An holistic bio-inspired approach for improving the performance of unmanned underwater vehicles

PhD ThesisThis research, as a part of the Nature in Engineering for Monitoring the Oceans (NEMO) project, investigated bio-inspiration to improve the performance of Unmanned Underwater Vehicles (UUVs). Initially, the capabilities and performance of current AUVs were compared with Biological Marine Systems (BMSs), i.e. marine animals (Murphy & Haroutunian, 2011). This investigation revealed significant superiority in the capabilities of BMSs which are desirable for UUVs, specifically in speed and manoeuvring. Subsequently, an investigation was carried out on BMSs to find means to make use of their superior functionality towards engineering improved UUVs. It was discovered that due to a mismatch between the purpose of each species evolution and the desired mission of an UUV, all desired characteristics are not evident in a single species. Moreover, due to the multi-functionality of biological systems, it is not possible to independently study each configuration. Therefore, an holistic approach to study BMSs as a system with numerous configurations was undertaken. An evolutionary search and selection algorithm was developed to obtain the myriad of biological information and adjust them to engineering needs (Haroutunian & Murphy, 2012). This Optimum System Selector (OSS) was implemented to output aspects of the appropriate design combination for a bio-inspired UUV, based on its specified mission. The OSS takes into account the energetic cost of the proposed combination as well as the trade-off between size, speed and manoeuvrability. Appreciating the uncertainty in existing measured biological data, the developed code was successfully verified in comparison with BMSs data. Energetic cost of transport is a key factor in selecting a design combination based on desired missions. This is key to the accuracy of the algorithm. Therefore, in another essential research theme, a sophisticated study has been carried out on the understanding, calculating, predicting and comparison of various biological and engineered underwater systems energetics (Phillips et al., 2012). The results of the OSS compared with existing AUVs, showed improvements in the overall capabilities. Therefore, this method is an excellent guide to transform complex biological data for the future design and development of UUVs.EPSRC

Understanding the power requirements of autonomous underwater systems, Part I: An analytical model for optimum swimming speeds and cost of transport

Many marine species exhibit capabilities that would be desirable for manmade systems operating in the maritime environment. However, without detracting from the potential, if bioinspiration is to prove beneficial, it is important to have a consistent set of metrics that allow fair comparison, without bias, when comparing the performance of engineered and biological systems. In this study we focus on deriving an unbiased metric of performance applicable to marine animals and engineered subsea vehicles for one of the most fundamental of properties; that of the energy cost of locomotion. We present a rational analytical model of the physics behind the total energy cost of locomotion applicable to both biological and engineered autonomous underwater marine systems. This model proposes the use of an equivalent spheroid efficiency as a fair metric to compare engineered and biological systems. The model is then utilised to identify how changes in mass, speed, spheroid efficiency and hotel load impact the performance of the system

The Risk of Venous Thromboembolism with Different Generation of Oral Contraceptives; a Systematic Review and Meta-Analysis

Introduction: Oral contraceptives (OCs) are considered as one of the most common risk factor of venous thromboembolism (VTE) in child bearing age. Some of the recent researches indicate that the odds of VTE may be even higher with newer generations of OCs. The present meta-analysis was designed to evaluate the effect of different generation of OCs on the occurrence of VTE. Methods: Two researchers independently ran a thorough search in Pubmed, ISI Web of Science, EMBASE, CINAHL and Scopus databases regarding study keywords including thromboembolic event, thromboembolism, embolism, thromboembolic, thrombotic and thrombosis, combined with oral contraceptive. The outcomes were the incidence of diagnosed thromboembolism, such as deep vein thrombosis, pulmonary embolism and cerebral venous thrombosis. Based on the heterogeneity of the studies, random effect model was used and pooled odds ratio was reported. Results: Three cohort and 17 case-control studies with 13,265,228 subjects were entered into meta-analysis. Analysis showed that the odds of VTE in women taking OCs are more than three-fold (OR=3.13; 95% CI: 2.61-3.65). The risk of VTE in women taking first-, second- and third-generation OCs are 3.5 fold (OR=3.48; 95% CI: 2.01-4.94), 3 fold (OR=3.08; 95% CI: 2.43-3.74) and 4.3 fold (OR=4.35; CI: 3.69‒5.01), respectively. Conclusion: It seems that the risk of VTE is not same between different generations of OCs, so that third-generation has highest risk. Taking second and third-generation OCs increases the risk of VTE up to 3 and 4.3 fold, respectively. The researchers of the present study suggest that more clinical trials be designed in relation to the effect of newer generations of OCs in different communities.

An experimental investigation into the effect of Cu2O particle size on antifouling roughness and hydrodynamic characteristics by using a turbulent flow channel

Copper and copper compounds are commonly used as biocides against biofouling on surfaces exposed to seawater. Copper oxide, one of the most commonly used forms of copper biocide, can provide an efficient mechanism for fouling-free surfaces, resulting in substantial fuel savings and reduction of Greenhouse Gases (GHG) emissions. However, copper oxide is commercially formulated with different particle sizes, which can consequently lead to surfaces with different roughness conditions. The roughness effect of various sizes of copper oxide particles on the drag performance of antifouling coatings, and hence on the ship hull drag, has not been systematically studied in the past. Therefore, to investigate the effect of particle sizes on antifouling roughness and hydrodynamic characteristics, a number of different sized cuprous oxide pigments (with median size ranging from 2µm to 250µm) were applied on Newcastle University’s (UNEW) standard acrylic flat test panels. Roughness characteristics were analysed by using an optical surface profilometer. Moreover, the microstructure observations of all test specimens were carried out using Scanning Electron Microscopy (SEM). Subsequently, a laboratory experiment of streamwise pressure drop measurements was conducted on all coated plates and compared to uncoated acrylic control panels. The Reynolds number for the experiment, based on bulk mean velocity and channel height, ranged from 3×〖10〗^4 to 1.6×〖10〗^5. Analysis indicated that for the panels coated with particle sizes ≥12µm, the roughness characteristics and frictional drag increased as particle size increased. Interestingly, due to particle agglomeration and surface finish condition, those panels coated with particle sizes <12µm were found not follow this trend and had higher roughness and drag characteristics than expected

Mission based optimum system selector for bio-inspired unmanned untethered underwater vehicles

This paper is a part of the Nature in Engineering for Monitoring the Oceans (NEMO) project, investigating bio-inspiration to improve the performance of Unmanned Untethered Underwater Vehicles (UUUVs). Since biological systems (i.e. marine animals) are natives to the oceans, successfully surviving through time, they have been the source of this approach.</p

Virtual Underwater Datasets for Autonomous Inspections

Underwater Vehicles have become more sophisticated, driven by the off-shore sector and the scientific community&rsquo;s rapid advancements in underwater operations. Notably, many underwater tasks, including the assessment of subsea infrastructure, are performed with the assistance of Autonomous Underwater Vehicles (AUVs). There have been recent breakthroughs in Artificial Intelligence (AI) and, notably, Deep Learning (DL) models and applications, which have widespread usage in a variety of fields, including aerial unmanned vehicles, autonomous car navigation, and other applications. However, they are not as prevalent in underwater applications due to the difficulty of obtaining underwater datasets for a specific application. In this sense, the current study utilises recent advancements in the area of DL to construct a bespoke dataset generated from photographs of items captured in a laboratory environment. Generative Adversarial Networks (GANs) were utilised to translate the laboratory object dataset into the underwater domain by combining the collected images with photographs containing the underwater environment. The findings demonstrated the feasibility of creating such a dataset, since the resulting images closely resembled the real underwater environment when compared with real-world underwater ship hull images. Therefore, the artificial datasets of the underwater environment can overcome the difficulties arising from the limited access to real-world underwater images and are used to enhance underwater operations through underwater object image classification and detection

Virtual Underwater Datasets for Autonomous Inspections

Underwater Vehicles have become more sophisticated, driven by the off-shore sector and the scientific community’s rapid advancements in underwater operations. Notably, many underwater tasks, including the assessment of subsea infrastructure, are performed with the assistance of Autonomous Underwater Vehicles (AUVs). There have been recent breakthroughs in Artificial Intelligence (AI) and, notably, Deep Learning (DL) models and applications, which have widespread usage in a variety of fields, including aerial unmanned vehicles, autonomous car navigation, and other applications. However, they are not as prevalent in underwater applications due to the difficulty of obtaining underwater datasets for a specific application. In this sense, the current study utilises recent advancements in the area of DL to construct a bespoke dataset generated from photographs of items captured in a laboratory environment. Generative Adversarial Networks (GANs) were utilised to translate the laboratory object dataset into the underwater domain by combining the collected images with photographs containing the underwater environment. The findings demonstrated the feasibility of creating such a dataset, since the resulting images closely resembled the real underwater environment when compared with real-world underwater ship hull images. Therefore, the artificial datasets of the underwater environment can overcome the difficulties arising from the limited access to real-world underwater images and are used to enhance underwater operations through underwater object image classification and detection

An Underwater Visual Navigation Method Based on Multiple ArUco Markers

Underwater navigation presents crucial issues because of the rapid attenuation of electronic magnetic waves. The conventional underwater navigation methods are achieved by acoustic equipment, such as the ultra-short-baseline localisation systems and Doppler velocity logs, etc. However, they suffer from low fresh rate, low bandwidth, environmental disturbance and high cost. In the paper, a novel underwater visual navigation is investigated based on the multiple ArUco markers. Unlike other underwater navigation approaches based on the artificial markers, the noise model of the pose estimation of a single marker and an optimal algorithm of the multiple markers are developed to increase the precision of the method. The experimental tests are conducted in the towing tank. The results show that the proposed method is able to localise the underwater vehicle accurately

A comparison of functional control strategies for underwater vehicles: theories, simulations and experiments

Functional control is key for any autonomous robot, linking high-level artificial intelligence with the robot actuators. Due to environmental disturbances, model uncertainties and nonlinear dynamic systems, reliable functional control is essential and improvements in the controller design can significantly benefit the overall vehicle performance. Even though there are many published studies considering the design of various advanced controllers, most of them are not evaluated in physical experiments. In this research, four different control strategies have been investigated: Proportional-Integral-Derivative Control (PID), Sliding Mode Control (SMC), Backstepping Control (BC) and Fuzzy Logic Control (FLC). The performances of these four controllers were simulated initially and evaluated by practical experiments in different conditions, including various environmental disturbances and hydrodynamic coefficients. The main contributions are as follows: Firstly, this paper reports a comparison study between different types of controllers based on simulations and physical experiments in various conditions; Secondly, this paper provides an improved SMC algorithm combining the merits from linear control and nonlinear control, and a customized second-order FLC method.</p

A low-cost visual inertial odometry system for underwater vehicles

The localization is a crucial issue for underwater vehicles. In the paper, a lightweight visual-inertial odometry is proposed. With dual inertial sensors giving the information of acceleration and attitude, an optical camera providing the seabed images where feature points are tracked by an optical flow algorithm, linear motion of the vehicle can be obtained by computing coordinate transformations and in the fusion section, the control input is also considered. The computational complexity of the proposed method is reduced dramatically relative to other methodologies, and the optical flow algorithm can allow the system to work in poor context environment conditions. The results evaluated by practical experiments show that the method is an effective, low-cost solution for underwater localization. </p