AN INTEGRATED SIMULATION APPROACH FOR AUV IMAGE-BASED SLAM NAVIGATION

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Authors
Figueroa, Jesus
Subjects
SLAM
iSAM2
USBL
AUV
Advisors
Horner, Douglas P.
Date of Issue
2021-12
Date
Publisher
Monterey, CA; Naval Postgraduate School
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Abstract
This thesis develops a simulation framework for undersea feature-based navigation. Using an autonomous underwater vehicle (AUV) to locate an item of interest on the seafloor is a capability that would greatly benefit the Navy. AUVs provide a gateway toward removing the workforce requirement; however, they are still costly both in acquisition and maintenance. A solution to this problem is using two AUVs, one with increased capability and charged with finding and marking seafloor items with a beacon. An expendable AUV outfitted with cost-effective sensors would relocate, identify and neutralize the threat. Using undersea imaging to correlate seafloor images to an a priori image mosaic together with a ultra short baseline (USBL) beacon allows the AUV to complete challenging mission objectives without traditional navigation systems. Incremental Smoothing and Mapping 2 (iSAM2) is a Simultaneous Localization and Mapping (SLAM) technique that can be used by the AUV for position localization and is an appropriate technique, with image and USBL sensing, for real-time navigation operations. A simulation framework provides the ability to evaluate an AUV's performance while minimizing the risk of real-world operations. The framework is composed of a software architecture that allows for testing using the same software applied in real-world operations. This thesis demonstrates this framework and provides analysis for its usability for image-based SLAM.
Type
Thesis
Description
Series/Report No
Department
Mechanical and Aerospace Engineering (MAE)
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NPS Report Number
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Distribution Statement
Approved for public release. Distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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