50 research outputs found

    Controlling the manipulator of an underwater ROV using a coarse calibrated pan tilt camera

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    International audienceIn this paper we present a vision-based method to control the displacement of robot arm mounted on an underwater ROV. A closed-loop system based on an eye-to-hand visual servoing approach has been designed to achieve this task. We show that, using such an approach, measuring the manipulator motion with proprioceptive sensors is not required to precisely control the end-effector motion. To maintain the end effector in the field of view, the camera orientation is also controlled. Presented results show the validity of the approach

    Dangerous Inspection & Versatile Exploration Robot (DIVER): Tracking, Monitoring and Assisting Human Divers in Commercial, Environmental and Military Applications

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    The Dangerous Inspection & Versatile Exploration Robot (DIVER) is an underwater remotely operated vehicle designed to assist, track and monitor professional scuba divers in commercial, research and military applications. Integration of custom and commercially available components allowed for hardware development of the ROV. Software development allowed for the integration of OpenTLD tracking algorithm and manual user controls for full autonomous or tele-operational missions. DIVER provides constant communication for the improvement of mission organization and professional diver safety

    Optimisation of docking locations for remotely operated vehicles.

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    This thesis describes work aimed at developing practical methods for determining the best docking locations for an underwater remotely operated vehicle (ROV) when inspecting an offshore platform. ROVs are used extensively in the offshore oil and gas industry to conduct a large variety of intervention tasks such as visual inspection, operational monitoring, equipment installation and operation, debris recovery, and so on. However, they have found only limited use in the more difficult tasks such as the detailed inspection of complex weld geometries. These complex welds are, however, found extensively in the construction of the majority of offshore structures and platforms ('oil rigs'). Furthermore, there is a safety requirement to have them inspected regularly since failure of these welds can potentially lead to catastrophic failure of the structures, the majority of which are manned. A number of specialist ROV systems have been developed that are able to attach onto platform structures and use their manipulators to conduct inspection. However, due to the short reach of the manipulators and the complex geometry of the welds (often encumbered with protruding pipes and other fittings) the success of any inspection is crucially dependent on a good initial choice of ROV docking position. This thesis will describe the problems and current manual planning methods, and then detail the development of two new methods for automated optimisation of docking positions - firstly using neural networks, and secondly using more conventional numerical processing. This thesis will also review related work in the field, such as the development of neural networks and their applications in the general offshore environment and in the control of ROVs and robot manipulator arms, and other approaches to ROV docking. It will further describe the use of the system developed here for planning docking positions on example commercial ROV inspection work programmes

    Underwater Vehicles

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    For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

    RRS James Cook cruise JC166-167, 19 June – 6 July 2018. CLASS – Climate-linked Atlantic System Science Haig Fras Marine Conservation Zone AUV habitat monitoring, Equipment trials and staff training

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    Expedition JC166-167 combined a number of science and technical objectives in order to deliver a comprehensive programme for the UK marine science sector. The expedition supported the NERC National Capability programme CLASS (Climate-Linked Atlantic Sector Science, grant no NE/R015953/1), which aims to increase our understanding of the Atlantic Ocean system, in order to support evidence-based ocean management. More specifically, JC166-167 was part of the Fixed Point Observations Underpinning Activity, where repeated observations and surveys of Marine Protected Areas (MPAs) and their surroundings provide insight into the development and recovery of benthic ecosystems following natural and/or anthropogenic impacts. The target location for JC166-167 was the Greater Haig Fras Marine Conservation Zone (MCZ), west of Cornwall, which was surveyed by NOC, using Autosub AUVs, in 2012 and 2015. The 2018 expedition continued that time series, and expanded the study by also looking at differences in benthic community observed between day and night. Haig Fras is the only rocky reef on the Celtic Shelf, and was protected in 2016. In parallel with these science objectives, JC166-167 included an extensive series of equipment trials, combined with training for staff members of the Marine Autonomous and Robotic Systems group at NOC. The robotic and autonomous systems tested included the Isis ROV, HyBIS vehicle, the Autosub6000 AUV, a deep glider, a wave glider, a C-worker 4 USV and a drone. Some of the trials were carried out in the shallow waters around Haig Fras, while others required greater depths, for which we visited the Whittard Canyon system along the Celtic Margin. Wherever possible, trials and training were carried out in a way that the resulting data would help address CLASS science objectives, including objectives related to the sustained observations in the Canyons MCZ

    QUANTIFICATION OF MARINE MEGAFAUNAL DISTRIBUTION PATTERNS USING A REMOTELY OPERATED VEHICLE

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    This thesis documents the development and application of the Automated Benthic Image Scaling System (ABISS), a novel structured lighting array for calculating image scale, accounting for perspective, to allow quantitative non-destructive megafaunal sampling using observations from a Remotely Operated Vehicle (ROV). Megafauna are important components of marine soft sediment assemblages that influence the composition of the associated assemblage and the flux of energy across the sediment-water interface, by altering the physical and chemical characteristics of the sediment during bioturbation. However, megafaunal species are not sampled adequately using traditional techniques. Megafaunal abundance estimates derived from ROV observations were validated against those derived from direct diver observations and results suggested that data were in close agreement. To quantify spatial variation of the megafaunal assemblage, spatially referenced images were collected with a maximum sample separation of 400 m within a broader area of homogeneous sediment in Plymouth Sound (United Kingdom) during May 2000 and March 2001. Results demonstrated that the spatial distribution of the megafaunal assemblage was neither uniform nor stable temporally. A hierarchy of spatial structure was detected, whereby, patches with minimum radius between 123-163 m were nested within patches up to 400 m radius. To assess the megafaunal contribution to endobenthic biomass, the population size structure and biomass of the dominant megafaunal bivalve Lutraria lutraria was estimated from measurements of the siphon tips. Results indicated that the population size structure was stable between years despite significant differences in abundance. In addition, L lutraria contributed approximately 90% of the endobenthic biomass, indicating that traditional assessment of benthic biomass by consideration of macrofaunal samples alone will underestimate severely the biomass and respiration of the entire endobentic assemblage. Novel techniques of quantifying the spatial distribution of megafaunal assemblages presented in this thesis offer ways forward to address how variation of megafaunal spatial structure affects macrofaunal assemblage structure, and to discuss the application of remote imaging to map and predict quantitatively the conservation value of subtidal soft sediments.Plymouth Marine Laborator
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