Autosub Long Range 6000: A Multiple-Month Endurance AUV for Deep-Ocean Monitoring and Survey

Roper, Daniel; Harris, Catherine A.; Salavasidis, Georgios; Pebody, Miles; Templeton, Robert; Prampart, Thomas; Kingsland, Matthew; Morrison, R. I. Guy; Furlong, Maaten; Phillips, Alexander B.; McPhail, S.D.

doi:10.1109/joe.2021.3058416

Cited by 34 publications

(4 citation statements)

References 29 publications

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“…The AUTOSUB Long Range 1500, which is being designed, built, and operated by the National Oceanography Center, is a highly capable AUV with the potential of providing measurements that would have been previously impossible to collect, therefore allowing key advances in marine ecology studies. This vehicle will be built to be able to reach a depth of 1500 m [70,71].…”

Section: Umv In Air Water Surfacementioning

confidence: 99%

Management and Sustainable Exploitation of Marine Environments through Smart Monitoring and Automation

Glaviano

Esposito

Cosmo

et al. 2022

JMSE

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Monitoring of aquatic ecosystems has been historically accomplished by intensive campaigns of direct measurements (by probes and other boat instruments) and indirect extensive methods such as aero-photogrammetry and satellite detection. These measurements characterized the research in the last century, with significant but limited improvements within those technological boundaries. The newest advances in the field of smart devices and increased networking capabilities provided by emerging tools, such as the Internet of Things (IoT), offer increasing opportunities to provide accurate and precise measurements over larger areas. These perspectives also correspond to an increasing need to promptly respond to frequent catastrophic impacts produced by drilling stations and intense transportation activities of dangerous materials over ocean routes. The shape of coastal ecosystems continuously varies due to increasing anthropic activities and climatic changes, aside from touristic activities, industrial impacts, and conservation practices. Smart buoy networks (SBNs), autonomous underwater vehicles (AUVs), and multi-sensor microsystems (MSMs) such as smart cable water (SCW) are able to learn specific patterns of ecological conditions, along with electronic “noses”, permitting them to set innovative low-cost monitoring stations reacting in real time to the signals of marine environments by autonomously adapting their monitoring programs and eventually sending alarm messages to prompt human intervention. These opportunities, according to multimodal scenarios, are dramatically changing both the coastal monitoring operations and the investigations over large oceanic areas by yielding huge amounts of information and partially computing them in order to provide intelligent responses. However, the major effects of these tools on the management of marine environments are still to be realized, and they are likely to become evident in the next decade. In this review, we examined from an ecological perspective the most striking innovations applied by various research groups around the world and analyzed their advantages and limits to depict scenarios of monitoring activities made possible for the next decade.

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Section: Umv In Air Water Surfacementioning

confidence: 99%

Management and Sustainable Exploitation of Marine Environments through Smart Monitoring and Automation

Glaviano

Esposito

Cosmo

et al. 2022

JMSE

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“…For the HUGIN AUV (Figure 4) equipped with chemical sensors and a SAS system, area coverage rates are estimated to be in the order of 2 km 2 /h. AUV-related research efforts are currently directed toward improved vehicle autonomy, including the ability for the vehicle to actively adapt to its environment [52,53] and endurance [54,55], as well as on solutions with resident AUVs able to re-charge their batteries using subsea docking stations [56] or wireless charging systems [57].…”

Section: Autonomous Underwater Vehiclesmentioning

confidence: 99%

Marine Monitoring for Offshore Geological Carbon Storage—A Review of Strategies, Technologies and Trends

et al. 2021

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Carbon capture and storage (CCS) could significantly contribute to reducing greenhouse gas emissions and reaching international climate goals. In this process, CO2 is captured and injected into geological formations for permanent storage. The injected plume and its migration within the reservoir is carefully monitored, using geophysical methods. While it is considered unlikely that the injected CO2 should escape the reservoir and reach the marine environment, marine monitoring is required to verify that there are no indications of leakage, and to detect and quantify leakage if it should occur. Marine monitoring is challenging because of the considerable area to be covered, the limited spatial and temporal extent of a potential leakage event, and the considerable natural variability in the marine environment. In this review, we summarize marine monitoring strategies developed to ensure adequate monitoring of the marine environment without introducing prohibitive costs. We also provide an overview of the many different technologies applicable to different aspects of marine monitoring of geologically stored carbon. Finally, we identify remaining knowledge gaps and indicate expected directions for future research.

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“…Autonomous Underwater Vehicle (AUV) plays an important role in marine cognition and resource development. [1][2][3][4] Since it takes more than 5 h to submerge into the deepest part of the ocean (about 11,000 m) for one time, the safety of the full-ocean-depth AUV is greatly important. 5,6 Safety decision-making in this paper means that the AUV can judge independently and take the corresponding measures to protect its own safety when it encounters danger.…”

Section: Introductionmentioning

confidence: 99%

Bayesian network-based security decision-making method for the full-ocean-depth “Wukong” AUV

Wang

Zhang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part M:

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Safety is a critical issue to be considered for a full-ocean-depth AUV, which is a platform to submerge into the deepest part of the ocean. This paper investigates the security decision-making problem for a full-ocean-depth AUV. In order to make a reasonable decision when the AUV encounters a hazard case, such as the leakage of the electronic cabin, this paper presents a security decision-making method based on Bayesian network for the full-ocean-depth AUV to improve the safety. Specifically, the structure of the Bayesian network is determined based on the greedy search algorithm, and it also gives the parameters of each node in the Bayesian network. Finally, this method is applied on the full-ocean-depth AUV, named “Wukong” AUV, to demonstrate the effectiveness of the developed method.

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Autosub Long Range 6000: A Multiple-Month Endurance AUV for Deep-Ocean Monitoring and Survey

Cited by 34 publications

References 29 publications

Management and Sustainable Exploitation of Marine Environments through Smart Monitoring and Automation

Management and Sustainable Exploitation of Marine Environments through Smart Monitoring and Automation

Marine Monitoring for Offshore Geological Carbon Storage—A Review of Strategies, Technologies and Trends

Bayesian network-based security decision-making method for the full-ocean-depth “Wukong” AUV

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