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Cooperative Localization and Bathyme...

Rui, Gao.

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Cooperative Localization and Bathymetry-Aided Navigation of Autonomous Marine Systems.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Cooperative Localization and Bathymetry-Aided Navigation of Autonomous Marine Systems./
作者:	Rui, Gao.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	197 p.
附註:	Source: Dissertations Abstracts International, Volume: 81-11, Section: B.
Contained By:	Dissertations Abstracts International81-11B.
標題:	Ocean engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27988176
ISBN:	9798641902586

Cooperative Localization and Bathymetry-Aided Navigation of Autonomous Marine Systems.
Rui, Gao.

Cooperative Localization and Bathymetry-Aided Navigation of Autonomous Marine Systems. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 197 p.

Source: Dissertations Abstracts International, Volume: 81-11, Section: B.

Thesis (Ph.D.)--National University of Singapore (Singapore), 2019.

This item must not be sold to any third party vendors.

In monitoring and surveillance, localization and navigation is especially important for underwater autonomous vehicles (AUVs) since GPS and radio signals are not accessible in most of the missions. A cooperative team formed by multiple autonomous vehicles has gained increasing interests as it offers more efficiency and reliability than a single vehicle. Much work has been done in the area of underwater localization and navigation with the aids from beacons with known positions. This dissertation focuses on a team of low-cost AUVs where no one has precise position. With the ability to communicate and make relative measurements from each other, vehicles share information across the team and cooperate to complete complex missions. The information shared among vehicles helps improve the overall performance. However, unlike terrestrial communication links, underwater acoustic channel has inherent constraints such as high latency, limited bandwidth and low reliability. In such a case, a distributed processing architecture with minimum inter-vehicle communications is preferred. At the same time, the severe underwater communication issues also impose challenges on the distributed processing. We show the benefit introduced through cooperation and the issue imposed by communication constraints on the distributed processing. We propose a feasible design of the distributed localization for a team of cooperative AUVs. The algorithm is robust to packet loss, outperforms single-vehicle localization and requires minimum communications. In the next step, we look at a simplified naive assumption in underwater multi-sensor tracking and multi-vehicle localization. This assumption naively assumes information from different sources are independent of each Summary viii other. We justify the assumption and answer when the assumption is good to use. With the justification, we move on to single-vehicle bathymetry-aided navigation as it can be safely extended to cooperative multi-vehicle navigation with bathymetric aids. Bathymetry map indicating the water depth offers an attractive tool to reduce the localization error of the submerged vehicles. With bathymetric measurements incorporated, we study the a posteriori description of the localization uncertainty using probabilistic methods. An information theoretical approach is used to describe the localization uncertainty. With this information theory measure, we build information entropy map and demonstrate how the bathymetry helps with different localization priors. Subsequently, a bathymetry-aided navigation is proposed to ensure a good localization at the destination. We formulate the path planning and solve it as an optimization problem. The algorithm is tested using real-world bathymetric data. Simulations show that near-optimal paths with good localization accuracy at the destination are generated within a few iterations.

ISBN: 9798641902586Subjects--Topical Terms:

660731
Ocean engineering.
Subjects--Index Terms:

Underwater autonomous vehicles

Cooperative Localization and Bathymetry-Aided Navigation of Autonomous Marine Systems.
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520 $a In monitoring and surveillance, localization and navigation is especially important for underwater autonomous vehicles (AUVs) since GPS and radio signals are not accessible in most of the missions. A cooperative team formed by multiple autonomous vehicles has gained increasing interests as it offers more efficiency and reliability than a single vehicle. Much work has been done in the area of underwater localization and navigation with the aids from beacons with known positions. This dissertation focuses on a team of low-cost AUVs where no one has precise position. With the ability to communicate and make relative measurements from each other, vehicles share information across the team and cooperate to complete complex missions. The information shared among vehicles helps improve the overall performance. However, unlike terrestrial communication links, underwater acoustic channel has inherent constraints such as high latency, limited bandwidth and low reliability. In such a case, a distributed processing architecture with minimum inter-vehicle communications is preferred. At the same time, the severe underwater communication issues also impose challenges on the distributed processing. We show the benefit introduced through cooperation and the issue imposed by communication constraints on the distributed processing. We propose a feasible design of the distributed localization for a team of cooperative AUVs. The algorithm is robust to packet loss, outperforms single-vehicle localization and requires minimum communications. In the next step, we look at a simplified naive assumption in underwater multi-sensor tracking and multi-vehicle localization. This assumption naively assumes information from different sources are independent of each Summary viii other. We justify the assumption and answer when the assumption is good to use. With the justification, we move on to single-vehicle bathymetry-aided navigation as it can be safely extended to cooperative multi-vehicle navigation with bathymetric aids. Bathymetry map indicating the water depth offers an attractive tool to reduce the localization error of the submerged vehicles. With bathymetric measurements incorporated, we study the a posteriori description of the localization uncertainty using probabilistic methods. An information theoretical approach is used to describe the localization uncertainty. With this information theory measure, we build information entropy map and demonstrate how the bathymetry helps with different localization priors. Subsequently, a bathymetry-aided navigation is proposed to ensure a good localization at the destination. We formulate the path planning and solve it as an optimization problem. The algorithm is tested using real-world bathymetric data. Simulations show that near-optimal paths with good localization accuracy at the destination are generated within a few iterations.
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