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ASV-aided AUV navigation: A field study on nonlinear estimation for localization of low-cost, scalable systems
Citation Link: https://doi.org/10.15480/882.16475
Publikationstyp
Conference Paper
Date Issued
2025-11-27
Sprache
English
Author(s)
TORE-DOI
Citation
IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2025
Contribution to Conference
Publisher DOI
Publisher
IEEE Xplore
ISBN
979-8-3315-4393-8
This work investigates the use of multiple Autonomous Surface Vehicles (ASVs) as Communication/Navigation Aids (CNAs) to enhance the navigation and state estimation of an Autonomous Underwater Vehicle (AUV). Our approach builds on recent advancements in low-cost sensors and platforms, which enable novel AUV applications across fundamental science, commercial industries, and defense. We consider six different combinations of Kalman Filter and Factor Graph localization solutions on three datasets, covering 53 minutes and 3.1 kilometers of operation. We first present the solution using the measurements from all three ASVs, before occluding measurements from two of the ASVs to assess the effect of reduced observability on localization performance.
DDC Class
629.892: Robot
623.8: Naval Architecture; Shipbuilding
621.38: Electronics, Communications Engineering
Publication version
publishedVersion
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Name
ASV-Aided_AUV_Navigation_A_Field_Study_on_Nonlinear_Estimation_for_Localization_of_Low-Cost_Scalable_Systems.pdf
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4.4 MB
Format
Adobe PDF