The application of fully unmanned robotic systems for inspection of subsea pipelines

Rumson, Alexander G.

doi:10.1016/j.oceaneng.2021.109214

Cited by 47 publications

(17 citation statements)

References 29 publications

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“…This can be directly related to regional survey already being relatively cost-e cient in comparison with the other stages of the exploration process. It should however be noted -that removing conventional regional survey vessels is likely to have a positive impact on risk to personnel, and to emissions to the environment while operating in the arctic, as the USVs will not be crewed -and will consume considerably less fuel (Rumson, 2021). On the other hand, removing crews will have negative effect on the employment rates in the subsea industry.…”

Section: Discussion and Policy Analysismentioning

confidence: 99%

“…USVs can be either remotly operated via data-link, pre-programmed or autnomous. USVs can carry any number of sensors or instruments -and be used for a wide arrange of purposes (Rumson, 2021;Zhang et al, 2019). In the context of this study, USVs are imagined as a replacement for survey vessels employed in regional survey of deep-sea mineral prospecting.…”

Section: Policiesmentioning

confidence: 99%

“…The great impact of replacing a survey vessel with a USV is that the removal of all personnel offshore -and the logistics involved maintaining crews offshore. Removing all offshore crews further affords signi cant risk mitigation and allows for elongated operating seasons in arctic waters (Rumson, 2021). The USV is henceforth signi cantly less costly to build operate, and it can operate for a longer period of the year and thereby be more productive.…”

Section: Policiesmentioning

confidence: 99%

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Exploring Exploration – How to Look for Deep- Sea Minerals

Trellevik

2023

Preprint

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In the spring of 2023, the subsea industry in Norway is gearing up for an opening of the Norwegian continental shelf (NCS) for deep-sea mineral exploration and extraction. Existing research indicates that the profitability of deep-sea mining with today's technology heavily depends on high ore grades. This study explores the potential for emerging techno-operational concepts for exploration to affect the profitability of Seafloor Massive Sulfides (SMS) Industry on the NCS. By way of computer simulation, the study analyzes technologies currently, or soon, poised to enter the subsea market, with regard to their advantage or disadvantage for the SMS industry on the NCS. The study indicates that there is significant advantage in developing geophysical sampling technology for assessing mineral resources and some advantage in developing unmanned surface vessels for regional surveys. It further indicates that developing fleet operated autonomous underwater vehicle concepts for high-resolution surveys is not only moot, but possibly counterproductive. The study thereby contributes techno-operational insight for a budding industry currently looking for technology to improve commercial prospects.

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Section: Discussion and Policy Analysismentioning

confidence: 99%

Section: Policiesmentioning

confidence: 99%

Section: Policiesmentioning

confidence: 99%

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Exploring Exploration – How to Look for Deep- Sea Minerals

Trellevik

2023

Preprint

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“…Autonomous Underwater Vehicles (AUV) have permitted us to deepen the knowledge of the oceans and seafloors. The use of AUVs in tasks such as structural inspection [1,2], environmental risks detection [3], and mapping underwater structures [4], among others, increases the safety of the mission and the reliability of their results [5], and reduces the operational costs considerably [6]. However, due the challenging conditions in the underwater environment, a high precision autonomous navigation is difficult to achieve [7].…”

Section: Introductionmentioning

confidence: 99%

Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles

González-García

Gómez-Espinosa

García-Valdovinos

et al. 2022

Sensors

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Several control strategies have been proposed for the trajectory tracking problem of Autonomous Underwater Vehicles (AUV). Most of them are model-based, hence, detailed knowledge of the parameters of the robot is needed. Few works consider a finite-time convergence in their controllers, which offers strong robustness and fast convergence compared with asymptotic or exponential solutions. Those finite-time controllers do not permit the users to predefine the convergence time, which can be useful for a more efficient use of the robot’s energy. This paper presents the experimental validation of a model-free high-order Sliding Mode Controller (SMC) with finite-time convergence in a predefined time. The convergence time is introduced by the simple change of a time-base parameter. The aim is to validate the controller so it can be implemented for cooperative missions where the communication is limited or null. Results showed that the proposed controller can drive the robot to the desired depth and heading trajectories in the predefined time for all the cases, reducing the error by up to 75% and 41% when compared with a PID and the same SMC with asymptotic convergence. The energy consumption was reduced 35% and 50% when compared with those same controllers.

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“…Artificial intelligence for autonomous ships (unmanned surface vehicles (USVs) and autonomous surface vehicles (ASVs)) has been extensively investigated in the private sector (including bathymetric measurements, subsea pipelines management, marine geography surveys, and safety management) and the military sector (including patrol, security, intrusion detection, blockage, and defense). Artificial intelligence has proven its benefits in solving control issues related to the operation of ships under an unstable natural environment, reducing risk, and enhancing efficiency under collaborative or competitive conditions with other ships in the real ocean [1][2][3][4][5][6].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Continuous Autonomous Ship Learning Framework for Human Policies on Simulation

2022

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Considering autonomous navigation in busy marine traffic environments (including harbors and coasts), major study issues to be solved for autonomous ships are avoidance of static and dynamic obstacles, surface vehicle control in consideration of the environment, and compliance with human-defined navigation rules. The reinforcement learning (RL) algorithm, which demonstrates high potential in autonomous cars, has been presented as an alternative to mathematical algorithms and has advanced in studies on autonomous ships. However, the RL algorithm, through interactions with the environment, receives relatively fewer data from the marine environment. Moreover, the open marine environment causes difficulties for autonomous ships in learning human-defined navigation rules because of excessive degrees of freedom. This study proposes a sustainable, intelligent learning framework for autonomous ships (ILFAS), which helps solve these difficulties and learns navigation rules specified by human beings through neighboring ships. The application of case-based RL enables the participation of humans in the RL learning process through neighboring ships and the learning of human-defined rules. Cases built as curriculums can achieve high learning effects with fewer data along with the RL of layered autonomous ships. The experiment aims at autonomous navigation from a harbor, where marine traffic occurs on a neighboring coast. The learning results using ILFAS and those in an environment where random marine traffic occurs are compared. Based on the experiment, the learning time was reduced by a tenth. Moreover, the success rate of arrival at a destination was higher with fewer controls than the random method in the new marine traffic scenario. ILFAS can continuously respond to advances in ship manufacturing technology and changes in the marine environment.

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The application of fully unmanned robotic systems for inspection of subsea pipelines

Cited by 47 publications

References 29 publications

Exploring Exploration – How to Look for Deep- Sea Minerals

Exploring Exploration – How to Look for Deep- Sea Minerals

Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles

Continuous Autonomous Ship Learning Framework for Human Policies on Simulation

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