIORI UNKNOWN ENVIRONMENTS.
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Towards bathymetry-optimized Doppler re-navigation for AUVs
Summary
Abstract
This paper describes a terrain-aided re-navigation algorithm for autonomous underwater vehicles (AUVs) built around optimizing bottom-lock Doppler velocity log (DVL) track lines relative to a ship derived bathymetric map. The goal of this work is to improve the precision of AUV DVL-based navigation for near- seafloor science by removing the low-frequency "drift" associated with a dead-reckoned (DR) Doppler navigation methodology. To do this, we use the discrepancy between vehicle-derived vs. ship-derived acoustic bathymetry as a corrective error measure in a standard nonlinear optimization framework. The advantage of this re-navigation methodology is that it exploits existing ship-derived bathymetric maps to improve vehicle navigation without requiring additional infrastructure. We demonstrate our technique for a recent AUV survey of large-scale gas blowout features located along the U.S. Atlantic margin.
Bibtex entry
@INPROCEEDINGS { reustice-2005d,
AUTHOR = { Ryan Eustice and Richard Camilli and Hanumant Singh },
TITLE = { Towards bathymetry-optimized {Doppler} re-navigation for {AUVs} },
BOOKTITLE = { Proceedings of the IEEE/MTS OCEANS Conference and Exhibition },
YEAR = { 2005 },
MONTH = { September },
ADDRESS = { Washington, DC, USA },
PAGES = { 1430--1436 },
}