Underwater Vehicle Research Articles

Non-Periodic Quantized Model Predictive Control Method for Underwater Dynamic Docking

This study proposed an event-triggered quantized model predictive control (ETQMPC) method for the dynamic docking of unmanned underwater vehicles (UUVs) and human-occupied vehicles (HOVs). The proposed strategy employed a non-periodic control approach that initiated the non-linear model predictive control (NMPC) optimization and state sampling based on tracking errors and deviations from the predicted optimal state, thereby enhancing computing performance and system efficiency without compromising the control quality. To further conserve communication resources and improve information transfer efficiency, a quantitative feedback mechanism was employed for sampling and state quantification. The simulation experiments were performed to verify the effectiveness of the method, demonstrating excellent docking trajectory tracking performance, robustness against bounded current interference, and significant reductions in computational and communication burdens. The experimental results demonstrated that the method outperformed in the docking trajectory tracking control performance significantly improved the computational and communication performance, and comprehensively improved the system efficiency.

Effects of wall heating on wall pressure fluctuations and flow noise in a low-Reynolds-number turbulent channel flow with temperature-dependent viscosity

Wall pressure fluctuations and flow noise substantially degrade sonar detection performance and the acoustic stealth performance of underwater vehicles. This paper numerically investigates the effects of wall heating on wall pressure fluctuations in turbulent channel flow of water with temperature-dependent viscosity, exploring a novel method for controlling wall pressure fluctuations and flow noise in underwater vehicles. Large-eddy simulation (LES) is employed for the numerical calculation of the flow field, while a hybrid method combining LES with Lighthills acoustic analogy is employed to predict flow noise. The numerical results show that when the temperature difference between the wall and the incoming flow is 30 K and 50 K, the peak root-mean-square pressure fluctuations decrease by 6.76% and 8.91%, respectively. Wall heating stabilizes the pressure field near the wall, with the spectral levels of wall pressure fluctuations showing average decreases of approximately 1 dB and 2 dB. Wall heating weakens the energy-containing structures of wall pressure fluctuations and increases the overall convection velocity by 1.22% and 3.81%, respectively. Flow structure analysis reveals that the weakening of energy-containing structures results from the suppression of the vortex structures in the near-wall region. In the wall heating cases, peak turbulent kinetic energy decreases by 12.6% and 15.8%, respectively. Moreover, the sound pressure level of flow noise decreases with increasing wall temperature, with the maximum noise reduction exceeding 3 dB. Previous studies have not yet explored the effects of viscosity reduction caused by wall heating on wall pressure fluctuations and flow noise. This study demonstrates that wall heating is a promising method for reducing wall pressure fluctuations and flow noise.

Event-Triggered Two-Part Separation Control of Multiple Autonomous Underwater Vehicles Based on Extended Observer

In this paper, we investigate the formation isolation regulation issue regarding multiple Autonomous Underwater Vehicles (AUVs) characterized by a “leader–follower” framework. Considering the cooperative–competitive relationship among the follower AUVs and the impact of unknown external disturbances, an extended state observer is designed based on backstepping to mitigate these disturbances, and an event-triggered control scheme is designed to realize the two-part consensus control within the multi-AUV system. Through rigorous theoretical analysis, it is shown that the system achieves asymptotic steadiness and is free from Zeno behavior under the proposed event-triggered control scheme. Finally, numerical simulations confirm the efficiency of the regulation strategy in achieving formation separation within the multi-AUV, where the trajectory tracking errors of individual AUVs gather in a compact vicinity close to the source, and the structure convergence is achieved, with the absence of Zeno behavior also demonstrated.

High-Efficiency Clustering Routing Protocol in AUV-Assisted Underwater Sensor Networks.

Currently, underwater sensor networks are extensively applied for environmental monitoring, disaster prediction, etc. Nevertheless, owing to the complicacy of the underwater environment, the limited energy of underwater sensor nodes, and the high latency of hydroacoustic channels, the energy-efficient operation of underwater sensor networks has become an important challenge. In this paper, a high-efficiency clustering routing protocol in AUV-assisted underwater sensor networks (HECRA) is proposed to address the energy limitations and low data transmission reliability in underwater sensor networks. The protocol optimizes the cluster head selection strategy of the traditional low-energy adaptive clustering hierarchy (LEACH) protocol by introducing the residual energy and node degree in the cluster head selection phase and performs some optimizations in the cluster formation and data transmission phases, including selecting clusters for joining by ordinary nodes based on the residual energy of the cluster head nodes and weight computation based on the depth and residual energy of the cluster head nodes to select the optimal message forwarding nodes. In addition, this paper introduces an autonomous underwater vehicle (AUV) as a dynamic relay node to improve network transmission efficiency. According to the simulation results, compared with the existing LEACH, the energy efficient routing protocol based on layers and unequal clusters in underwater wireless sensor networks (EERBLC) and energy-efficient clustering multi-hop routing protocol in a UWSN (EECMR), the HECRA significantly improves network lifetime, the residual node energy, and the number of successfully transmitted packets, which can effectively prolong network lifetime and ensure efficient data transmission.

Navigating uncharted waters: Legal challenges and the future of unmanned underwater vehicles in maritime military cyber operations

The evolving landscape of maritime security is increasingly shaped by the integration of cyber technologies into naval operations, posing complex legal challenges under international maritime law. This paper examines the 2016 Bowditch incident, in which a U.S. Navy Unmanned Underwater Vehicle was detained by the Chinese navy, as a case study for comprehending the legal implications of maritime military cyber operations. The research delves into the ambiguous legal standing of unmanned underwater vehicles and their activities, particularly within the framework of the United Nations Convention on the Law of the Sea. Through a detailed analysis of the incident, this study identifies significant gaps in existing legal frameworks and advocates for the urgent need to augment international law to adequately address the emergence of cyber technologies in maritime military operations. The findings underscore the crucial role of international consensus in defining the legal status of unmanned maritime systems and the norms governing maritime military cyber operations, essential for upholding global maritime security and stability.

Numerical Investigation of Hydrodynamic Characteristics of a Rim-Driven Thruster Coupled with an Underwater Vehicle

In this paper, the hydrodynamic characteristics of a rim-driven thruster (RDT) behind the hull of an underwater vehicle are investigated. The studied underwater vehicle is the benchmark DARPA (Defense Advanced Research Projects Agency) suboff model, with and without full appendages. In order to verify and validate the numerical model, a grid sensitivity analysis is made for the AFF-1, AFF-8 and the ducted propeller cases, respectively. Then, the resistance and pressure distribution over the surface of the suboff with and without appendages are compared with available experimental measurements and good correlations were observed. As for the propeller, a well-studied ducted propeller, the 19A duct in combination with Ka-47 blades, is employed, and the numerical results exhibit a close relationship with the available experimental data under a wide range of advance coefficients. Afterwards, the self-propulsion characteristics of the suboff models propelled by RDTs using different duct configurations are studied, more specifically, the unsteady effects of the flow field induced by the interactions between propeller and hull under various working conditions. The results indicate that due to the influence of the hull, the RDTs operate in different working conditions compared to open water and exhibit distinct hydrodynamic characteristics. Moreover, the duct profile can have a significant effect on the unsteady pressure fluctuations in the flow field, especially in the vicinity of the propeller.

Adaptive hierarchical interval type-2 fuzzy control for trajectory tracking of an underactuated AUV with uncertain dynamics

In this study, an adaptive hierarchical interval type-2 fuzzy control (AHIT2FC) scheme is presented for three-dimensional (3D) trajectory tracking control of an underactuated autonomous underwater vehicle (AUV), which has only three independent control inputs and is subject to partially parametric uncertainty and unknown external disturbances. To decrease reliance on hydrodynamic parameters, an interval type-2 fuzzy logic system (IT2FLS) is utilized, which exhibits superior capabilities in handling high levels of uncertainties prevalent in the underwater environment as compared to a type-1 fuzzy logic system. However, the traditional fuzzy system structure encounters the “curse of dimensionality” issue, which results in high computational complexity and imposes a significant burden on the limited computing resources underwater. The proposed AHIT2FC framework, based on a hierarchical structure, can substantially enhance computational speed while ensuring excellent control performance. Subsequently, Lyapunov’s theory is adopted to guarantee that all the tracking errors in the closed-loop system are semiglobally uniformly bounded (SGUB). Finally, comparative simulation results demonstrate the effectiveness and superiority of the proposed AHIT2FC scheme.

Noisy Dueling Double Deep Q-Network algorithm for autonomous underwater vehicle path planning.

How to improve the success rate of autonomous underwater vehicle (AUV) path planning and reduce travel time as much as possible is a very challenging and crucial problem in the practical applications of AUV in the complex ocean current environment. Traditional reinforcement learning algorithms lack exploration of the environment, and the strategies learned by the agent may not generalize well to other different environments. To address these challenges, we propose a novel AUV path planning algorithm named the Noisy Dueling Double Deep Q-Network (ND3QN) algorithm by modifying the reward function and introducing a noisy network, which generalizes the traditional D3QN algorithm. Compared with the classical algorithm [e.g., Rapidly-exploring Random Trees Star (RRT*), DQN, and D3QN], with simulation experiments conducted in realistic terrain and ocean currents, the proposed ND3QN algorithm demonstrates the outstanding characteristics of a higher success rate of AUV path planning, shorter travel time, and smoother paths.

A Method for Tracking an Underwater Pipeline from Stereo Images Using an Autonomous Underwater Vehicle

The problem of tracking an underwater pipeline (UP) is considered in the context of an inspection mission. It is assumed that the diameter of the cylindrical pipe is known. To solve this problem, a tracking method is proposed, based on searching and calculating the center line of the UP, and determining the relative position of the autonomous underwater robot (AUV) and UP in the coordinate system of the AUV camera. Unlike well-known analogues, in which the solution is based on recognizing and constructing the boundaries of the UP in images, the proposed method searches for the true position of the center line of the UP on a set of possible options by checking their veracity. Possible options for the spatial position of the search centerline of the current UP section are generated by varying the direction of the beam in the horizontal and vertical plane. The starting point of the ray is the end point of the centerline of the previous section. The veracity criterion is to check that the 3D point features constructed in the scene belong to the cylindrical surface of the UP. The generation and matching of pointfeatures in images of a stereo pair is carried out using the SURF detector. The choice of the correct direction of the center line of the current UP section is ultimately made by voting. The end point of the center line of the current section is determined taking into account the calculated common visibility area with the previous section of the UP. To evaluate the effectiveness of the method, computational experiments were carried out on virtual scenes. The effectiveness was assessed by the accuracy of UP localization (in the AUV coordinate system) and by the speed of calculations in comparison with: a) the first version of this method, based on the use of a vectorized form of images; b) analogues using the Canny and Hough Transform detectors. The stability of the method to the accumulation of navigation accuracy errors during long-term tracking of UPs was also assessed.

Modeling and design for metal hydride-based hydrogen storage systems in underwater PEMFC applications

Utilizing metal hydride materials presents a promising avenue for establishing a highly concentrated hydrogen medium suitable for onboard vehicle applications, including underwater contexts. This paper introduces a design solution devised to estimate the characteristics of a metal hydride-based hydrogen storage system tailored for underwater vehicle deployment. The solution facilitates sensitivity analysis across various parameters by offering system mass and volume estimations. The findings highlight the significance of thermodynamic properties and operational conditions in determining the suitability of metal hydrides for compact and efficient hydrogen storage. The study underscores the importance of refueling time, L/D ratio, cooling fluid temperature and velocity, and hydrogen storage capacity in influencing system mass, volume, and thermal management. The model provides insights into the design and optimization of metal hydride-based hydrogen storage systems, offering a comprehensive approach to enhancing performance and reliability for underwater applications.

Arbitrary 6-DOF large-angle tracking control for autonomous underwater vehicles via stochastic contraction stability and rotation matrix-based attitude representation

Arbitrary 6-DOF large-angle tracking control for autonomous underwater vehicles via stochastic contraction stability and rotation matrix-based attitude representation

Nonlinear model predictive dynamic positioning of a remotely operated vehicle with wave disturbance preview

Exploiting preview information of disturbances within robot control is an effective method of handling state perturbations. For underwater vehicles operating in wave-dominated environments, disturbances significantly influence vehicle response and pose a threat to operational safety. In consideration of this, a complete end-to-end control architecture is developed in this work for disturbance rejection during station keeping tasks under wave perturbations, encompassing a nonlinear model predictive controller (NMPC) combined with a deterministic sea wave predictor (DSWP). The wave predictor exploits a continuous measurement of the wave elevation at a location upstream of the vehicle to form a forecast of the temporal evolution of the wave elevation at the vehicle location. The predicted wave parameters are then used to estimate the impending wave-induced hydrodynamic loading, enabling explicit consideration of accurate short-term disturbance forecasts within the controller, ensuring this preview is incorporated in the optimised control sequence. Experimental testing confirms the validity of the wave predictor, producing RMSE as low as 0.017 m. The proposed strategy is then simulated under various wave conditions, optimising control actions inclusive of the preview information. The NMPC outperforms a similar disturbance mitigating feed-forward controller, with average improvements of up to 52% and is found to perform best even with noisy, lower accuracy wave predictions, as well as with communication time delays, providing a high degree of robustness. This demonstrates the potential of the proposed control framework to effectively tackle disturbance mitigation of underwater vehicles subject to large magnitude wave disturbances, expanding the operational envelop of autonomous systems towards forbidding ocean environments.

Performance evaluation of the static thrust and efficiency of an actuated biomimetic jellyfish model

Abstract This study offers an in-depth analysis of a jellyfish-inspired robotic model designed to simulate the expansion and contraction mechanisms found in natural jellyfish. By employing variable Duty Cycles to replicate the cyclic motions of the jellyfish, the thrust generation of the model is measured through static thrust assessments using a load cell, while its efficiency is evaluated using the Thrust-to-Power Ratio, TPR. The findings indicate that increasing the amplitude of the motion leads to more complex wave patterns, which in turn reduce the peak-to-peak force generated. Specifically, a 25% increase in the A/D ratio results in a significant 30% decrease in static thrust. It was observed that higher actuation frequencies do not notably influence thrust generation when the A/D ratio remains constant. Importantly, the TPR was found to be highest at an A/D ratio of 0.10, with an increase of up to 6% observed at higher Duty Cycles, suggesting that smaller actuation amplitudes are more efficient in enhancing thrust performance. These results highlight the critical role of amplitude in the efficiency of static thrust generation within a given Duty Cycle, emphasizing that lower amplitudes generally lead to higher efficiency. The study underscores the importance of optimizing both geometric and kinematic parameters for improved propulsion performance. It suggests that future research should focus on fine-tuning A/D ratios and Duty Cycles, as well as exploring alternative geometric configurations and materials to further enhance the hydrodynamic performance of jellyfish-inspired robots. The insights gained from this study provide a valuable foundation for developing more efficient and effective bio-inspired underwater vehicles.

Quaternion-based fixed-time tracking control for an autonomous underwater vehicle with consideration of measurement bias

This article investigates trajectory and attitude tracking control problem of a 6-degree of freedom (DOF) autonomous underwater vehicle (AUV) subject to measurement bias and external disturbance. First, the model dynamics of rotational channels are established by unit-quaternion, which possesses simplicity and broader applicability compared to the Euler angle such that the maneuver signal could be uniquely determined. Meanwhile, by introducing constraint of the logarithm function and initial value, the unwinding phenomenon existing in rotation motion can be avoided tactfully. Considering the high requirement for sensor accuracy, the resulting measurement bias in position and velocity channels, making AUV into a mismatched system and bring the uncertain term in the process of controller design. Therefore, the echo state network (ESN) with online updates performance is applicable to approximate uncertain term simultaneously generated by measurement bias and unknown external disturbance. Then, by incorporating composite hyperbolic tangent function, the quasi-fast terminal sliding mode (QTSM) surface is constructed to realize the fixed-time convergence peculiarity of the AUV tracking system. Compared with the existing methods, the proposed algorithm can regulate artificially the stable schedule of the AUV tracking system and possess the capacity of bias tolerance and anti-disturbance. Finally, simulation results verify the validity and feasibility of the developed control algorithm.

Research on Autonomous Underwater Vehicle Path Optimization Using a Field Theory-Guided A* Algorithm

Autonomous Underwater Vehicles (AUVs) have become indispensable tools in the fields of ocean exploration, resource exploitation, and environmental monitoring. Path planning and obstacle avoidance are crucial to improve the operational capabilities of AUVs. However, most algorithms focus only on macro-global or micro-local path planning and rarely address both problems simultaneously. This study extends the classical A* algorithm by integrating field theory principles. The resulting Field Theory Augmented A* (FT-A*) algorithm combines the constraints in the AUV’s dynamics and the threats posed by obstacles to ensure a safe navigation distance. The paths planned by the FT-A* algorithm were subsequently re-optimised in conjunction with Dubins curves, taking into account path smoothness and redundant node problems. Simulation experiments confirm that the improved algorithm can effectively help AUVs navigate safely around obstacles, which greatly improves navigation safety and increases the arithmetic power and navigation efficiency. The proposed FT-A* algorithm provides a robust solution for underwater path planning and demonstrates great practical value for AUV operation in complex marine environments.

Dynamic Docking Anti‐Disturbance Control of Overactuated AUV: System, Method, and Lake Trails

ABSTRACTDynamic docking control technology is crucial for autonomous underwater vehicles (AUV) to perform tasks underwater. To enhance the docking success rate of AUVs during dynamic docking, this paper presents a robust anti‐disturbance control algorithm specifically designed for overactuated AUV dynamic docking scenarios. During a dynamic docking mission, the AUV's depth control is adversely affected by the complex flow field generated by the underwater recovery device. To address this issue, this research proposes an AUV control scheme that combines an extended state observer (ESO) with a combined disturbance rejection method of the elevator‐vertical tunnel controller. First, an ESO is constructed to estimate and compensate for complicated disturbances such as model uncertainty and environmental disturbances. These estimations are then incorporated into the control law to mitigate the effects of the complicated flow field interference experienced during the AUV's dynamic docking process. Second, as turbulence intensifies at the end of the docking stage, the vertical thrust allocation is achieved using a hyperbolic tangent transition function. This ensures the stability of the AUV's attitude and depth, thereby enabling precise docking. Finally, the effectiveness of the proposed control algorithm is verified through lake trials and compared against the classic proportional‐integral‐differential (PID) and active disturbance rejection control (ADRC) methods. The trial results indicate that the proposed control algorithm significantly reduces the pitch and depth errors of the AUV, resulting in a remarkable 91% success rate for dynamic docking (based on 45 tests). The lake trials demonstrate that the proposed control algorithm is highly precise and robust.

Investigating the vibration characteristics of vector thrusters under complex inclination angle variations

ABSTRACT As autonomous underwater vehicles advance, the study of design and dynamic characteristics of vector thrusters is of significant engineering importance. In this paper, the mechanical model based on a vector thruster with a universal joint is established, followed by the analysis of its vertical torsional coupled vibration across different modes of inclination angle variations. Then, a simulated calculation of dynamic characteristics is carried out by the Newmark method. Finally, following the introduction of several structure parameters, the characteristics of vertical and torsional vibrations of the driven shaft under impact load are studied. The results show that the increase in the stiffness ratio can reduce not only the amplitude of angular displacement but also the stability time of vibration. The combinations of inclination angles should be selected preferentially, and the action value of actuators must be reasonably adjusted to ensure the inclination angle ratio remains as small as possible in the thruster control.

Self-Propulsive Property of Flexible Foil Undergoing Traveling Wavy Motion: A Numerical Investigation

The propulsive characteristics of self-propelling 3D flexible foil are numerically studied. Two kinds of dynamic boundary techniques, namely the dynamic mesh technique and overlapping mesh technique, are used to realize the self-propulsion of flexible foil. The effects of aspect ratio (AR), characteristic thickness (d), and section shape on propulsive characteristics are numerically studied. Results demonstrate that the moving velocity increases monotonically with the consistent growth of AR, and a linear relationship is found between them. The peak value of propulsive efficiency can be acquired when AR = 1.0. Moreover, the growth of d shall produce a negative effect on moving velocity. It is suggested that the value of d should be smaller than 0.15 for the sake of acquiring high propulsive efficiency. As for the section shape effect, the foil with a rectangular shape presents the worst propulsive property, while the NACA0015 foil exhibits the best one. Furthermore, the typical vortex structures are also exhibited and analyzed. The conclusions acquired in this study are of great significance for designing a bionic underwater vehicle.

Motion control of autonomous underwater vehicle based on physics-informed offline reinforcement learning

Online reinforcement learning (RL) methods for autonomous underwater vehicles (AUV) are time-consuming and unsafe due to the need for real-world interaction. Offline RL methods can improve efficiency and safety by training with dynamic models, but an accurate model for AUV is difficult to obtain due to its highly nonlinear dynamics. These limit the application of RL methods in AUV control. To solve this issue, we propose physics-informed model-based conservative offline policy optimization (PICOPO). It offers the advantages of small dataset, strong generalizability and high safety by combining the physics-informed dynamic modelling method and the offline RL technique. First, the PICOPO constructs a physics-informed model based on a small offline dataset to serve as the digital twins (DT) of the actual AUV. This DT can forecast the long-term motion states of AUV with high-precision. The RL-based controller is then trained offline within this DT, eliminating the need for real-world interaction and allowing direct deployment to the AUV without fine-tuning. In this paper, simulations and field tests are carried out to evaluate the proposed method. Our results demonstrate that PICOPO achieves accurate motion control with just 2000 samples and enables zero-shot sim-to-real transfer, showcasing strong generalizability across various motion control tasks.

Propulsive Performance of Bionic Underwater Vehicle Based on Four Flexible Oscillating Foils: A Numerical Investigation

Propulsive Performance of Bionic Underwater Vehicle Based on Four Flexible Oscillating Foils: A Numerical Investigation