Automatic Underwater Vehicle Research Articles

Adaptive Sliding Mode Control for AUV based on Backstepping and Neural Networks

Abstract Automatic Underwater Vehicle (AUV) inevitably suffers from various interference issues in the marine environment. Due to the limitations of underwater measurement methods and tools, as well as the complexity of AUV's control parameters in the underwater environment, dynamic measurement errors are easily cascaded and amplified, leading to the failure of the control system. In response to this phenomenon, this paper focuses on overcoming the influence of internal and external unknown factors in the tracking and control process of AUV trajectories. The internal factors are mainly the uncertainties generated by the model mismatch problem, and the external factors are mainly from the dynamic ocean currents. The AUV disturbances mainly affect the kinematics and dynamics levels directly or indirectly. In order to achieve the control of internal and external dynamic disturbances, we have designed a control system that employs backstepping (BS) and a sliding mode controller (SMC) with RBF neural networks to achieve the cascaded control of kinematics and dynamics. Comparison of multiple sets of simulations shows that our proposed algorithm has excellent anti-disturbance performance for dynamic conditions with low measurement accuracy.

An in-motion alignment method of AUV SINS/DVL navigation system based on FGO

The navigation system of automatic underwater vehicle (AUV) usually needs to wait for about 20 min for initial alignment before running. However, most of in-motion alignment methods have no re-integration process, so the positioning error caused by early attitude error will remain in the positioning result.Besides, current in-motion alignment methods are usually based on recursive Extended Kalman Filter (EKF). In nonlinear systems, the accuracy of recursive optimization will be reduced.In this study, a method of in-motion alignment using factor graph is proposed. This method optimizes the states of the whole trajectory in batch. Experiments show that the position accuracy of the method proposed is much better than the existing method.

Research on 3D trajectory tracking of underactuated AUV under strong disturbance environment

Underactuated AUV (automatic underwater vehicle) possess a lower number of actuators than its degrees of freedom, which helps to conserve energy and improve maneuverability in complex underwater environments. However, the complex and variable disturbance environment under the sea makes the control of underactuated AUVs extremely difficult, so it is urgent to study controllers with strong disturbance capability. This paper focuses on 3D trajectory tracking under strong disturbance environment. The 5-DOF underactuated AUV kinematics and dynamics equations are established and simplified by adopting appropriate assumptions. The NDOB (nonlinear disturbance observer) combined with sliding mode control is utilized to complete the 3D trajectory tracking of underwater unmanned cluster under strong disturbance environment. The effectiveness of the control algorithm is verified through multiple sets of simulation experiments. Through the comparison of experimental data, the anti-disturbance ability of the algorithm proposed in this paper is more than 80% higher than that of the adaptive sliding mode controller under strong disturbance environment. This research provides an effective solution for 3D Trajectory tracking of underactuated AUV, which is of great practical significance for improving the efficiency of underwater exploration, ocean observation, and underwater operations.

A novel RBFNN-UKF-based SOC estimator for automatic underwater vehicles considering a temperature compensation strategy

Accurate state of charge (SOC) estimation of batteries is a prerequisite for the reliable operation of automatic underwater vehicles. Currently, the accuracy of traditional SOC evaluation algorithms deteriorates significantly at low temperatures and low SOCs. Hence, a novel SOC estimator is proposed in this study, consisting of three efforts. Firstly, a new radial basis function neural network (RBFNN) battery model is built to replace the equivalent circuit model (ECM) for SOC estimation. Then, based on the relation between SOC and terminal voltage at a different temperature, a temperature compensation strategy is developed, which is an effortless operation and does not increase the computational burden. Finally, incorporating the new battery model, the temperature compensation strategy, and the unscented Kalman filter (UKF), a novel SOC estimation frame expressed as RBFNN-UKF is designed.The performance of the proposed method, including accuracy, generalization ability, and low-temperature adaptation, is evaluated systematically based on a publicly available dataset, where the inaccurate initial value and the current errors are added in each case. The results show that: (1) The SOC estimation curve of RBFNN-UKF can converge quickly to the reference curve and maintain good consistency even at low SOCs; (2) The proposed method exhibits excellent generalization capability for different dynamic cycles; (3) At low temperatures, the SOC estimation error of the RBFNN-UKF is reduced to 17 % of traditional ECM-UKF algorithm with the recursive least squares parameter identification method. The above results indicate that the proposed RBFNN-UKF-based SOC estimator has a high application value for AUVs and other vehicles working in complex environments.

MTrajPlanner: A Multiple-Trajectory Planning Algorithm for Autonomous Underwater Vehicles

Trajectory planning is a crucial task in designing the navigation systems of automatic underwater vehicles (AUVs). Due to the complexity of underwater environments, decision makers may hope to obtain multiple alternative trajectories in order to select the best. This paper focuses on the multiple-trajectory planning (MTP) problem, which is a new topic in this field. First, we establish a comprehensive MTP model for AUVs, by taking into account the complex underwater environments, the efficiency of each trajectory, and the diversity among different trajectories, simultaneously. Then, to solve the MTP, we develop an ant colony-based trajectory optimizer, which is characterized by a niching strategy, a decayed alarm pheromone measure, and a diversified heuristic measure. The niching strategy assists in identifying and maintaining a diverse set of high-quality solutions. The use of decayed alarm pheromone and diversified heuristic further improves the search effectiveness and efficiency of the algorithm. Experimental results on practical datasets show that our proposed algorithm not only provides multiple AUV trajectories for a flexible choice, but it also outperforms the state-of-the-art algorithms in terms of the single trajectory efficiency.

Efficient Asynchronous Federated Learning for AUV Swarm.

The development of automatic underwater vehicles (AUVs) has brought about unprecedented profits and opportunities. In order to discover the hidden valuable data detected by an AUV swarm, it is necessary to aggregate the data detected by AUV swarm to generate a powerful machine learning model. Traditional centralized machine learning generates a large number of data exchanges and faces problems of enormous training data, large-scale models, and communication. In underwater environments, radio waves are strongly absorbed, and acoustic communication is the only feasible technology. Unlike electromagnetic wave communication on land, the bandwidth of underwater acoustic communication is extremely limited, with the transmission rate being only 1/105 of the electromagnetic wave. Therefore, traditional centralized machine learning cannot support underwater AUV swarm training. In recent years, federated learning could only interact with model parameters without interacting with data, which greatly reduced communication costs. Therefore, this paper introduces federated learning into the collaboration of an AUV swarm. In order to further reduce the constraints of underwater scarce communication resources on federated learning and alleviate the straggler effect, in this work, we designed an asynchronous federated learning method. Finally, we constructed the optimization problem of minimizing the weighted sum of delay and energy consumption, relying on jointly optimizing the AUV CPU frequency and signal transmission power. In order to solve this complex optimization problem of high-dimensional non-convex time series accumulation, we transformed the problem into a Markov decision process (MDP) and use the proximal policy optimization 2 (PPO2) algorithm to solve this problem. The simulation results demonstrate the effectiveness and superiority of our method.

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.

Circuit Coupling Model Containing Equivalent Eddy Current Loss Impedance for Wireless Power Transfer in Seawater

Nowadays, as the whole world put more emphasis on ocean resource exploration, the use of automatic underwater vehicles (UAVs) comes to be increasingly frequent. Inductive wireless power transfer (IWPT), as a power transfer solution with high safety and exibility, is quite promising applied in UAV power supply. However, when applied underwater, IWPT efficiency decreases due to eddy current loss (ECL) caused by high conductivity of water medium. In order to analyze IWPT output characteristics in seawater, this paper proposes a coupling circuit model involving equivalent eddy current loss impedance (EECLI), which is derived via three- coil model. On the one hand, it is found that splitting frequency still exists in IWPT under seawater. On the other hand, EECLI is independent to coil distance, but proportional to operation frequency. The validity of the proposed model for IWPT system with coils in small size (coil outer diameter 12 cm, system resonant fre- quency 570 kHz) is verified by experiment, which means it is available for IWPT system design and analysis.

Simulation of the controlled movement based on the complexity principle for an automatic underwater vehicle

The paper deals with the mathematical modeling of the controlled motion of an automatic underwater vehicle under conditions of inaccuracy and uncertainty of information support. Methodological and theoretical approaches based on the application of the principle of complexity and fuzzy logic are proposed.

Propulsive Characteristics of Twin Oscillating Airfoils

The bionic propulsion can be used on the aerostat and other automatic vehicles. The general single oscillating tail fin can induce the yawing and whole airship rolling because of the lateral force and the gravity moment of heavier oscillating tail fin. The parallel twin oscillating tail fins by symmetrical swing mode can eliminate the lateral force and gravity moment through the symmetrical swing of the two tail fins. The propulsive characteristics of parallel twin fins have not been investigated up to now. In this paper, we investigated the propulsive characteristics and mechanism of parallel twin oscillating airfoils using consistent and symmetrical swing mode. By using the numerical calculation and analysis, the consistent swing mode may decrease the total propulsion efficiency. While, the symmetrical swing mode can improve the propulsion efficiency and reduce the lateral force and gravity moment. This mode can be used to propel the aerostat and automatic underwater vehicles efficiently.

Acoustic beam profile-based rapid underwater object detection for an imaging sonar

In sonar applications, the ability to locate underwater structures such as pipelines and a wreckage of submerged airplane is important. To investigate extensive sections of the seabed within a limited time period, the scanning speed and the reliability of object detection alarms are the most critical factors for finding objects. In this paper, we propose a method to provide an automatic detection alarm indicating the presence of suspected underwater objects using high-speed imaging sonar. The proposed method is based on the cross-correlations between two successive acoustic beam profiles of imaging sonar. The alarm signal alerts human operators or automatic underwater vehicles to suspected objects, which may be a part of or all of the target object. Using this signal as a trigger, the object can then be examined in more detail to determine whether it is the target. We verified the feasibility of the proposed method by indoor and field experiments.

Kalman Filter for Cross-Noise in the Integration of SINS and DVL

The integration of strapdown inertial navigation system and Doppler velocity log (SINS/DVL) is widely used for navigation in automatic underwater vehicles (AUVs). In the integration of SINS/DVL, the velocity measured by DVL in body frame should be projected into navigation frame with the help of attitude matrix calculated by SINS to participate in data fusion. In the process of data fusion based on standard Kalman filter, the errors in calculated attitude matrix are characterized by state variance and process noise while the errors in measurement vector from DVL are by measurement noise. But the above projection will bring process noise into measurement noise, and thus the assumption of the independence between process noise and measurement noise will not stand. In this paper, the forming mechanism of cross-noise in SINS/DVL is studied in detail and Kalman filter for cross-noise is introduced to deal with this problem. Simulation results indicate that navigation accuracy, especially the position accuracy, can be improved when the cross-noise is processed in Kalman filter.

Investigation of CFD Method Simulating Hydrodynamic Performance of AUV with Complicated Shape

Analyze veracity and computing efficiency of direct route drag of axis symmetry revolution body with 2D Computer Fluid Dynamic (CFD) method by comparing to the experiment data, discuss affection of different wall boundary functions to the results when calculating Automatic Underwater Vehicles (AUVs) hydrodynamic performance in CFD method. Find out characters of several meshing strategies when spring-based smooth dynamic model is adopted. Method with ball domain inside, which can simulate all the PMM tests and get reasonable outcome, turned out to be the best choice.

Design and Simulation of High Altitude Air-Launched Automatic Underwater Vehicles

In this paper, an high altitude air-launched automatic underwater vehicles (AL-AUV) is designed based on the traditional torpedo-like AUV, REMUS. And an additional ex-range gliding wings unit is assembled on the top of AUV, which enable the AUV to be dropped at high altitude and gliding long distance to reach the signed investigating ocean field. The controllable surface on the wings also enhanced the controllability and flexibility of AUV gliding through the air and the ability against the influence of airflow interference. The AUV’s six DOF gliding model is established and a simulation system of AL-AUV is built with Matlab/Simulink. Analyzing the recorded simulation velocity and pitch characteristics of AL-AUV deployed at varying initial velocities and wing area, the optimized wing is selected.

Predictive S Control of AUV Based on Model of Support Vector Machine

Because of nonlinear dynamic performances and uncertain working environment, precise motion control of Automatic Underwater Vehicle (AUV) has always been a problem. For the time lag and nonlinearity of AUV, a new method called Predictive S Control (PSC) based on model of Support Vector Machine (SVM) is presented. Firstly, in establishing the model of SVM, the fine property of approaching to the nonlinear model is utilized to solve the predictive problem. Then, the control parameters of S controller are optimized by constructing the error function. At last the motion control of AUV is realized. It has been proved that this method is feasible and effective. Using this method, a good control result is obtained in the simulation.

Study on Hydrodunamic Coefficients of Mini Automatic Underwater Vehicle

Maneuverability is an important part of the vehicle’s general abilities.This paper uses sofware Fluent to simulate the planar movement mechanism(PMM) experiment while turbulence modle is adoped.The results of steady-state tests and unsteady-state tests could be analyzed to the hydrodunamic coefficients of a Mini Automatic Underwater Vehicle(AUV)and the dymatic mesh is adoped to simulate the motion of heave,sway,pitch,yaw.Finally, the motion simulation platform was built with the hydrodunamic coefficients and the motion performance of the vehicle was analyzed.

Research on the Hydrodynamics of a Horizontal Trigonal Pectoral Fin Propulsor Actuated by SMA Wires

Inspired by some batoid fishes using horizontal trigonal pectoral fin for propulsion or maneuverability, a micro flexible mimetic propulsor actuated by shape memory alloy (SMA) wires is presented. Firstly, based on the motion characters of the pectoral fin of manta ray, a simplified kinematics model was set up. Secondly, a three-dimensional numerical simulation on the oscillatory fin was performed by computational fluid dynamic (CFD) to investigate the interaction with the surrounding fluid and the propulsive force production. Thirdly, action experiment of the propulsor is done to verify the concept. At last, the propulsive performance of the propulsor is evaluated through thrust force measurement experiments. The experimental results accord with the CFD results well. The propulsor have potential feasibility applying in automatic underwater vehicles (AUV).

What Can Technology Offer the Future Fisheries Scientist – Possibilities for Obtaining Better Estimates of Stock Abundance by Direct Observations

The need for quality data from fisheries abundance surveys for the rational management of the world's major fisheries resources has been steadily increasing. The limitation of fish resources and the heavy exploitation pressure put on these resources have forced the industry to change and adjust strategy accordingly and to develop new and more efficient fishing gears and fish finding instruments. Earlier, the assessment and management was based on models which utilized data primarily from the fishing fleet. However, the lack of continuity and stability caused by the continuously changing fishing techniques, creates uncertainty for the management decisions based on catch data. The experience from 30 to 40 years of scientific surveys has shown that this source of information also involves a great deal of uncertainty. The need for improvements in survey methodology is crucial for improving assessments of all major fish stocks. The great limitation in improving the reliability of survey based abundance estimates is the variability and inconsistency of the data collected at sea. In the development of acoustic surveys the policy has been to continuously improve the technical equipment. New technology has been introduced when sufficient calibration exists so as not to seriously disrupt the time series. In contrast, standardization has been the most dominant philosophy in bottom trawl survey history. Therefore new technology and information has been difficult to implement in survey equipment and procedures. The main challenge in the next century will be to update survey methodology with state-of-the-art technology. Further, combining information from different sources will be the greatest challenge for new research, for example combining data from acoustic and bottom trawl surveys. Underwater observation technology (video, laser, electronic tags, automatic underwater vehicles etc.) will greatly improve our insight on the efficiency and variability of standard survey methodologies. A major difficulty will be to distinguish between and make decisions on the need for additional monitoring and/or modelling based on new technology and information.