Autonomous Underwater Vehicles in Extreme Environment

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (10 December 2021) | Viewed by 21527

Special Issue Editors


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Guest Editor
Southampton Business School, University of Southampton, Southampton SO17 1BJ, UK
Interests: autonomous underwater vehicles; risk; reliability; availability ; safety; probability modelling; simulation; artificial intelligence

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Guest Editor
Ocean and Naval Architectural Engineering. Memorial University of Newfoundland. 240 Prince Phillip Drive, 40 Arctic Ave, St. John's, NL A1B 3X7, Canada
Interests: autonomous underwater vehicles; simulation; oil spill response; marine pollution

Special Issue Information

Dear Colleagues,

Autonomous underwater vehicles are effective tools for many maritime applications, for example to support underwater pipe inspection, geological surveys, mine counter measures and many others. Most applications of autonomous underwater vehicles are in benign environments where the risks are known and well controlled. In recent years there has been an increase in the number of deployments of autonomous underwater systems in extreme environments, such as: under ice, at depths greater than 5000 metres or for oil spills contour mapping.

To improve the performance of these vehicles in extreme environments, researchers must develop novel methods to ensure safe operations of AUVs.

This special issue aims to publish novel solutions that enable AUV missions in extreme environments.

We will seek to publish the latest research in the following areas:

  • Mission planning and control
  • Structural models and structural analysis
  • Sensors operation regime for risk control
  • Power management and control
  • Communications management
  • Safety functions for risk control
  • Models for mission analysis
  • Multiple vehicle mission control and planning
  • Probabilistic and stochastic models for risk quantification
  • Condition monitoring systems
  • Policy and regulation

Developments in these fields will enable AUVs to be systematically deployed in extreme environments. To make the research relevant to the AUV community we encourage authors to use AUV data to evaluate proposed solutions.


Dr. Mario Brito
Dr. Worakanok Thanyamanta
Guest Editors

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Keywords

  • Mission planning and control
  • Structural models and structural analysis
  • Sensors operation regime for risk control
  • Power management and control
  • Communications management
  • Safety functions for risk control
  • Models for mission analysis
  • Multiple vehicle mission control and planning
  • Probabilistic and stochastic models for risk quantification
  • Condition monitoring systems
  • Policy and regulation

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Published Papers (5 papers)

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Research

17 pages, 6095 KiB  
Article
A Novel Multi-Robot Task Allocation Model in Marine Plastics Cleaning Based on Replicator Dynamics
by Le Hong, Weicheng Cui and Hao Chen
J. Mar. Sci. Eng. 2021, 9(8), 879; https://doi.org/10.3390/jmse9080879 - 14 Aug 2021
Cited by 7 | Viewed by 3672
Abstract
As marine plastic pollution threatens the marine ecosystem seriously, the government needs to find an effective way to clean marine plastics. Due to the advantages of easy operation and high efficiency, autonomous underwater vehicles (AUVs) have been applied to clean marine plastics. As [...] Read more.
As marine plastic pollution threatens the marine ecosystem seriously, the government needs to find an effective way to clean marine plastics. Due to the advantages of easy operation and high efficiency, autonomous underwater vehicles (AUVs) have been applied to clean marine plastics. As for the large-scale marine environment, the marine plastic cleaning task needs to be accomplished through the collaborative work of multiple AUVs. Assigning the cleaning task to each AUV reasonably and effectively has an essential impact on improving cleaning efficiency. The coordination of AUVs is subjected to harsh communication conditions. Therefore, to release the dependence on the underwater communications among AUVs, proposing a reliable multi-robot task allocation (MRTA) model is necessary. Inspired by the evolutionary game theory, this paper proposes a novel multi-robot task allocation (MRTA) model based on replicator dynamics for marine plastic cleaning. This novel model not only satisfies the minimization of the cost function, but also reaches a relatively stable state of the task allocation. A novel optimization algorithm, equilibrium optimizer (EO), is adopted as the optimizer. The simulation results validate the correctness of the results achieved by EO and the applicability of the proposed model. At last, several valuable conclusions are obtained from the simulations on the three different assumed AUVs. Full article
(This article belongs to the Special Issue Autonomous Underwater Vehicles in Extreme Environment)
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19 pages, 56094 KiB  
Article
A Backseat Control Architecture for a Slocum Glider
by Yaomei Wang, Craig Bulger, Worakanok Thanyamanta and Neil Bose
J. Mar. Sci. Eng. 2021, 9(5), 532; https://doi.org/10.3390/jmse9050532 - 15 May 2021
Cited by 8 | Viewed by 3807
Abstract
Adaptive sampling provides an innovative and favorable method of improving the effectiveness of underwater vehicles in collecting data. Adaptive sampling works by controlling an underwater vehicle by using measurements from sensors and states of the vehicle. A backseat driver system was developed in [...] Read more.
Adaptive sampling provides an innovative and favorable method of improving the effectiveness of underwater vehicles in collecting data. Adaptive sampling works by controlling an underwater vehicle by using measurements from sensors and states of the vehicle. A backseat driver system was developed in this work and installed on a Slocum glider to equip it with an ability to perform adaptive sampling tasks underwater. This backseat driver communicated with the main vehicle control system of the glider through a robot operating system (ROS) interface. The external control algorithms were implemented through ROS nodes, which subscribed simulated sensor measurements and states of the glider and published desired states to the glider. The glider was set up in simulation mode to test the performance of the backseat driver as integrated into the control architecture of the glider. Results from the tests revealed that the backseat driver could effectively instruct the depth, heading, and waypoints as well as activate or deactivate behaviors adaptively. The developed backseat driver will be tested in future field experiments with sensors included and safety rules implemented before being applied in adaptive sampling missions such as adaptive oil spill sampling. Full article
(This article belongs to the Special Issue Autonomous Underwater Vehicles in Extreme Environment)
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27 pages, 8552 KiB  
Article
Design and Testing of a Spherical Autonomous Underwater Vehicle for Shipwreck Interior Exploration
by Ross Eldred, Johnathan Lussier and Anthony Pollman
J. Mar. Sci. Eng. 2021, 9(3), 320; https://doi.org/10.3390/jmse9030320 - 14 Mar 2021
Cited by 15 | Viewed by 5719
Abstract
This article details the design, construction and implementation of a novel, spherical unmanned underwater vehicle (UUV) prototype for operations within confined, entanglement-prone marine environments. The nature of shipwreck interiors, the exploration of which the vehicle was originally designed, imposes special risks that constrain [...] Read more.
This article details the design, construction and implementation of a novel, spherical unmanned underwater vehicle (UUV) prototype for operations within confined, entanglement-prone marine environments. The nature of shipwreck interiors, the exploration of which the vehicle was originally designed, imposes special risks that constrain system requirements while promoting other attributes uncommon in typical open-water UUV designs. The invention, the Wreck Interior Exploration Vehicle (WIEVLE), was constructed using 3-D additive manufacturing technology combined with relatively inexpensive commercial components. Similar inventions are compared, followed by a thorough review of the physical and functional characteristics of the system. The key attributes of the design include a smooth, spherical hull with 360-degree sensor coverage, and a fixed, upward-angled thruster core, relying on inherent buoyancy to take the place of a dedicated depth-changing mechanism. Initial open-loop control testing demonstrated stable 4 degrees of freedom (DOF) maneuvering capability. The article concludes with an overview of the results of the initial testing, a review of how the key system design attributes address the unique shipwreck interior exploration challenges, and a plan for the future development of the platform. Full article
(This article belongs to the Special Issue Autonomous Underwater Vehicles in Extreme Environment)
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17 pages, 5106 KiB  
Article
Microbubbles as Proxies for Oil Spill Delineation in Field Tests
by Yaomei Wang, Worakanok Thanyamanta, Craig Bulger, Neil Bose and Jimin Hwang
J. Mar. Sci. Eng. 2021, 9(2), 126; https://doi.org/10.3390/jmse9020126 - 27 Jan 2021
Cited by 11 | Viewed by 3377
Abstract
To overcome the environmental impacts of releasing oil into the ocean for testing acoustic methods in field experiments using autonomous underwater vehicles (AUVs), environmentally friendly gas bubble plumes with low rise velocities are proposed in this research to be used as proxies for [...] Read more.
To overcome the environmental impacts of releasing oil into the ocean for testing acoustic methods in field experiments using autonomous underwater vehicles (AUVs), environmentally friendly gas bubble plumes with low rise velocities are proposed in this research to be used as proxies for oil. An experiment was conducted to test the performance of a centrifugal-type microbubble generator in generating microbubble plumes and their practicability to be used in field experiments. Sizes of bubbles were measured with a Laser In-Situ Scattering and Transmissometry sensor. Residence time of bubble plumes was estimated by using a Ping360 sonar. Results from the experiment showed that a larger number of small bubbles were found in deeper water as larger bubbles rose quickly to the surface without staying in the water column. The residence time of the generated bubble plumes at the depth of 0.5 m was estimated to be over 5 min. The microbubble generator is planned to be applied in future field experiments, as it is effective in producing relatively long-endurance plumes that can be used as potential proxies for oil plumes in field trials of AUVs for delineating oil spills. Full article
(This article belongs to the Special Issue Autonomous Underwater Vehicles in Extreme Environment)
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11 pages, 3496 KiB  
Article
Acoustic Search and Detection of Oil Plumes Using an Autonomous Underwater Vehicle
by Jimin Hwang, Neil Bose, Hung Duc Nguyen and Guy Williams
J. Mar. Sci. Eng. 2020, 8(8), 618; https://doi.org/10.3390/jmse8080618 - 17 Aug 2020
Cited by 18 | Viewed by 3325
Abstract
We introduce an adaptive sampling method that has been developed to support the Backseat Driver control architecture of the Memorial University of Newfoundland (MUN) Explorer autonomous underwater vehicle (AUV). The design is based on an acoustic detection and in-situ analysis program that allows [...] Read more.
We introduce an adaptive sampling method that has been developed to support the Backseat Driver control architecture of the Memorial University of Newfoundland (MUN) Explorer autonomous underwater vehicle (AUV). The design is based on an acoustic detection and in-situ analysis program that allows an AUV to perform automatic detection and autonomous tracking of an oil plume. The method contains acoustic image acquisition, autonomous triggering, and thresholding in the search stage. A new biomimetic search pattern, the bumblebee flight path, was designed to maximize the spatial coverage in the oil plume detection phase. The effectiveness of the developed algorithm was validated through simulations using a two-dimensional planar plume model and a 90-degree scanning sensor model. The results demonstrate that the bumblebee search design combined with a genetic solution for the Traveling Salesperson Problem outperformed a conventional lawnmower survey, reducing the AUV travel distance by up to 75.3%. Our plume detection strategy, using acoustic sensing, provided data of plume location, distribution, and density, over a sector in contrast with traditional chemical oil sensors that only provide readings at a point. Full article
(This article belongs to the Special Issue Autonomous Underwater Vehicles in Extreme Environment)
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