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Massachusetts Institute of Technology

Autonomous Underwater Vehicle (AUV) path planning and adaptive on-board routing for adaptive rapid environmental assessment

Abstract

dc:description.abstract

In shallow water, a large part of underwater acoustic prediction uncertainties are induced by sub-meso-to-small scale oceanographic variabilities. Conventional oceanographic measurements for capturing such ocean-acoustic environmental variabilities face the classical conflict between resolution and coverage. The Adaptive Rapid Environmental Assessment (AREA) project was proposed to resolve this conflict by optimizing the location of in-situ measurements in an adaptive manner. In this thesis, ideas, concepts and performance limits in AREA are clarified. Both an engineering and a mathematical model for AREA are developed. A modularized AREA simulator was developed and implemented in C++. Philosophies in AREA are discussed. Presumptions about the ocean are made to bridge the gap between the viewpoint in the oceanography community, where the ocean environment is considered to be a deterministic but very complicated system, and that of the underwater acoustic community, where the ocean environment is treated as a random system. At present, how to optimally locate the in-situ measurements made by a single AUV carrying a CTD (conductivity, temperature and depth) sensor is considered in AREA. In this thesis, the AUV path planning is modeled as a Shortest Path problem. However, due to the sound velocity correlation effect, the size of this problem can be very large. A method is developed to simplify the graph for a fast solution. As a significant step, a linear approximation for acoustic Transmission Loss (TL) is investigated numerically and analytically. In addition to following a predetermined path, an AUV can also adaptively generate its path on-board. This adaptive on-board AUV routing problem is modeled using Dynamic Programming (DP) in this thesis.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Mechanical Engineering.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2007

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Wang, Ding, Ph. D. Massachusetts Institute of Technology
Advisor dc:contributor.advisor
  • Henrik Schmidt and Pierre Lermusiaux.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/42292
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/42292

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Wang, Ding, Ph. D. Massachusetts Institute of Technology. Autonomous Underwater Vehicle (AUV) path planning and adaptive on-board routing for adaptive rapid environmental assessment. Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42292