Optimal depth navigation algorithm for reducing energy consumption in a multi-pass or multi-AUV framework using aggregated acoustic doppler current profiler data: a thesis in Computer and Information Science

Wesley I. Fowlks

doi:10.62791/19960

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Optimal depth navigation algorithm for reducing energy consumption in a multi-pass or multi-AUV framework using aggregated acoustic doppler current profiler data: a thesis in Computer and Information Science

Thesis

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Optimal depth navigation algorithm for reducing energy consumption in a multi-pass or multi-AUV framework using aggregated acoustic doppler current profiler data: a thesis in Computer and Information Science

Wesley I. Fowlks

Master of Science (MS), University of Massachusetts Dartmouth

2018

DOI:

https://doi.org/10.62791/19960

Abstract

Oceanographic submersibles.

Autonomous vehicles.

Remote submersibles.

Autonomous Underwater Vehicles (AUVs) are growing in application and demand, however one of the main limiting factors of AUVs is power consumption, which can vary based on behavioral changes. The focus of this project is to develop a behavioral algorithm for the vehicle to utilize the positive and negative water currents in the environment to reduce power consumption. When making multiple passes of an area or when multiple AUVs communicate, they are able to use the water current profile to adjust their travel depth and reduce power consumption.

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Title: Optimal depth navigation algorithm for reducing energy consumption in a multi-pass or multi-AUV framework using aggregated acoustic doppler current profiler data
Creators: Wesley I. Fowlks
ORCID: 0000-0001-8338-9645
Contributors: Ramprasad Balasubramanian (Advisor) - University of Massachusetts Dartmouth, Office of the Provost
Haiping Xu (Committee Member) - University of Massachusetts Dartmouth, Department of Computer and Information Science
Jan Bergandy (Committee Member) - University of Massachusetts Dartmouth
Number of pages: xi, 85 pages
Illustrations: illustrations
Table of contents: Chapter 1 : Introduction -- Chapter 2 : Motivation and background. Purpose ; Problem statement ; Thesis focus ; Acoustic doppler current profiler and doppler velocity log ; Backseat driver architecture ; Mission oriented operating suite -- Chapter 3 : Previous work. Overview ; Shipboard ADCP ; Portable ADCP ; Image processing of DVL data -- Chapter 4 : Methodology. Overview ; Image processing ; Depth utility computation ; Speed of the second AUV ; Battery model -- Chapter 5 : Results. Datasets ; Synthetic dataset ; Real datasets ; Conclusion and future work -- Appendix -- References.
References: Includes bibliographical references (page 85).
Awarding Institution: University of Massachusetts Dartmouth
Degree Awarded: Master of Science (MS)
Degree in: Computer and Information Science
Academic Unit: Department of Computer and Information Science
Language: English
Resource Type: Thesis
DOI: https://doi.org/10.62791/19960
Record Identifier: 9914424891101301