Small Autonomous Underwater Vehicle Research Articles

Design and extensibility analysis of a variable buoyancy system for small autonomous underwater vehicles

PurposeA switching depth controller based on a variable buoyancy system (VBS) is proposed to improve the performance of small autonomous underwater vehicles (AUVs). First, the requirements of VBS for small AUVs are analyzed. Second, a modular VBS with high extensibility and easy integration is proposed based on the concepts of generality and interchangeability. Subsequently, a depth-switching controller is proposed based on the modular VBS, which combines the best features of the linear active disturbance rejection controller and the nonlinear active disturbance rejection controller.Design/methodology/approachThe controller design and endurance of tiny AUVs are challenging because of their low environmental adaptation, limited energy resources and nonlinear dynamics. Traditional and single linear controllers cannot solve these problems efficiently. Although the VBS can improve the endurance of AUVs, the current VBS is not extensible for small AUVs in terms of the differences in individuals and operating environments.FindingsThe switching controller’s performance was examined using simulation with water flow and external disturbances, and the controller’s performance was compared in pool experiments. The results show that switching controllers have greater effectiveness, disturbance rejection capability and robustness even in the face of various disturbances.Practical implicationsA high degree of standardization and integration of VBS significantly enhances the performance of small AUVs. This will help expand the market for small AUV applications.Originality/valueThis solution improves the extensibility of the VBS, making it easier to integrate into different models of small AUVs. The device enhances the endurance and maneuverability of the small AUVs by adjusting buoyancy and center of gravity for low-power hovering and pitch angle control.

Cooperative Ocean Survey Method by a UAV and an AUV: State Estimation of the AUV Based on the UAV

Abstract This paper proposes a new concept of the ocean exploration method using an unmanned aerial vehicle (UAV) and an autonomous underwater vehicle (AUV) in cooperation. Conventional ocean survey by AUVs is supported by a ship and humans for deployment, recovery, and positioning during its survey. Therefore, it has been difficult to survey shallow areas that are inaccessible by ships or far from the land without a ship. In this study, however, this problem is solved by using the UAV to support the entire process from the beginning to the end of the survey. The UAV also acts as a positioning reference station for the AUV by deploying an acoustic positioning system. This allows the AUV to perform ocean exploration while estimating its position relative to the UAV. Sea experiments were conducted using a small AUV and UAVs, demonstrating that although the UAVs were manually controlled, the UAV and AUV can perform the entire exploration process from the beginning to the end, and especially that the AUV can estimate its position based on the UAV.

IMAGE FEATURE EXTRACTION METHODS FOR STRUCTURE DETECTION FROM UNDERWATER IMAGERY

Abstract. The use of autonomous underwater vehicles (AUVs) for surveying underwater infrastructure presents a potential cost saving in comparison to remotely operated vehicles (ROVs). One of the challenges when processing images of underwater structures captured by an AUV, is that vast number of images captured during the mission usually do not show the structure. For instance, images captured during the dive to the structure or of the sea floor, or of the deep sea facing away from the structure. Too many images captured, without relevant information for a 3D reconstruction of the structure, leads to increased processing time and issues during the reconstruction process. There are two solutions to reduce the images to only images showing the structure. Firstly, only images of the structure are captured in the first place or remove images that are not useful after the capture and before further processing. This study developed and evaluated techniques that would enable the first strategy to be applied in an AUV. To apply this strategy in an AUV, would require an on-board structure detection system to ensure that they are correctly orientated for capturing useful footage during a survey mission. However, the marine environment poses several challenges to image-based object detection. Furthermore, small AUVs have limited power and computational resources available while deployed on a mission. To investigate the suitability of creating a lightweight structure detection model for the purpose of image evaluation, three computationally efficient image feature extraction methods (colour moments, local binary patterns (LBP), and Haar wavelet decomposition) were evaluated for their ability to distinguish underwater structures from background areas using unsupervised k-means models. LBP was found to be an effective method for identifying underwater structures in open water conditions. For identifying a structure against the seabed, colour moments were identified as the most effective method.

Application Field and Development Trend of Small Autonomous Underwater Vehicle

In recent years, with the implementation and promotion of the national Marine strategy - "toward deep blue", it means that our exploration of the ocean is no longer limited to the offshore, and at the same time, countries around the world are also deeply exploring the ocean. Small autonomous underwater vehicle technology is not only playing an increasingly prominent role in Deep Blue's strategy, but also plays an important role in industries such as industry, agriculture, and services. This paper describes the application development and future prospect of small autonomous underwater vehicle in various fields.

Nonlinear model predictive control for hydrobatics: Experiments with an underactuated AUV

AbstractHydrobatic autonomous underwater vehicles (AUVs) can be efficient in range and speed, as well as agile in maneuvering. They can be beneficial in scenarios such as obstacle avoidance, inspections, docking, and under‐ice operations. However, such AUVs are underactuated systems—this means exploiting the system dynamics is key to achieving elegant hydrobatic maneuvers with minimum controls. This paper explores the use of model predictive control (MPC) techniques to control underactuated AUVs in hydrobatic maneuvers and presents new simulation and experimental results with the small and hydrobatic SAM AUV. Simulations are performed using nonlinear model predictive control (NMPC) on the full AUV system to provide optimal control policies for several hydrobatic maneuvers in Matlab/Simulink. For implementation on AUV hardware in robot operating system, a linear time varying MPC (LTV‐MPC) is derived from the nonlinear model to enable real‐time control. In simulations, NMPC and LTV‐MPC shows promising results to offer much more efficient control strategies than what can be obtained with PID and linear quadratic regulator based controllers in terms of rise‐time, overshoot, steady‐state error, and robustness. The LTV‐MPC shows satisfactory real‐time performance in experimental validation. The paper further also demonstrates experimentally that LTV‐MPC can be run real‐time on the AUV in performing hydrobatic maneouvers.

Autonomous underwater vehicle motion state recognition and control pattern mining

Self-awareness of its own state during autonomous operation is critical for Autonomous Underwater Vehicles (AUVs) to execute tasks and monitor their health. Automated data analysis methods appear to be the most appropriate tool for attempting to understand and elucidate the motion states of AUVs. However, research scholars often focus on the state recognition of small AUVs used for shallow water detection, and the relevant conclusions cannot be directly applied to deep-sea AUVs. As a representative deep-sea AUV, Qianlong-3 is studied in this paper. In this study, a data-driven approach was employed to recognize the motion states and control modes of the Qianlong-3 AUV while retaining the original data noise. First, the class imbalance problem in the data was addressed, and then the data features were enhanced through a sliding window statistical method. By comparing the differences in the accuracy of motion state recognition after class imbalance processing using different supervised learning methods, the Random Forest (RF) algorithm was found to be the most suitable classification algorithm. In addition, the Toeplitz Inverse Covariance-Based Clustering (TICC) algorithm was used to recognize and mine the motion states and control modes of the AUV. The TICC algorithm was effective in extracting latent information from the actual data. Finally, through correlation analysis, the three motion states of the AUV were discussed, and the control modes for each of these states were determined. Overall, this study demonstrates the feasibility of relevant algorithms in practical deep-sea applications for state recognition and control mode mining. This provides valuable reference and experience for the development of future deep-sea AUV.

Sediment penetration performance of a portable underwater robot for core sampling

AbstractAs described in this paper, we investigate the sediment penetration performance of a portable underwater robot with a helical screw pipe using marine thrusters with limited force. First, we derive a mathematical model based on an empirical and simple method using the undrained shear strength of cohesive soil to provide a rough estimate of maximum penetration depths. Then, we perform numerical analysis for estimating the maximum depth of sediment penetration and for designing a sampling pipe. Additionally, we use experimentation to investigate the relation between the penetration depth of the helical screw pipe and the force of marine thrusters mounted on the portable underwater robot. After testing the penetration performance in a water tank, we conduct a field experiment at Lake Biwa and obtain results of the penetration depths. The maximum penetration into the lake sediment is at least 0.30 m. The results demonstrated the possibility of using the derived mathematical model to make a rough estimation of the maximum penetration depth for clay sediments. Additionally, we can use non‐powerful thrusters equipped with small autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs) for sediment sampling. The proposed method is also applicable for the installation of underwater sensors using small AUVs and ROVs.

Experimental Study on the Vibration Transfer Function of a Small Autonomous Underwater Vehicle

This paper presents the experimental results about vibration characteristics of a small autonomous underwater vehicle (AUV) named OKPO 300. The autonomy of AUVs leads to the increased use of AUVs in scientific, military, and commercial areas because their autonomy makes it possible for AUVs to be utilized instead of humans in hazardous missions such as mine countermeasure missions (MCMs). It is impossible to use devices with electro-magnetic waves for gathering information in an underwater environment. Only sonar systems that use sound waves can be utilized underwater, and the performance of sonar can strongly affect the autonomy of AUVs. Since a thruster system that combines a motor and propeller in a single structure is widely used as the propulsion system of an AUV and is mounted on the outside of the AUV’s stern, the vibration generated by the thruster system can be transferred throughout the shell of the AUV from the stern to the bow. The transferred vibration can affect the performance of various sonar systems that are installed in the AUV such as side-scan sonar or forward-looking sonar. Therefore, it is necessary to identify the effect of the transferred vibration of the AUV on the sonar systems. Even if various numerical methods were used to analyze the vibration problem of surface ships, it would be hard to apply numerical methods of the surface ships to identify the vibration phenomena of an AUV because of the underwater environment. In this work, an experimental study with OKPO 300 and an impact hammer was carried out to analyze vibration features of an actual small AUV in the air. Based on the experimental results, the frequency response function of vibration is presented. Based on the experimental results of this study, the natural frequency of OKPO 300 was confirmed, and the possibility of estimating the vibration characteristics of AUV using the transfer function method was shown.

Tracking control for small autonomous underwater vehicles in the Trans-Atlantic Geotraverse hydrothermal field based on the modeling trajectory

• A multi-parameter high-order extended state observer is designed to estimate lumped uncertainties. • A fixed-time fault-tolerant adaptive trajectory tracking controller is presented. • The desired trajectory is constructed by interpolating the path. • The simulation topography is built according to the TAG active mound. This paper investigates the fixed-time trajectory tracking problem of small autonomous underwater vehicles (S-AUVs) in the Trans-Atlantic Geotraverse (TAG) active mound with ocean current, unknown disturbances, model uncertainties, actuator faults, and input saturations. First, the effect of the near-bottom environment of the mound on S-AUVs is analyzed in detail from three issues. Without the upper bound and gradient of lumped uncertainties, a high-order adaptive extended state observer (ESO) is designed. Then, a continuous fixed-time sliding mode manifold is applied to obtain fast convergence performance. In order to realize the fixed-time convergence of tracking errors, an adaptive fault-tolerant trajectory tracking control law with an auxiliary dynamic system (ADS) is proposed. In addition, the simulated topography of the TAG mound is constructed and the trajectory based on path points is modeled by cubic spline interpolation. The effectiveness and superiority of the proposed algorithm are validated by comprehensive simulations.

A hierarchical disturbance rejection depth tracking control of underactuated AUV with experimental verification

This paper presents a hierarchical disturbance rejection depth tracking control scheme for the underactuated autonomous underwater vehicle (AUV) with comparative experimental results. The proposed hierarchical control scheme is constructed by two layers in the kinematics and dynamics. First, the line-of-sight (LOS) guidance is adopted to transform the depth tracking problem of the underactuated AUV into the pitch tracking in the kinematics layer, and then the adaptive line-of-sight guidance (ALOS) is proposed to estimate online and compensate for the angle of attack neglected in the traditional LOS guidance or in the presence of disturbance. Second, in order to further enhance the capability of disturbance rejection, active disturbance rejection control (ADRC) is adopted to track the desired pitch angle in the dynamics layer. In addition, a modified velocity saturation tracking differentiator (VSTD) by considering the motion characteristics of the AUV is introduced to enable the easy tuning of the control parameters and the adaptability to varying conditions in practice. Finally, a small size underactuated AUV prototype named as ARMs-AUV 1.0 is used to implement the control algorithms. Comparative experimental results are illustrated to demonstrate the effectiveness and the remarkable performance of the proposed depth tracking control scheme.

A Low-Complexity Underwater Acoustic Coherent Communication System for Small AUV

While underwater acoustic (UWA) communication offers a practical way to establish a wireless link with underwater vehicles, designing a UWA communication system onboard a small autonomous underwater vehicle (AUV) still poses significant challenges. As the adoption of the low-complexity, robust noncoherent communication technology is limited by low bandwidth efficiency and a low data rate, coherent UWA communication requires Doppler mitigation and channel equalization measures to achieve a relatively high data rate in a moving state. Due to the strict constraints of a small-scale AUV in terms of resources and energy consumption, it is not appropriate to use high-complexity Doppler/multipath compensation technology from the prospect of system implementation. In this paper, an efficient and low-complexity UWA differential binary phase-shift keying (DBPSK) system onboard a small AUV is proposed by simplifying the Doppler and multipath compensation. Specifically, for Doppler, the delay of the adjacent DBPSK symbols is calculated according to the Doppler estimate to facilitate delay-tuning Doppler correction. For multipath, low-complexity LMS channel equalization is incorporated with error correction coding to enable multipath mitigation. With a simple structure and low computational complexity, the proposed scheme facilitates the practical hardware implementation and system integration in the small AUV platform. The numerical simulations are conducted to assess the validity of the proposed scheme under different channel conditions and the effectiveness of the proposed scheme is further verified by two UWA communication field tests, which are performed at a practical shallow water sea and lake, respectively.

Sidescan Only Neural Bathymetry from Large-Scale Survey.

Sidescan sonar is a small and low-cost sensor that can be mounted on most unmanned underwater vehicles (UUVs) and unmanned surface vehicles (USVs). It has the advantages of high resolution and wide coverage, which could be valuable in providing an efficient and cost-effective solution for obtaining the bathymetry when bathymetric data are unavailable. This work proposes a method of reconstructing bathymetry using only sidescan data from large-scale surveys by formulating the problem as a global optimization, where a Sinusoidal Representation Network (SIREN) is used to represent the bathymetry and the albedo and the beam profile are jointly estimated based on a Lambertian scattering model. The assessment of the proposed method is conducted by comparing the reconstructed bathymetry with the bathymetric data collected with a high-resolution multi-beam echo sounder (MBES). An error of 20 cm on the bathymetry is achieved from a large-scale survey. The proposed method proved to be an effective way to reconstruct bathymetry from sidescan sonar data when high-accuracy positioning is available. This could be of great use for applications such as surface vehicles with Global Navigation Satellite System (GNSS) to obtain high-quality bathymetry in shallow water or small autonomous underwater vehicles (AUVs) if simultaneous localization and mapping (SLAM) can be applied to correct the navigation estimate.

수중 사출에 의한 소형 무인잠수정의 전동기 역기전력 보호회로 설계 및 모델링 방안

In this paper, we identify the electric power problem of the high-speed underwater discharge in a small autonomous underwater vehicle(AUV) and propose a circuit design method to protect it. High-speed underwater discharge of an AUV arouse propeller rotates due to the water flow. Excessive initial propeller rotation generates a back EMF of the motor and causes a voltage increase at the DC terminal of the inverter. To figure out this problem, a simulation was performed to limit the back EMF in a simplified environment. Then, a simulation-based controller protection circuit was proposed. Finally, the validity of the proposed simulation and the superiority of the protection circuit were confirmed through the actual underwater discharge test.

Smart vector-inspired optical vision guiding method for autonomous underwater vehicle docking and formation.

A smart vector-inspired optical vision guiding (VIOVG) method for autonomous underwater vehicle (AUV) docking and formation is proposed. Unlike traditional optical guiding methods based on LED arrays, the method is inspired by a vector, and uses four laser diodes to form a wing-light pattern to realize smart optical guiding for AUVs. Due to the light scattering effect from water, the four laser diodes can emit four bright and slim laser beams in water, which can be captured by underwater cameras. The intersections of the laser beams form wing-lights as markers for AUV distance and pose estimation. The wing-light pattern is easily tuned and extended by changing the propagation direction and the power of the laser beams beyond the limitation of the physical size of the AUV or docking station. The simulations and experiments show that the proposed method can achieve high precision positioning. A relative distance error of 3.35% is achieved in a positioning experiment at ∼10 m. It has great potential for AUV docking and formation, especially for small AUVs.

Adaptive Disturbance-Observer-Based Continuous Sliding Mode Control for Small Autonomous Underwater Vehicles in the Trans-Atlantic Geotraverse Hydrothermal Field with Trajectory Modeling Based on the Path

Considering intense hydrothermal activities and rugged topography in a near-bottom environment of the trans-Atlantic geotraverse (TAG) hydrothermal mound, a small autonomous underwater vehicle (S-AUV) will suffer from time-varying disturbances, model uncertainties, actuator faults, and input saturations. To handle these issues, a fault-tolerant adaptive robust sliding mode control method is presented in this paper. Firstly, unknown disturbances, model uncertainties, and actuator faults of the S-AUV are synthesized into a lumped uncertain vector. Without requiring the upper bound and gradient of the uncertainties, a continuous adaptive finite-time extended state observer is designed to estimate the lumped uncertain vector. Then, an auxiliary dynamic system composed of continuous functions is introduced to deal with input saturations, thereby contributing to achieving fixed-time trajectory tracking control of S-AUVs. Based on a designed continuous fixed-time nonsingular fast sliding mode surface, the proposed continuous adaptive controller is chattering free. Simulated topography is built according to topographic data of the TAG mound, and a smooth trajectory model is constructed by cubic spline interpolation. Comprehensive simulations performed on an actual S-AUV model are given to validate the effectiveness and superiority of the presented algorithm.

Design of a Broadband Cavity Baffle Bender Transducer

As low-frequency and broadband acoustic emission capability is beneficial to the detection range and acoustic communication speed of small scale autonomous underwater vehicles (AUV), this type of transducer is required, especially in cases of complex acoustic environments. A broadband bender transducer with cavity baffle that suits small scale AUV is proposed. Rather than additional benders, a passive cavity baffle, which would be capable of providing mutual radiation and a fluid cavity mode, is introduced to a single bender. The bending resonant frequency is reduced by the mutual radiation between the bender and the cavity baffle, the cavity baffle extends the lower limit of the available frequency band of the transducer, the liquid resonant frequency behind the former expands the higher limit, then the cavity baffle bender transducer fills the role of radiating low-frequency and broadband emissions through multimode coupling. The finite element method is used to analyze the acoustic performance of the transducer under different baffle conditions. Then, a prototype of the broadband cavity baffle bender transducer is developed according to the optimized parameters of simulation. The acoustic parameters of the prototype were measured in an anechoic pool. The resonant frequency measured in water of the bender itself is 3 kHz, and the −3dB bandwidth is 560 Hz. The prototype test results show that the cavity baffle scheme can improve the −3dB bandwidth of the bender from 560 Hz to 1000 Hz, which fundamentally realizes the expectations of the prototype design.

Measurement of Tidal Currents Using an Autonomous Underwater Vehicle

Small autonomous underwater vehicles (AUVs) offer advantages in ease of deployment and recovery, covertness, and minimal logistical requirements for operation; however, speed and battery capacity can limit their effectiveness in areas where there are strong currents. While measurement of currents from these platforms is enabled by use of Doppler velocity logs (DVLs) with profiling capability, the quality of these current measurements needs evaluation. A trial was conducted in the Narrows channel of Halifax Harbour in October 2019 with coinciding tidal current measurements using fixed acoustic Doppler current profilers, drifters, and an AUV equipped with a profiling DVL. Output from a high-resolution tidal current model, Halifax Finite-Volume Community Ocean Model, has also been compared. The intercomparison of the current measurements and model output shows good agreement and highlights the complex structure of the tidal flow in the harbor channel. Evaluation of the AUV/DVL current measurements shows that adequate smoothing is achieved using shorter spatial/temporal averaging windows than other investigators have reported. A spatial (alongtrack) averaging bin size of 20 m, or equivalently 13 1-Hz profiles at 3-kn speed, reduces the standard deviation of the current magnitude measurements to a stable level. A shorter averaging scale allows fine enough detail in current mapping to be useful in harbor and littoral environments with strongly localized flows.

Design, analysis, and testing of Petrel acoustic autonomous underwater vehicle for marine monitoring

Autonomous underwater vehicles (AUVs) provide a unique and cost-effective platform for conducting ocean acoustic measurements and surveys such as marine mammal monitoring, extensive area seafloor topography survey, and fish stock survey. The small and medium-sized AUVs combine load-carrying capability, motion, and range and allow for timescale observations that are difficult to achieve with traditional acoustic observation platforms. However, self-noise is still an unavoidable challenge for AUVs when applied in passive acoustic monitoring. This paper presents the acoustic observation application of the Petrel acoustic AUV in marine monitoring. The layout design of a Petrel acoustic AUV and acoustic sensor integration are described in detail, and the self-noise characteristics of Petrel acoustic AUVs are evaluated by simulation and testing. The results showed that the self-noise level of Petrel acoustic AUVs is effectively controlled with its optimized design, and the maximum noise of the propulsion system is only 75 dB in the low-frequency band. Therefore, the Petrel acoustic AUV can be used as an ideal acoustic observation platform to carry out diverse observation tasks. Finally, a solution of fixed-depth motion is proposed to address the problem that frequent attitude adjustment affects the quality of acoustic data in fixed-depth navigation. According to a sea trial in the South China Sea, the method can significantly reduce the attitude adjustment frequency and, thus, provide an ideal environment for acoustic observation. This method also applies to other underwater mobile observation platforms. This study provides a reference for the acoustic integration design of underwater equipment such as long-range AUVs or hybrid-driven underwater gliders.

Design and experimental results of passive iUSBL for small AUV navigation

This paper presents a passive inverted Ultra-Short Baseline (piUSBL) positioning system which provides accurate and instantaneous positioning for small Autonomous Underwater Vehicles (AUVs) at low cost and power consumption. Conventional underwater positioning systems tend to be expensive and bulky, limiting the application of small AUVs. This system is based on an iUSBL positioning system, which places a small circular receiver array on an AUV rather than on a deployment ship. The One-Way Travel-Time (OWTT) range and Direction of Arrival (DOA) between the vehicle and a single acoustic beacon enable AUV navigation relative to the beacon. Deconvolved conventional beamforming (dCv) provides high-resolution azimuth estimation. This paper describes the system design in detail and presents experimental results in an anechoic tank and some field lakes. The piUSBL system shows great potential for small AUVs after several successful AUV applications.

Underwater Localization and Mapping Based on Multi-Beam Forward Looking Sonar.

SLAM (Simultaneous Localization And Mapping) plays a vital role in navigation tasks of AUV (Autonomous Underwater Vehicle). However, due to a vast amount of image sonar data and some acoustic equipment's inherent high latency, it is a considerable challenge to implement real-time underwater SLAM on a small AUV. This paper presents a filter based methodology for SLAM algorithms in underwater environments. First, a multi-beam forward looking sonar (MFLS) is utilized to extract environmental features. The acquired sonar image is then converted to sparse point cloud format through threshold segmentation and distance-constrained filtering to solve the calculation explosion issue caused by a large amount of original data. Second, based on the proposed method, the DVL, IMU, and sonar data are fused, the Rao-Blackwellized particle filter (RBPF)-based SLAM method is used to estimate AUV pose and generate an occupancy grid map. To verify the proposed algorithm, the underwater vehicle is equipped as an experimental platform to conduct field tasks in both the experimental pool and wild lake, respectively. Experiments illustrate that the proposed approach achieves better performance in both state estimation and suppressing divergence.