Deployment Of Autonomous Underwater Vehicles Research Articles

Reliable Data Collection Techniques in Underwater Wireless Sensor Networks: A Survey

Reliable data collection techniques, whose aim is to ensure that sensed data are received successfully by a sink, are essential for applications in Underwater Wireless Sensor Networks (UWSNs). However, traditional data collection with Radio Frequency (RF) functions poorly in UWSNs due to peculiar features of underwater. Moreover, acoustic communication creates challenges for the reliability of data collection such as high bit error rate, packet collision and voids in routing. Furthermore, the deployment of Autonomous Underwater Vehicles (AUVs) in some scenarios changed the paradigm of data collection and introduced new issues that affect reliability such as inaccurate navigation and lengthy travel time. Consequently, numerous studies focus on the relative reliability of various currently available data collection in UWSNs. In this paper, we first review the problems specific to UWSNs and their impact on reliable data collection. It is followed by a discussion about characteristics, challenges, and features associated with the design of reliable techniques in UWSNs. Afterward, to provide readers with an overview of reliable data collection techniques in UWSNs, this paper categorizes them according to their ability to enhance reliability at all the key stages of data collection. In this categorization framework, the advantages and disadvantages of each technique have been in-depth discussed. Finally, several possible areas for further research are identified and discussed.

A Pipeline Extraction Algorithm for Forward-Looking Sonar Images Using the Self-Organizing Map

An autonomous underwater vehicle (AUV) can operate automatically with a small number of humans and requires few resources when compared to a remotely operated vehicle (ROV). The pipeline inspection with the use of an AUV can be significantly cheaper than those of an ROV. Successful deployment of AUVs relies on accurate pipeline detection and extraction that can automatically locate and track a pipeline direction in real time. We proposed to use forward-looking sonar images to locate and extract pipeline paths since sonar can easily image through turbulence and small particles, commonly found in underwater environments. However, sonar images are prone to disturbance from the environment. Thus, as a superior alternative, we developed a pipeline detection algorithm by considering that a pipeline has a piecewise linear shape. Next, the self-organizing map (SOM) is employed to join the labeled segments together to form a pipeline track to extract the pipeline path for the navigation of an AUV since SOM can map a 2-D image of pipeline into a 1-D line. In our experiment, data obtained from the Gulf of Thailand are used for the performance analysis, and we are able to extract and describe a pipeline direction with accuracies between 90% and 97%.

Human Error in Autonomous Underwater Vehicle Deployment: A System Dynamics Approach.

The use of autonomous underwater vehicles (AUVs) for various applications have grown with maturing technology and improved accessibility. The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extremities in the Antarctic. A thorough analysis of risks is therefore crucial for formulating effective risk control policies and achieving a lower risk of loss. Existing risk analysis approaches focused predominantly on the technical aspects, as well as identifying static cause and effect relationships in the chain of events leading to AUV loss. Comparatively, the complex interrelationships between risk variables and other aspects of risk such as human errors have received much lesser attention. In this article, a systems-based risk analysis framework facilitated by system dynamics methodology is proposed to overcome existing shortfalls. To demonstrate usefulness of the framework, it is applied on an actual AUV program to examine the occurrence of human error during Antarctic deployment. Simulation of the resultant risk model showed an overall decline in human error incident rate with the increase in experience of the AUV team. Scenario analysis based on the example provided policy recommendations in areas of training, practice runs, recruitment policy, and setting of risk tolerance level. The proposed risk analysis framework is pragmatically useful for risk analysis of future AUV programs to ensure the sustainability of operations, facilitating both better control and monitoring of risk.

Fuzzy System Dynamics Risk Analysis (FuSDRA) of Autonomous Underwater Vehicle Operations in the Antarctic.

With the maturing of autonomous technology and better accessibility, there has been a growing interest in the use of autonomous underwater vehicles (AUVs). The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extreme operating environment. To control the risk of loss, existing risk analyses approaches tend to focus more on the AUV's technical aspects and neglect the role of soft factors, such as organizational and human influences. In addition, the dynamic and complex interrelationships of risk variables are also often overlooked due to uncertainties and challenges in quantification. To overcome these shortfalls, a hybrid fuzzy system dynamics risk analysis (FuSDRA) is proposed. In the FuSDRA framework, system dynamics models the interrelationships between risk variables from different dimensions and considers the time-dependent nature of risk while fuzzy logic accounts for uncertainties. To demonstrate its application, an example based on an actual Antarctic AUV program is presented. Focusing on funding and experience of the AUV team, simulation of the FuSDRA risk model shows a declining risk of loss from 0.293 in the early years of the Antarctic AUV program, reaching a minimum of 0.206 before increasing again in later years. Risk control policy recommendations were then derived from the analysis. The example demonstrated how FuSDRA can be applied to inform funding and risk management strategies, or broader application both within the AUV domain and on other complex technological systems.

Control design of a gyro-based wave energy converter for autonomous underwater vehicle

Autonomous Underwater Vehicle (AUV) is an intelligent machine that works at hazardous underwater environment. It can only operate for hours or days at a time by battery charging system. This paper presents a new gyroscopic charging system to reform the traditional way. The new system utilizes the gyroscopic effects of a large rotating flywheel in combination with a controlled power take-off device to extract power from wave motion. In this paper, a gyroscopic energy converter model is given, which contains a description of dynamic equation and controlling design. Consequently, a detailed process of applying the gyroscopic system to a typical AUV is shown. The gyroscopic charging system promises to reduce AUV battery requirements negating the necessity to carry sufficient energy reserves (size and weight) for entire missions, reduce costs by freeing support vessel time (a major cost component in AUV deployment) and enable AUVs to be remotely and renewably recharged at sea, indefinitely extending missions. Software simulation is the main method to prove the validation of the results. The results show that the generated power is sufficient to provide power for AUV which is better than the battery charging system.

Multiple field-based methods to assess the potential impacts of seismic surveys on scallops

Marine seismic surveys are an important tool to map geology beneath the seafloor and manage petroleum resources, but they are also a source of underwater noise pollution. A mass mortality of scallops in the Bass Strait, Australia occurred a few months after a marine seismic survey in 2010, and fishing groups were concerned about the potential relationship between the two events. The current study used three field-based methods to investigate the potential impact of marine seismic surveys on scallops in the region: 1) dredging and 2) deployment of Autonomous Underwater Vehicles (AUVs) were undertaken to examine the potential response of two species of scallops (Pecten fumatus, Mimachlamys asperrima) before, two months after, and ten months after a 2015 marine seismic survey; and 3) MODIS satellite data revealed patterns of sea surface temperatures from 2006–2016. Results from the dredging and AUV components show no evidence of scallop mortality attributable to the seismic survey, although sub-lethal effects cannot be excluded. The remote sensing revealed a pronounced thermal spike in the eastern Bass Strait between February and May 2010, overlapping the scallop beds that suffered extensive mortality and coinciding almost exactly with dates of operation for the 2010 seismic survey. The acquisition of in situ data coupled with consideration of commercial seismic arrays meant that results were ecologically realistic, while the paired field-based components (dredging, AUV imagery) provided a failsafe against challenges associated with working wholly in the field. This study expands our knowledge of the potential environmental impacts of marine seismic survey and will inform future applications for marine seismic surveys, as well as the assessment of such applications by regulatory authorities.

Autonomous underwater vehicle self-localization using a tetrahedral array and passive acoustics

The recent development of very low-cost, miniature autonomous underwater vehicles (AUVs) has lowered the barrier toward the deployment of multiple AUVs for spatially distributed sensing. However, these AUVs introduce size, power, and cost constraints that prevent the use of traditional approaches for vehicle self-localization, such as Doppler velocity log (DVL)-aided inertial navigation. In this work, we describe a system that estimates the vehicle's position relative to a single acoustic transmitter. The transmitter periodically outputs a linear up-chirp that is synchronously recorded by a tetrahedral ultra-short baseline (USBL) hydrophone array on the AUV. Real-time 3D phased-array beamforming and matched filtering is performed on-board the vehicle, and integrated with AUV pitch-roll-heading to calculate azimuth, inclination, and range measurements to the transmitter. Finally, a particle filter incorporates these measurements with vehicle speed estimates and a motion model to generate a positional likelihood for the acoustic transmitter relative to the AUV. This system enables vehicle self-localization in the case where the transmitter is stationary, and is entirely passive on the vehicle, allowing multiple AUVs to localize using a single transmitter. We describe the processing pipeline of our system, and present results from AUV field experiments. [Work supported by Battelle, ONR, Lincoln Laboratory and DARPA.]

自律型水中ロボットの長期間展開に向けた研究開発

自律型水中ロボットの長期間展開に向けた研究開発

The three-dimensional shape of sea ice revealed by multibeam sonar

The life history of sea ice is written in its basal morphology. Sea ice progresses through several stages during its lifecycle, including frazil, nilas and pancake ice, until it bonds into a near-continuous sheet known as first-year (FY) ice. If this ice survives the summer melt-season, it becomes multiyear (MY) ice (Weeks & Ackley 1986). Both FY and MY sea ice have significant morphological variability, ranging from undeformed, level ice to heavily deformed or ridged ice. These variations lead to a complex, highly heterogeneous ice topography. Profiling the underside of Arctic sea ice was first performed by nuclear submarines (e.g. Wadhams 1988, 2000); however, since the end of the Cold War, military submarine transits of the Arctic have become less frequent and are insufficient to understand climate-induced trends. Therefore, deployment of autonomous underwater vehicles (AUVs) equipped with upward-looking multibeam sonar represents an important innovation. Sea ice is not a homogeneous medium. It occurs in a wide variety of forms due to the various thermodynamic and dynamic forces it undergoes during its lifecycle of growth, decay and deformation. The greatest variability is associated with deformed ice in the form of ridges: long, quasi-linear features composed of blocks of ice, piled both above and below the relatively level ice surface. Ridge sails may be up to several metres in height above the sea surface and keels may reach depths of >40 m. These morphological variations lead to a complex, highly heterogeneous sea-ice topography that varies on scales from <1 metre to 100s …

A Dual-Mode Rechargeable Lithium-Bromine/Oxygen Fuel Cell

Increasing global energy demand has driven the exploitation of oil reservoirs in deep oceans. The high risk of oil spill due to unexpected failures of undersea facilities urges the deployment of autonomous underwater vehicles (AUV) for frequent and thorough inspections in these extreme environments that humans cannot easily access. To meet the long endurance and occasionally high power requirements of the AUV, we propose a lithium-bromine/oxygen fuel cell with a protected lithium metal anode to provide high specific energy at either low-power mode with seawater (oxygen) or high-power mode with bromine catholytes. The proof-of-concept fuel cell with a flat catalyst-free graphite electrode can discharge at 3mW/cm2 with seawater, and 9mW/cm2 with dilute bromine catholytes. The fuel cell can also be recharged with LiBr catholytes efficiently to recover the lithium metal anode. Scanning electron microscopy images reveal that both the organic electrolye and the bromine electrolyte corrode the solid electrolyte plate quickly, leading to nanoporous pathways that can percolate through the plate, thus limiting the cell performance and lifetime. With improved solid electrolytes or membraneless flow designs, the dual-mode lithium-bromine/oxygen system could enable not only AUV but also land-based electric vehicles, by providing a critical high-power mode to high-energy-density (but otherwise low-power) lithium-air batteries.

Modeling position uncertainty of networked autonomous underwater vehicles

Recently there has been increasing engineering activity in the deployment of Autonomous Underwater Vehicles (AUVs). Different types of AUVs are being used for applications ranging from ocean exploration to coastal tactical surveillance. These AUVs generally follow a predictable trajectory specified by the mission requirements. Inaccuracies in models for deriving position estimates and the drift caused by ocean currents, however, lead to uncertainty when estimating an AUV’s position. In this article, two forms of position uncertainty – internal and external – are studied, which are the position uncertainty associated with a particular AUV as seen by itself and that as seen by others, respectively. Then, a statistical model to estimate the internal uncertainty for a general AUV is proposed. Based on this model, a novel mathematical framework using Unscented Kalman Filtering is developed to estimate the external uncertainty. Finally, the benefits of this framework for several location-sensitive applications are shown via emulations.

Optimized deployment of autonomous underwater vehicles for characterization of coastal waters

Autonomous Underwater Vehicles (AUV) have evolved most often with specific mission focus areas determined by the defense sponsor or commercial customer. These focus areas have driven platform design and capabilities, as well as the mission planners delivered with these vehicles. While these mission planners have a broad spectrum of sophistication in the interfaces, none provide substantial guidance to the operator in designing a track plan optimized for the physical environment. For some mission areas, survey design is relatively straight-forward. If 100% sensor coverage or over-sampling of an area are required, as is often the case for mine-clearance or industrial reconnaissance, the area of responsibility determines the boundaries, and an estimate of sensor sweep width determines the track spacing. There are other mission areas, however, where area boundaries are too large, and the dynamic parameters too variable, to allow full sensor coverage in a synoptic sense. In these cases, compromises in survey extent and resolution demand track optimization that is driven by vehicle number, speed and endurance trade-offs, spatial and temporal variability of the measured parameters, and environmental factors that physically influence AUV performance. Rapid Environmental Assessment (REA) is one critical mission area where survey optimization is essential, and the selection of waypoints, depths, and geometries to best characterize the changing physical environment with limited platforms and time becomes a critical challenge. Researchers at the Naval Undersea Warfare Division, Newport are using commercially available AUVs from OceanServer Technologies, Inc. (OSTI) with YSI oceanographic sensors to conduct REA surveys in shallow waters. Dynamic Graphics, Inc. (DGI) software is used to establish a 3-D grid and compare the incoming data log files from the AUV sensors with the developing detail of the oceanographic characterization. Confidence estimates are generated in near real-time to represent cost versus benefit of continued survey effort. On-board adjustments to initial survey design, such as increased track spacing, can result from this evaluation to reduce the survey effort and still meet the tactical requirements for accuracy and precision. Field experiments with OSTI AUVs in Lake Champlain, NY and South Watuppa Pond, MA in July, 2007 demonstrated that DGI software could develop high-fidelity data-centric 2-D and 3-D characterizations of environmental parameters with irregular trackline data. The characterizations were suitable for statistical evaluation in near-real time to assess the return on continued survey effort and to recognize dynamic areas for subsequent survey focus. For these environments, reductions in total survey effort of 50%–70% could be achieved with little loss in 2D- and 3D-grid fidelity or feature definition. While the potential for reduction in survey effort is a function of environmental variability, the strength of this approach lies in the ability to establish in-stride the minimum effort required for a fidelity threshold without a first-guess field or a priori knowledge. Processing times and results support future on-board, in-stride analysis by AUVs for survey re-planning to optimize track and depth plans.