Underwater Vehicle Applications Research Articles

Motion Control of a Low-Cost Underwater Vehicle with Three-Position Cross Rudder

Underwater vehicles are widely employed as platforms for marine monitoring and operations, with rudders playing a crucial role in controlling their movements. Traditional underwater vehicles utilize servos to steer rudders, which results in high production and maintenance costs. To reduce the manufacturing costs of small underwater vehicles, this paper proposes a design featuring a three-position cross rudder driven by a binary-controlled electromagnet. Additionally, a novel virtual rudder angle controller is developed, which utilizes PWM frequency conversion to perform rudder control, ensuring motion performance comparable to that of conventional underwater vehicles. By establishing kinematic and dynamic models of a typical underwater vehicle (REMUS100), a corresponding virtual rudder angle control strategy is introduced. Based on the binary-controlled three-position cross rudder and virtual rudder angle controller, the effectiveness of the motion control method is verified by numerical simulation. The results confirm that the proposed virtual rudder angle controller successfully executes turning and spatial path-tracking tasks. The binary-controlled three-position cross rudder, together with the virtual rudder angle controller, offers a cost-effective solution for the practical application of small unmanned underwater vehicles, particularly for disposable underwater vehicles that do not require recovery.

Highly Effective Electrolytes Toward High‐Performance Aluminum/Seawater Batteries

AbstractThe poor performance of metal/water batteries caused by self‐corrosion of anodes and low catalytic activity of cathodes has been a long‐standing challenge, greatly limiting their practical applications, in particular the underwater unmanned vehicle (UUV) application. We have fabricated an Al/seawater battery using simulated seawater with an appropriate pH and added with polyacrylic acid (PAA) as the electrolyte. This electrolyte simultaneously greatly retards self‐corrosion of the Al anode by in situ forming a PAA‐Al3+ complex film on it and increases the electrocatalytic activity toward the hydrogen evolution reaction by improving the electronic structure of Pt. When utilizing the multielement‐doped Al sheet as the anode and nickel foam supported loading‐amount‐optimized Pt/C catalyst as the cathode and adopting the developed new electrolyte, the obtained Al/H2O battery exhibits an energy density of 2271 Wh kg−1, which is the highest among those of all the reported batteries, and a power density of 20.87 mW cm−2, which outperforms all the reported metal/H2O batteries. This work not only develops a new type of high‐performance Al/H2O batteries for practical applications such as UUVs, but provides scientific insight into the design of superior electrolytes, which could be further extended for improving the performances of various metal batteries.

A novel underwater object detection enhanced algorithm based on YOLOv5‐MH

AbstractUnderwater object detection is an important application of underwater vehicles. However, traditional underwater object detection algorithms have several shortcomings in underwater settings. These include imprecise feature extraction, slow detection speeds, and a lack of robustness. To address these shortcomings, a novel approach based on YOLOv5‐MH (Multi‐Head) is proposed in this paper. Firstly, an image enhancement technique is utilised. This technique uses adaptive linear mapping to adjust contrast and improve the quality of underwater images. Secondly, the C2f module for feature extraction is employed to enable more effective capture of object characteristics. Subsequently, the multi‐head self‐attention and coordinate attention are integrated into the network's backbone. This integration increases the attention given to input data, thereby enhancing the network's performance in handling complex tasks. Furthermore, a bidirectional feature pyramid is implemented to adeptly handle objects of varying scales and sizes, and elevate model performance. Finally, through comprehensive testing on the 2018 URPC dataset and deep plastic dataset, this method demonstrates superior performance. This performance is compared to the original YOLOv5 and other similar networks. It holds immense promise for practical applications across a wide spectrum of underwater tasks.

Direction-Finding Study of a 1.7 mm Diameter Towed Hydrophone Array Based on UWFBG.

This paper investigates a 1.7 mm diameter ultra-weak fiber Bragg grating (UWFBG) hydrophone towed array cable for acoustic direction finding. The mechanism of the underwater acoustic waves received by this integrated-coating sensitizing optical cable is deduced, and it is shown that the amplitude of its response varies with the direction of the sound wave. An anechoic pool experiment is carried out to test the performance of such a hydrophone array. The test array is a selection of six sensing fibers, each of which is coiled into 9 cm diameter fiber ring suspended in the water to receive acoustic signals. An average sensitivity of -141.2 dB re rad/μPa at frequencies from 2.5 kHz to 6.3 kHz was achieved, validating the detection of the azimuth of underwater acoustic waves. The ultra-thin towing cable system, with free structure, high sensitivity, and underwater target-detection capability has demonstrated great potential for future unmanned underwater vehicle (UUV) applications.

Mechanical properties and failure behavior of additively manufactured Al2O3 lattice structures infiltrated with phenol-formaldehyde resin

The lightweight design and load-bearing capacity of underwater vehicles remain perennial focal points. Ceramic lattice structures (CLSs) offer significant weight reduction while maximizing structural strength; however, their inherent brittleness poses a limitation. To optimize the performance of CLSs for underwater vehicle applications, a biomimetic Al2O3/phenol-formaldehyde (PF) resin composite structure (APCS) was proposed and fabricated by infiltrating additive-manufactured Al2O3 lattice structures (ALSs) with PF. Comprehensive assessments of the quasi-static mechanical properties were conducted using both experimental and simulation methods. The specific compressive strength and specific energy absorption of the APCSs under quasi-static compressive loading exhibited remarkable improvements, with the maximum values achieved from the body-centered cubic (BCC)/PF structure increasing by ∼15.23 and ∼307.93 times, respectively. In contrast to ALSs, the failure process of APCSs was gradual, with the confining pressure introduced by the PF promoting transverse crack propagation and layer-by-layer failure, thereby strengthening the ceramic lattice. Toughing mechanisms (i.e., crack arrest, crack deflection, and branching) were also observed in the APCSs. Furthermore, the simulation results aligned well with the experimental results, providing an in-depth analysis of internal damage and crack propagation. The improvements introduced by the composite structure in this study provide a reliable approach for obtaining lightweight and strong materials, thereby accelerating the application of ceramic-based materials in underwater vehicles.

Unmanned Underwater Vehicles in Crime Detection and Prevention

The relevance of the research is determined by the need to develop effective methods and strategies for the use of modern technologies to ensure the security of marine and underwater facilities in the face of the growing threat of underwater activity, terrorism, and violations of laws at sea. The research aims to analyse and document specific tactical and organisational approaches to the use of unmanned underwater vehicles aimed at increasing the effectiveness of actions related to the detection, investigation, and prevention of underwater crime. Classification, analytical, functional, statistical, and synthesis methods are among the methods used. The research results highlight the global experience of using drones in forensic practice and may serve as a basis for further improvement of legislation in this area. The application of uninhabited underwater vehicles by law enforcement and state bodies in the investigation of criminal offences is considered in the article, and the norms of criminal procedural legislation of the Republic of Kazakhstan regulating the use of technical means in criminal proceedings are analysed. The study reveals the lack of comprehensive research on the use of unmanned underwater vehicles as scientific and technical means for the investigation of certain types of criminal cases, such as drug-trafficking and poaching, and offers recommendations on their use to identify and search for evidence in the aquatic environment. This research has a practical value by providing new methodologies and strategies for organisations and law-enforcement agencies in the field of underwater security, contributing to more effective detection, investigation, and prevention of crime in the maritime and underwater domains.

Multifidelity topology design of a maritime survey operation with UUVs

Multifidelity topology design of a maritime survey operation with UUVs

Recent Advances in Superhydrophobic Materials Development for Maritime Applications.

Underwater superhydrophobic surfaces stand as a promising frontier in materials science, holding immense potential for applications in underwater infrastructure, vehicles, pipelines, robots, and sensors. Despite this potential, widespread commercial adoption of these surfaces faces limitations, primarily rooted in challenges related to material durability and the stability of the air plastron during prolonged submersion. Factors such as pressure, flow, and temperature further complicate the operational viability of underwater superhydrophobic technology. This comprehensive review navigates the evolving landscape of underwater superhydrophobic technology, providing a deep dive into the introduction, advancements, and innovations in design, fabrication, and testing techniques. Recent breakthroughs in nanotechnology, magnetic-responsive coatings, additive manufacturing, and machine learning are highlighted, showcasing the diverse avenues of progress. Notable research endeavors concentrate on enhancing the longevity of plastrons, the fundamental element governing superhydrophobic behavior. The review explores the multifaceted applications of superhydrophobic coatings in the underwater environment, encompassing areas such as drag reduction, anti-biofouling, and corrosion resistance. A critical examination of commercial offerings in the superhydrophobic coating landscape offers a current perspective on available solutions. In conclusion, the review provides valuable insights and forward-looking recommendations to propel the field of underwater superhydrophobicity toward new dimensions of innovation and practical utility.

A Control Architecture for Developing Reactive Hybrid Remotely Operated Underwater Vehicles

This article introduces a control architecture designed for the development of Hybrid Remotely Operated Underwater Vehicles. The term ”Hybrid” characterizes Remotely Operated systems capable of autonomously executing specific operations. The presented architecture maintains teleoperation capabilities while enabling two fully autonomous applications. The approach emphasizes the implementation of reactive navigation by exclusively utilizing data from a Mechanical Scanned Imaging Sonar for control decisions. This mandates the control system to solely react to data derived from the vehicle’s environment, without considering other positioning information or state estimation. The study involves transforming a small-scale commercial Remotely Operated Underwater Vehicle into a hybrid system without structural modifications, and details the development of an intermediate Operational Control Layer responsible for sensor data processing and task execution control. Two practical applications, inspired by tasks common in natural or open-water aquaculture farms, are explored: one for conducting transects, facilitating monitoring and maintenance operations, and another for navigating toward an object for inspection purposes. Experimental results validate the feasibility and effectiveness of the authors’ hypotheses. This approach expands the potential applications of underwater vehicles and facilitates the development of Hybrid Remotely Operated Underwater Vehicles, enabling the execution of autonomous reactive tasks.

Assessment of Numerical Captive Model Tests for Underwater Vehicles: The DARPA SUB-OFF Test Case

During the early design stage of an underwater vehicle, the correct assessment of its manoeuvrability is a crucial task. Conducting experimental tests still has high costs, especially when dealing with small vehicles characterized by low available budget. In the current investigation, virtual towing tank tests are simulated using the open-source OpenFOAM library in order to assess the reliability of CFD methods for the prediction of hydrodynamic forces and moments. A well-known case study, the Defence Advanced Research Projects Agency (DARPA) SUB-OFF model, is used, and the outcomes are compared to the experimental results available in the literature. Five different configurations are investigated for pure drift tests, rudder tests and pure rotation in both vertical and horizontal plane. The results show an overall good agreement with the experimental data with a quite low demanding mesh arrangement of 3M cells, a favourable balance between accuracy and computational time. In more detail, the expected error in the most significant forces during manoeuvres is less than 2% for the fully appended configuration (the submarine real operative condition), whereas the accuracy is moderately reduced for the barehull configuration (a case not representative of a real hull) with an expected error of 15%. A possible reason for the differences observed could be attributed to the description of the two streamwise vortices generated when manoeuvring. Apart from the lateral force and yaw moment, the results of the longitudinal force are also presented, having a greater disparity when compared to the experimental data. Nevertheless, the longitudinal force has no important role for the purpose of making stability and control predictions. The study contributes to the validation and consolidation of CFD methods, offering insights into their accuracy and limitations for practical applications in underwater vehicles.

Safety-Critical Trajectory Generation and Tracking Control of Autonomous Underwater Vehicles

Safety-critical control is crucial but difficult in the applications of autonomous underwater vehicles (AUVs). This article proposes a novel hierarchical safety-critical framework for the control of AUVs consisting of waypoint-based optimal trajectory generation and tracking. The objective is to generate a smooth and feasible trajectory to conform to the dynamics of the AUV and then control the AUV to operate in a safe region. To this end, the offline trajectory generator and the online controller are designed. In the offline step, an improved minimum snap polynomial trajectory is generated as the tracking reference. Specifically, the trajectory is optimized by explicitly considering the practical constraints of the AUV's actuator, which alleviates the complexity of the controller design and computational burden compared with the real-time nonlinear optimization. In the online step, the time- and state-dependent high-order control barrier functions are incorporated into optimization through quadratic programming (QP) that modifies the backstepping-based nominal controller in a minimally invasive way. As a supplement and adjustment to the offline planning, the online step ensures that the system states are maintained in the safety set, thus ensuring obstacle avoidance. The online computational efficient QP structure guarantees convenience and scalability in practical implementation. Both the online static and dynamic obstacle avoidance simulations demonstrate the adherence to the safety constraints. Experimental results validate the effectiveness of the proposed method.

Performance Comparison of Feature Detectors on Various Layers of Underwater Acoustic Imagery

Image feature matching is essential in many computer vision applications, and the foundation of matching is feature detection, which is a crucial feature quantification process. This manuscript focused on detecting more features from underwater acoustic imageries for further ocean engineering applications of autonomous underwater vehicles (AUVs). Currently, the mainstream feature detection operators are developed for optical images, and there is not yet a feature detector oriented to underwater acoustic imagery. To better analyze the suitability of existing feature detectors for acoustic imagery and develop an operator that can robustly detect feature points in underwater imageries in the future, this manuscript compared the performance of well-established handcrafted feature detectors and that of the increasingly popular deep-learning-based detectors to fill the gap in the literature. The datasets tested are from the most commonly used side-scan sonars (SSSs) and forward-looking sonars (FLSs). Additionally, the detection idea of these detectors on the acoustic imagery phase congruency (PC) layer was innovatively proposed with the aim of finding a solution that balances detection accuracy and speed. The experimental results show that the ORB (Oriented FAST and Rotated BRIEF) and BRISK (Binary Robust Invariant Scalable Keypoints) detectors achieve the best overall performance, the FAST detector is the fastest, and the PC and Sobel layers are the most favorable for implementing feature detection.

A Switched Variational Estimation Algorithm for Continuous Discrete Measurement Information Loss in Underwater Navigation: Linear versus Nonlinear

In various applications of automatic underwater vehicles (AUVs), it is necessary to acquire the real-time location and speed information of the AUV. However, the complicated and fluctuating marine environment leads to measurement information loss. The accuracy of noise measurement is vital for accurate state estimation, but it is difficult for traditional algorithms to acquire time-varying noise measurements. Due to inaccurate process models and measurement noise, the filtering performance becomes poor or even diverges. To address the problems above, a switched variational estimation filtering (SVEF) algorithm, which combines the advantages of both Gaussian filtering and the variational estimation (VE) method, is proposed. In SVEF, VE is embedded into a linear or nonlinear filtering algorithm. Owing to the continuous discrete underwater navigation model, the state vector is estimated by the SVEF in the case of measurement information loss, and the accurate position and velocity of the AUV are determined. The experimental results prove that the SVEF achieves better positioning precision and is more robust than other conventional algorithms for AUV applications.

A Prototype Design and Sea Trials of an 11,000 m Autonomous and Remotely-Operated Vehicle Dream Chaser

To better study the biology and ecology of hadal trenches for marine scientists, the Hadal Science and Technology Research Center (HAST) of Shanghai Ocean University proposed to construct a movable laboratory that includes a mothership, several full-ocean-depth (FOD) submersibles, and FOD landers to obtain samples in the hadal trenches. Among these vehicles, the project of an FOD autonomous and remotely-operated vehicle (ARV) named “Dream Chaser” was started in July 2018. The ARV could work in both remotely-operated and autonomous-operated modes, and serves large-range underwater observation, on-site sampling, surveying, mapping, etc. This paper proposed a novel three-body design of the FOD ARV. A detailed illustration of the whole system design method is provided. Numerical simulations and experimental tests for various sub-systems and disciplines have been conducted, such as resistance analysis using the computational fluid mechanics method and structural strength analysis for FOD hydrostatic pressure using the finite element method and pressure chamber tests. In addition, components tests and the entire system tests have been performed on land, underwater, and in the pressure chamber in the laboratory of HAST, and the results are discussed. Extensive experiments of two critical components, i.e., the thrusters and ballast-abandoning system, have been conducted and further analyzed in this paper. Finally, the procedures and results of lake trials, South China Sea trials and the first phase of Mariana Trench sea trials of the ARV in 2020 are also introduced. This paper provides a design method for the novel three-body FOD ARV. More importantly, the lessons learned from the FOD pressure test, lake tests, and sea trials, no matter the success or failure, will guide future endeavors and the application of ARV Dream Chaser and underwater vehicles of this kind.

Impacts of Discretization and Numerical Propagation on the Ability to Follow Challenging Square Wave Commands

This study determines the threshold for the computational rate of actuator motor controllers for unmanned underwater vehicles necessary to accurately follow discontinuous square wave commands. Motors must track challenging square-wave inputs, and identification of key computational rates permit application of deterministic artificial intelligence (D.A.I.) to achieve tracking to a machine-precision degree of accuracy in direct comparison to other state-of-art approaches. All modeling approaches are validated in MATLAB simulations where the motor process is discretized at varying step-sizes (inversely proportional to computational rate). At a large step-size (fast computational rate), discrete D.A.I. shows a mean error more than three times larger than that of a ubiquitous model-following approach. Yet, at a smaller step size (slower computational rate), the mean error decreases by a factor of 10, only three percent larger than that of continuous D.A.I. Hence, the performance of discrete D.A.I. is critically affected by the sampling period for discretization of the system equations and computational rate. Discrete D.A.I. should be avoided when small step-size discretization is unavailable. In fact, continuous D.A.I. has surpassed all modeling approaches, which makes it the safest and most viable solution to future commercial applications in unmanned underwater vehicles.

Key Techniques of SINS/DVL Integrated Navigation System

Doppler Velocity Log (DVL) aided Strapdown Inertial Navigation System (SINS) is commonly used for the applications of Autonomous Underwater Vehicles (AUVs). In lack of other aiding sensors, how to maintain precise integrated navigation is still a challenge issue. In this paper, the structure and basic principles of the SINS is presented. Alignment calibration of SINS and DVL, fast in-motion alignment and data fusion are key factors which has great influence on the navigation accuracy. Research efforts taken in these fields in recent years are surveyed. This paper may provide a firm foundation for the researchers in related areas.

Application of unmanned underwater vehicles in polar research

The importance of polar ice as vital components of the global ocean–climate system is widely recognized. In this paper, we demonstrate the importance and urgency of polar research, describe the primary characteristics of sea ice and ice shelves, and outline the current status and difficulties associated with sub-ice research. We highlight the importance of Unmanned Underwater Vehicles (UUVs) as important tools for oceanographic research. We present recent progress in UUV deployment in sub-ice research in the Arctic and the Antarctic, and review the latest international developments in UUV structure, navigation, payload, and field operation. Moreover, Chinese polar UUVs and their deployments in the polar regions are presented in detail. Key technologies and solutions regarding polar application of UUVs (e.g., sub-ice navigation and positioning, energy supply and data transmission, and sub-ice guidance and recovery) are discussed. Given the current worldwide attention on polar science, the potential future directions of UUV-related polar research (e.g., observations under Antarctic ice shelves, long-range surveys beneath Arctic sea ice and application of intelligent technology) are discussed. Citation :Zeng J B, Li S, Liu Y. Application of unmanned underwater vehicles in polar research. Adv Polar Sci, 2021, 32(3): 173-184, doi: 10.13679/j.advps.2021.0018

Simultaneous localisation and mapping for autonomous underwater vehicle using a combined smooth variable structure filter and extended kalman filter

ABSTRACT Localisation technology is one of the most important challenges of underwater vehicle applications that accomplish any scheduled mission in the complex underwater environment. Currently, the Simultaneous Localisation and Mapping (SLAM) of the Autonomous Underwater Vehicle (AUV) is becoming a hotspot research. AUVs have, only recently, received more attention and underwater platforms continue to dominate the research. To ensure the success of an accurate AUV localisation mission, the problem of drift on the estimated trajectory must be overcome. In order to improve the positioning accuracy of the AUV localisation, a new filter referred to as the Adaptive Smooth Variable Structure Filter (ASVSF) based SLAM positioning algorithm is proposed. To verify the improvement of this filter, the combined SVSF and the Extended Kalman Filter (EKF) are presented. Experimental results based on dataset for underwater SLAM algorithm show the accuracy and stability of the ASVSF AUV localisation position. Several experiments were tested under real-life conditions with an autonomous underwater vehicle based on different filters. The results of these filters have been compared based on Root Mean Squared Error (RMSE) and in terms of localisation and map building errors. It is shown that the adaptive SVSF-SLAM strategy obtains the best performance compared to other algorithms.

MAPPING SOUTH CHINA SEA REGION BY GMT FOR MARINE GEOLOGICAL ANALYSIS AND VISUALIZATION

The study details geological analysis of the South China Sea region. South China Sea is a marginal sea located in unique geographical region of west Pacific Ocean. It has a complex tectonics history being developed at subduction zone of three tectonic plates: Eurasian, Pacific and Indian. Geologically, South China Sea is rich in mineral resources and has high geological prospects. Within the scope of the study, the review of the general settings of the study area (bathymetry, geology, tectonics and sedimentation) is accomplished by the report on the current activities, methods and research clusters. Current directions in the marine geological research in the South China Sea area are presented. Research methods of the seafloor surveying and mapping currently undertaken in the South China Sea region are described: systematic measurement by multi-beam echo-sounders, altimetric measurements, GPS positioning, application of the unmanned underwater vehicles, GIS mapping, data analysis, dredging and drilling. The results include maps visualized by means of Generic Mapping Tools (GMT) showing geological and geophysical settings in the South China Sea region, bathymetry and model of the marine free-air gravity. Research development and recent progress in marine geologic investigations are reported with focus on current activities in the coastal area of the South China Sea region.

District Partition-Based Data Collection Algorithm With Event Dynamic Competition in Underwater Acoustic Sensor Networks

The advent of underwater acoustic sensor networks (UASNs) has enhanced marine environmental monitoring, auxiliary navigation, and marine military defense. One of the core functions of UASNs is data collection. However, current underwater data collection schemes generally encounter problems such as high energy consumption and high latency. Furthermore, the application of multiple autonomous underwater vehicles (AUVs) has contributed to more problems of task assignment and load balancing. This leads to significant failure in data collections and controlling of spontaneous emergencies. To address these problems, a district partition-based data collection algorithm with event dynamic competition in UASNs has been proposed. In this algorithm, the value of information of the packet determines the priority of its transmission to the cluster head. The navigation position of the mobile sink and the area under the responsibility of each AUV are determined by the spatial region division. The path of the AUV in the subregion is then planned using reinforcement learning. Subsequently, the dynamic competition of multiple AUVs is used to handle emergency tasks. The simulation demonstrates that our proposed algorithm significantly reduces energy consumption to guarantee load balancing while reducing end-to-end transmission delay.