Buoyancy-driven Underwater Gliders Research Articles

Development of hybrid neural network and current forecasting model based dead reckoning method for accurate prediction of underwater glider position

Buoyancy-driven underwater gliders are considered to be advanced platforms for large-scale ocean exploration. However, it is greatly affected by ocean currents, and traditional dead reckoning navigation methods are inadequate in accurately predicting its own position, causing great difficulties in underwater target detection. To solve this problem, a navigation estimation method based on the current prediction model and a convolutional neural network-long short-term memory hybrid neural network is proposed in this paper to predict the position of underwater gliders. Analysis of the experimental results shows that the hybrid neural network model trained with underwater glider sea trial data and simulated motion data can predict the glider speed more accurately than the current-assisted dead reckoning navigation, and can predict the relative position of the glider more accurately with the updated feedback from the current prediction model. The test results show that the data-driven prediction method can greatly help to predict the position of underwater gliders in the absence of other underwater positioning and navigation equipment.

Unsupervised time–frequency environment perception model for underwater vehicle in irregular ocean

Dynamic ocean environments are difficult to monitor and affect the motion balance of underwater vehicles. Existing unsupervised environment perception methods have poor performance and less consideration of environment and vehicle interaction effects. This paper proposes a novel unsupervised time–frequency environment perception model for underwater vehicles in the irregular ocean. First, the observed ocean information is transformed into the time–frequency space based on the wavelet transform. After that, an adaptive dual-threshold diagnosis model is proposed to automatically extract and locate ocean features and depress the background noise. Then, the environment-vehicle interaction model is derived to quantitatively predict the state change of underwater vehicles caused by environmental features. Finally, extensive experiments on the novel buoyancy-driven underwater glider and publicly South China Sea dataset are conducted to verify the effectiveness of the proposed method. The result shows that the diagnosis model can better perceive the ocean environment, and the performance outperforms traditional unsupervised statistical and supervised learning methods. The thermocline detection accuracy is 100%, and the location accuracy is 98.73%. The environment-vehicle interaction model can accurately describe the state changes of underwater vehicles under environmental influence, with an average accuracy of 94.88%.

Dynamic modeling and motion control of a novel conceptual multimodal underwater vehicle for autonomous sampling

This paper presents a conceptual design of a novel multimodal underwater vehicle that integrates the merits of the Argo profiling float, the buoyancy-driven underwater glider and the propeller/rudder-driven underwater vehicle, which serves as a long-endurance and highly maneuverable platform for multiple-water-column ocean sampling with high spatiotemporal resolution. Key design principles of this multimodal underwater vehicle are firstly formulated to enable mode switching. The mathematical model of this proposed vehicle is derived based on unit quaternions for the three modes of locomotion, namely, Argo mode, zigzag gliding mode and propeller/rudder-driven mode (PR mode). Heading deviation arises during transition between Argo mode and zigzag gliding mode is fully revealed. To tackle this key challenge, a multi-level motion controller is developed for this hybrid vehicle, which not only guarantees rapid mode switching, but also allows the vehicle to be capable of traveling between adjacent columns in zigzag gliding mode, vertical sampling in Argo mode as well as heading correction and position compensation in PR mode. The feasibility of the mode transition, the property of the heading deviation and the performance of the devised control scheme are validated and analyzed via a series of numerical simulations and experiments.

Smartfloat: A Multimodal Underwater Vehicle Combining Float and Glider Capabilities

This paper proposes a novel hybrid underwater vehicle, the Smartfloat, which integrates the concept of buoyancy-driven underwater gliders and conventional profiling floats. The vehicle is presented to address the challenges in ocean monitoring, such as the multidisciplinary observations of long-range transport of the mesoscale features with high spatial-temporal resolution. The vehicle combines the mechanisms of Argo profiling float and the underwater glider, with the application of a special designed attitude control system and the ingenious general arrangement. The vehicle can switch the operating mode between drifting mode and gliding mode. Such a multimodal vehicle would merge the benefits of making measurements in a very energy-efficient way when drifting with the currents in Argo mode, and operating as an underwater glider in glider mode when it is needed to cross the ocean eddies, ocean fronts, filaments, or some stirring regions. In this paper, a proof-of-concept platform including its concept of operations, the main components and subsystems design, and the correlative mathematical analysis is introduced in detail. Experiments in field trials are presented to characterize and illustrate each mode of operation and repeated mode transitions. The results demonstrate the feasibility and the good performance of the proposed vehicle.

Attitude control of underwater glider combined reinforcement learning with active disturbance rejection control

Buoyancy-driven underwater gliders are highly efficient winged underwater vehicles driven by modifying the net buoyancy and internal shape. Many advantages, such as wide cruise range, less power consumption, low noise, and no pollution, make the underwater glider an important platform for marine environment observation and ocean resource exploration. For the wide cruise range, attitude control of underwater glider becomes the core technology. In this paper, the underwater glider named OUC-III has been developed for marine observation. To control the attitude of glider, the kinematic and dynamic models of it have been calculated by mathematical analysis. Furthermore, a novel control algorithm is proposed to control the attitude of glider. The algorithm is combined reinforcement learning with Active Disturbance Rejection Control (ADRC) and compared with classical ADRC by simulation based on the dynamic model of OUC-III. The simulation experimental results indicate that the proposed algorithm compensates well for the ocean current disturbances on OUC-III attitude control mission and it obtains high-precision and high-adaptive control ability.

Study on docking guidance algorithm for hybrid underwater glider in currents

The development of a novel type of hybrid underwater glider (HUG) that combines the advantages of buoyancy-driven underwater glider and propeller-driven autonomous underwater vehicle (AUV) has recently received considerable interest. HUG is designed with a rotatable thruster to ensure the enough maneuverability of the vehicle for underwater docking. Unlike the fixed funnel-type dock, the dock proposed here can rotate actively to allow the vehicle to approach the docking station from most range of directions providing better accessibility for the vehicle. Considering that the ocean current may have a significant impact on the HUG, a pursuit guidance algorithm with current compensation is presented. The performance of the guidance algorithm is compared with other existing guidance algorithms, such as pure pursuit guidance and proportional navigation guidance by simulation based on the dynamic model of HUG. Moreover, underwater docking experiments are conducted to validate the feasibility of the docking system and the effectiveness of the proposed guidance algorithm. The experimental results indicate that the proposed algorithm compensates well for the current disturbances on HUG docking mission and the HUG can dock with the rotatable dock entrance successfully.

A hybrid-driven underwater glider model, hydrodynamics estimation, and an analysis of the motion control

An autonomous hybrid-driven glider is a new class of autonomous underwater glider that integrates the concept of a buoyancy-driven underwater glider and a conventional autonomous underwater vehicle (AUV). This glider has multi-functionality that enables it to overcome the speed and maneuverability limitations of buoyancy-driven gliders. Thus, this paper presents a mathematical model of the hybrid-driven glider, an estimation of the hydrodynamics and an analysis of the motion control. A Newtonian approach has been used to model the glider under the influence of water current. In addition, the hydrodynamics were estimated by using a Strip theory and a computational fluid dynamic (CFD). In order to analyze the motion of the glider, a Neural Network Predictive Control (NNPC) has been designed and its performance has been compared with the Model Predictive Control (MPC) and Linear Quadratic Regulator (LQR). The simulation results demonstrated that the Neural Network Predictive Control (NNPC) produced better control performance than the performance of the MPC and LQR when dealing with disturbances. In addition, the results also demonstrate the hydrodynamic response of the glider over the velocity, angle of attack and sideslip angle.

Underwater source localization using a hydrophone-equipped glider

Buoyancy-driven underwater gliders are autonomous underwater vehicles that were originally developed to collect oceanographic data. CMRE is studying the use of this technology for the characterization of denied areas, including alternate sensor payloads and applications. During the Rapid Environmental Assessment phase of the Noble Mariner 2012 NATO exercise, Conducted in Gulf of Lions in September 2012, an omnidirectional hydrophone was mounted on a shallow water glider to sample the spatial distribution of the acoustic and oceanographic fields at different ranges and depths. This paper presents a study of the potential to localize acoustic sources by using the acoustic and environmental data collected by the glider. During the experiment, a bottom moored acoustic source was deployed in an area with benign bathymetry. Continuous wave and frequency modulated pulses were broadcast for approximately 6 h. The glider was flying along predefined tracks and the distances from the source were typically from 5 to 9 km. A Ray tracing model is used to evaluate the arrival structures of the acoustic signal, and to estimate the source location. The impact of the range dependent water column sound speed profile on the uncertainty of the source localization is also discussed.

Analysis of the Propulsion Efficiency of Buoyancy-driven Underwater Gliders

As a new type of autonomous underwater vehicle, the underwater glider has many advantages such as long endurance, high propulsion efficiency, and low self-noise due to the application of buoyancy-driven technology.It has promising applications in the oceanographic survey and ocean exploration.The propulsion energy when the underwater glider dives and ascends with a constant velocity is analyzed.The propulsion efficiency is then defined on the basis of this analysis and the calculation methods are derived with and without consideration of the extra energy losses.Investigation is also conducted to figure out factors that influence the efficiency and methods for improving the efficiency.The lift-to-drag ratio of wings and the extra energy losses are found to be the main factors influencing the propulsion efficiency and the lift-to-drag ratio of wings is the most important factor.In order to reveal the relationships between the propulsion efficiency and the structure parameters and the forms of the glider wings, the effect of the aspect ratio and the sweep angle of wings on the lift-to-drag ratio are investigated by using an empirical equation, and the lift-to-drag ratio of wings with same area but different forms are also calculated by using computational fluid dynamics software Fluent 6.2.The results provide an insight into the underwater glider design.

MATLAB-based simulation of buoyancy-driven underwater glider motion

The mass configuration of the buoyancy-driven underwater glider is decomposed and defined. The coupling between the glider body and its internal masses is addressed using the energy law. A glider motion model is established, and the corresponding simulation program is derived using MATLAB. The characteristics of the glider motion are explored using this program. The simulation results show that the basic characteristic of a buoyancy-driven underwater glider is the periodic alternation of downward and upward motions. The glider’s spiral motion can be applied to missions in restricted regions. The glider’s horizontal velocity, gliding depth and its motion radius in spiral motion can be changed to meet different application purposes by using different glider parameter designs. The simulation also shows that the model is appropriate and the program has strong simulation functions.