5,166 research outputs found

    The Hierarchic treatment of marine ecological information from spatial networks of benthic platforms

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    Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.Peer ReviewedPostprint (published version

    ECO2 Briefing Paper No. 1: The scientific basis for offshore CCS

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    A Flexible Autonomous Robotic Observatory Infrastructure for Bentho-Pelagic Monitoring

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    This paper presents the technological developments and the policy contexts for the project “Autonomous Robotic Sea-Floor Infrastructure for Bentho-Pelagic Monitoring” (ARIM). The development is based on the national experience with robotic component technologies that are combined and merged into a new product for autonomous and integrated ecological deep-sea monitoring. Traditional monitoring is often vessel-based and thus resource demanding. It is economically unviable to fulfill the current policy for ecosystem monitoring with traditional approaches. Thus, this project developed platforms for bentho-pelagic monitoring using an arrangement of crawler and stationary platforms at the Lofoten-Vesterålen (LoVe) observatory network (Norway). Visual and acoustic imaging along with standard oceanographic sensors have been combined to support advanced and continuous spatial-temporal monitoring near cold water coral mounds. Just as important is the automatic processing techniques under development that have been implemented to allow species (or categories of species) quantification (i.e., tracking and classification). At the same time, real-time outboard processed three-dimensional (3D) laser scanning has been implemented to increase mission autonomy capability, delivering quantifiable information on habitat features (i.e., for seascape approaches). The first version of platform autonomy has already been tested under controlled conditions with a tethered crawler exploring the vicinity of a cabled stationary instrumented garage. Our vision is that elimination of the tether in combination with inductive battery recharge trough fuel cell technology will facilitate self-sustained long-term autonomous operations over large areas, serving not only the needs of science, but also sub-sea industries like subsea oil and gas, and mining

    Low cost underwater acoustic localization

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    Over the course of the last decade, the cost of marine robotic platforms has significantly decreased. In part this has lowered the barriers to entry of exploring and monitoring larger areas of the earth's oceans. However, these advances have been mostly focused on autonomous surface vehicles (ASVs) or shallow water autonomous underwater vehicles (AUVs). One of the main drivers for high cost in the deep water domain is the challenge of localizing such vehicles using acoustics. A low cost one-way travel time underwater ranging system is proposed to assist in localizing deep water submersibles. The system consists of location aware anchor buoys at the surface and underwater nodes. This paper presents a comparison of methods together with details on the physical implementation to allow its integration into a deep sea micro AUV currently in development. Additional simulation results show error reductions by a factor of three.Comment: 73rd Meeting of the Acoustical Society of Americ

    An overview of robotics and autonomous systems for harsh environments

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    Across a wide range of industries and applications, robotics and autonomous systems can fulfil the crucial and challenging tasks such as inspection, exploration, monitoring, drilling, sampling and mapping in areas of scientific discovery, disaster prevention, human rescue and infrastructure management, etc. However, in many situations, the associated environment is either too dangerous or inaccessible to humans. Hence, a wide range of robots have been developed and deployed to replace or aid humans in these activities. A look at these harsh environment applications of robotics demonstrate the diversity of technologies developed. This paper reviews some key application areas of robotics that involve interactions with harsh environments (such as search and rescue, space exploration, and deep-sea operations), gives an overview of the developed technologies and provides a discussion of the key trends and future directions common to many of these areas

    Characterization of optical communication in a leader-follower unmanned underwater vehicle formation

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    As part of the research to development an optical communication design of a leader-follower formation between unmanned underwater vehicles (UUVs), this paper presents light field characterization and design configuration of the hardware required to allow the use of distance detection between UUVs. The study specifically is targeting communication between remotely operated vehicles (ROVs). As an initial step in this study, the light field produced from a light source mounted on the leader UUV was empirically characterized and modeled. Based on the light field measurements, a photo-detector array for the follower UUV was designed. Evaluation of the communication algorithms to monitor the UUV’s motion was conducted through underwater experiments in the Ocean Engineering Laboratory at the University of New Hampshire. The optimal spectral range was determined based on the calculation of the diffuse attenuation coefficients by using two different light sources and a spectrometer. The range between the leader and the follower vehicles for a specific water type was determined. In addition, the array design and the communication algorithms were modified according to the results from the light field

    Marine baseline and monitoring strategies for Carbon Dioxide Capture and Storage (CCS)

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    The QICS controlled release experiment demonstrates that leaks of carbon dioxide (CO2) gas can be detected by monitoring acoustic, geochemical and biological parameters within a given marine system. However the natural complexity and variability of marine system responses to (artificial) leakage strongly suggests that there are no absolute indicators of leakage or impact that can unequivocally and universally be used for all potential future storage sites. We suggest a multivariate, hierarchical approach to monitoring, escalating from anomaly detection to attribution, quantification and then impact assessment, as required. Given the spatial heterogeneity of many marine ecosystems it is essential that environmental monitoring programmes are supported by a temporally (tidal, seasonal and annual) and spatially resolved baseline of data from which changes can be accurately identified. In this paper we outline and discuss the options for monitoring methodologies and identify the components of an appropriate baseline survey

    Advancing Climate Change Research and Hydrocarbon Leak Detection : by Combining Dissolved Carbon Dioxide and Methane Measurements with ADCP Data

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    With the emergence of largescale, comprehensive environmental monitoring projects, there is an increased need to combine state-of-the art technologies to address complicated problems such as ocean acidifi cation and hydrocarbon leak detection

    Underwater robotics in the future of arctic oil and gas operations

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    Master's thesis in Petroleum engineeringArctic regions have lately been in the centre of increasing attention due to high vulnerability to climate change and the retreat in sea ice cover. Commercial actors are exploring the Arctic for new shipping routes and natural resources while scientific activity is being intensified to provide better understanding of the ecosystems. Marine surveys in the Arctic have traditionally been conducted from research vessels, requiring considerable resources and involving high risks where sea ice is present. Thus, development of low-cost methods for collecting data in extreme areas is of interest for both industrial purposes and environmental management. The main objective of this thesis is to investigate the use of underwater vehicles as sensor platforms for oil and gas industry applications with focus on seabed mapping and monitoring. Theoretical background and a review of relevant previous studies are provided prior to presentation of the fieldwork, which took place in January 2017 in Kongsfjorden (Svalbard). The fieldwork was a part of the Underwater Robotics and Polar Night Biology course offered at the University Centre in Svalbard. Applied unmanned platforms included remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs) and an autonomous surface vehicle (ASV). They were equipped with such sensors as side-scan sonar, multi-beam echo sounder, camera and others. The acquired data was processed and used to provide information about the study area. The carried out analysis of the vehicle performance gives an insight into challenges specific to marine surveys in the Arctic regions, especially during the period of polar night. The discussion is focused on the benefits of underwater robotics and integrated platform surveying in remote and harsh environment. Recommendations for further research and suggestions for application of similar vehicles and sensors are also given in the thesis
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