Navigation Of Unmanned Underwater Vehicles Research Articles

Sensor Fusion for Underwater Vehicle Navigation Compensating Misalignment Using Lie Theory.

This paper presents a sensor fusion method for navigation of unmanned underwater vehicles. The method combines Lie theory into Kalman filter to estimate and compensate for the misalignment between the sensors: inertial navigation system and Doppler Velocity Log (DVL). In the process and measurement model equations, a 3-dimensional Euclidean group (SE(3)) and 3-sphere space (S3) are used to express the pose (position and attitude) and misalignment, respectively. SE(3) contains position and attitude transformation matrices, and S3 comprises unit quaternions. The increments in pose and misalignment are represented in the Lie algebra, which is a linear space. The use of Lie algebra facilitates the application of an extended Kalman filter (EKF). The previous EKF approach without Lie theory is based on the assumption that a non-differentiable space can be approximated as a differentiable space when the increments are sufficiently small. On the contrary, the proposed Lie theory approach enables exact differentiation in a differentiable space, thus enhances the accuracy of the navigation. Furthermore, the convergence and stability of the internal parameters, such as the Kalman gain and measurement innovation, are improved.

Preliminary Study on the Application of Heat Pipe Reactor in Unmanned Underwater Vehicles

At the beginning of the 21st century, due to the re-proposal of the United States space exploration program, heat pipe reactors once again received widespread attention from researchers. With their long lifespan, high energy density, and inherent safety features, they exhibit promising prospects for application in space nuclear reactors, land-based mobile nuclear power sources, and deep-sea unmanned equipment exploration. Consequently, they represent an ideal novel energy source for unmanned underwater vehicles (UUVs). This article selected the SUBOFF submarine model as a basis to calculate UUVs’ navigation resistance at various speeds using the 1+k method. By comparing the converted UUVs navigation power demand with that of traditional batteries and heat pipe stacks’ output power, it was concluded that heat pipe reactors offer superior power supply and endurance capabilities. Subsequently, based on the structural characteristics of the heat pipe stack, this study summarized battery advantages and characteristics while also addressing construction and development aspects of heat pipe stack energy systems. Furthermore, the key technologies that need to be overcome in the application of heat pipe stacks in UUVs are introduced. Through the formula of heat transfer limit of heat pipe, the factors that limit the heat transfer performance of heat pipe are analyzed, and the positive correlation among the number of heat pipe, heat transfer limit and heat transfer power was obtained. Finally, the challenges faced by the future application of heat pipe stacks in UUVs were pointed out.

A performance-enhanced DVL/SINS integrated navigation system based on data-driven approach

With the aid of Doppler velocity logger (DVL), strapdown inertial navigation systems (SINSs) can provide continuous and accurate navigation parameters for unmanned underwater vehicles (UUVs). However, owing to the complex underwater environment, partial DVL beams may fail to be reflected by the seafloor, resulting in DVL measurement outage. In this study, a novel data-driven approach enhancing DVL/SINS integrated navigation system is proposed to improve the robustness and accuracy of UUV navigation with limited DVL beams. First, to make full use of the available beam, the velocities of DVL beams are used to assist the SINS navigation instead of the 3D velocity of DVL. Subsequently, a virtual beam predictor based on multi-output least-squares support vector regression (MLS-SVR) is built to run in parallel with the DVL/SINS integrated system. Specifically, when the DVL operates normally, all four beams can be applied for integrated navigation and stored as the training dataset. Once partial beams are missing, the available beams and the outputs of SINS and pressure sensors can train the MLS-SVR model along with the corresponding missing beams in the training set. Subsequently, the missing beams can be predicted by the trained model for integrated navigation together with the available beams. UUV sea trials indicate that the proposed system can accurately predict unavailable beams and improve the positioning accuracy of the DVL/SINS integrated navigation system.

In-Lab Demonstration of an Underwater Acoustic Spiral Source.

Underwater acoustic spiral sources can generate spiral acoustic fields where the phase depends on the bearing angle. This allows estimating the bearing angle of a single hydrophone relative to a single source and implementing localization equipment, e.g., for target detection or unmanned underwater vehicle navigation, without requiring an array of hydrophones and/or projectors. A spiral acoustic source prototype made out of a single standard piezoceramic cylinder, which is able to generate both spiral and circular fields, is presented. This paper reports the prototyping process and the multi-frequency acoustic tests performed in a water tank where the spiral source was characterized in terms of the transmitting voltage response, phase, and horizontal and vertical directivity patterns. A receiving calibration method for the spiral source is proposed and showed a maximum angle error of 3° when the calibration and the operation were carried out in the same conditions and a mean angle error of up to 6° for frequencies above 25 kHz when the same conditions were not fulfilled.

A novel adaptive nonlinear Kalman filter scheme for DVL-aided SINS alignment in underwater vehicles

The rapid and accurate initial alignment of a strapdown inertial navigation system (SINS) aided by a Doppler velocity logger (DVL) still poses a significant challenge in unmanned underwater vehicle navigation. In this study, a novel adaptive nonlinear filtering alignment scheme is developed for a SINS with a large misalignment angle. In previous studies, the frame-inconsistency problem of the nonlinear SINS error model was neglected. Thus, a modified nonlinear error model of a SINS is derived here rigorously as the process model of the nonlinear Kalman filter. In addition, the noise amplification of applying Sage-Husa adaptive Kalman filter (SHAKF) in alignment is analyzed, and a novel arctangent fading memorial factor is introduced to dynamically adjust the weight of current measurements. Simulations and field experiments indicate that the proposed algorithm is efficient in underwater DVL/SINS in-motion alignment. The alignment accuracy and convergence rate of the modified model are significantly improved compared to those of the traditional model. The arctangent fading memorial SHAKF can reliably estimate the measurement noise and improve the performance of alignment.

Vision-based environment perception and autonomous obstacle avoidance for unmanned underwater vehicle

We propose two schemes to solve the problems of visual perception delay and limited obstacle avoidance capability in the autonomous navigation of unmanned underwater vehicles (UUV). In the aspect of visual perception, this paper presents a compressed algorithm based on the UNDERWATER-CUT model for underwater image enhancement and a two-stage compressed YOLOv5s model for object detection, simultaneously reducing the model volume, decreasing the run-time memory footprint, and lowering the number of computing operations, without compromising enhancement effect and recognition accuracy. The 2D coordinates of the obstacles acquired by the visual perception algorithms and the depth values by the depth camera are then merged into real-time navigation information. In terms of obstacle avoidance, this paper proposes the adapted modified guidance vector field (AMGVF) to achieve autonomous navigation. A high-fidelity underwater simulation platform based on AirSim is constructed to jointly validate the above algorithms. Finally, the experimental results on visual perception and obstacle avoidance show that the above methods apply to the UUV well in complex underwater environment.

Finite-Time Controller for Coordinated Navigation of Unmanned Underwater Vehicles in a Collaborative Manipulation Task

Unmanned underwater vehicles perform inspection and maintenance tasks in complex and changing environments. Some of these tasks require synchronous navigation of multiple vehicles, which is challenging. This paper proposes a synchronous navigation scheme for two BlueROV2 underwater vehicles for a coordinated multi-vehicle task. In the proposed scheme, the vehicles perform the collaborative task of grasping, transporting, and releasing an object. In this scheme, no vehicle-to-vehicle communication is required. A model-free second-order sliding mode controller with finite-time convergence is used to accomplish this task. The controller's convergence time is user-defined and does not depend on the physical or hydrodynamic parameters of the vehicle, unlike the other finite-time controllers found in the literature. Simulation experiments were conducted to verify the controller's performance, including high ocean currents as external disturbances. Comparisons were made with two state-of-the-art controllers with finite-time convergence. The results showed that the proposed controller achieved the best results, as the user-defined convergence time was achieved for both vehicles and the collaborative task was completed, no ripples, deviations, or oscillations were observed, and no chattering occurred. The results proved the robustness of the controller in the presence of high ocean currents without the need to readjust the parameters.

An adaptive interactive multi-model navigation method based on UUV

This paper introduces an adaptive interactive multi-model algorithm for the navigation system of the unmanned underwater vehicle (UUV). The underwater environment is diverse and time-varying. Obtaining high-precision navigation is very important for the safety and effectiveness of autonomous navigation of unmanned underwater vehicles, which makes the reliability of UUV navigation-related sensors particularly demanding. When the underwater environment has absorbing substances or a deep-sea environment, the Doppler velocity log (DVL) will produce outliers or even fail. When the vehicle navigates to a flat terrain area and terrain aided navigation (TAN) performs navigation parameter matching, multiple adaptation positions will appear, resulting in abnormal measurement data. Similarly, when UUV sails to a strong magnetic area, magnetic compass (MCP) will be disturbed, etc. To improve the robustness of navigation and reduce the influence of the change of system model and measurement noise model caused by environmental factors, an adaptive interactive multi-model algorithm is proposed, which is carried out with the UUV based INS/DVL/MCP/TAN integrated navigation system. For the problem that the measurement noise of the system changes, different models are organized into a collection, and according to different situations, the corresponding model or hybrid model is selected in the collection of models to describe the measurement noise, so as to realize the seamless switching of the system model. The simulation results show that the adaptive multi-model algorithm can effectively control the impact of system noise model uncertainty on navigation accuracy, so that UUV has higher accuracy and less computation than single navigation and traditional algorithms, and has robustness and scalability.

A Survey on Visual Navigation and Positioning for Autonomous UUVs

Autonomous navigation and positioning are key to the successful performance of unmanned underwater vehicles (UUVs) in environmental monitoring, oceanographic mapping, and critical marine infrastructure inspections in the sea. Cameras have been at the center of attention as an underwater sensor due to the advantages of low costs and rich content information in high visibility ocean waters, especially in the fields of underwater target recognition, navigation, and positioning. This paper is not only a literature overview of the vision-based navigation and positioning of autonomous UUVs but also critically evaluates the methodologies which have been developed and that directly affect such UUVs. In this paper, the visual navigation and positioning algorithms are divided into two categories: geometry-based methods and deep learning-based. In this paper, the two types of SOTA methods are compared experimentally and quantitatively using a public underwater dataset and their potentials and shortcomings are analyzed, providing a panoramic theoretical reference and technical scheme comparison for UUV visual navigation and positioning research in the highly dynamic and three-dimensional ocean environments.

Motion planning and tracking control of unmanned underwater vehicles: technologies, challenges and prospects

The motion planning and tracking control techniques of unmanned underwater vehicles (UUV) are fundamentally significant for efficient and robust UUV navigation, which is crucial for underwater rescue, facility maintenance, marine resource exploration, aquatic recreation, etc. Studies on UUV motion planning and tracking control have been growing rapidly worldwide, which are usually sorted into the following topics: task assignment of the multi-UUV system, UUV path planning, and UUV trajectory tracking. This paper provides a comprehensive review of conventional and intelligent technologies for motion planning and tracking control of UUVs. Analysis of the benefits and drawbacks of these various methodologies in literature is presented. In addition, the challenges and prospects of UUV motion planning and tracking control are provided as possible developments for future research.

Application of unmanned underwater vehicles in polar research

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

Collection of Marine Debris by Jointly Using UAV-UUV With GUI for Simple Operation

In recent years, floating debris in the sea has damaged the environment and harmed wildlife. Systems for collecting floating marine debris in the open ocean by installing a huge net or using a vacuum device have been proposed. However, to the best of our knowledge, there is no system for collecting marine debris in complex topographies, such as ports wherein marine debris tends to accumulate, and large vessels cannot enter. This study proposes a system to locate and collect floating marine debris by jointly using an unmanned aerial vehicle (UAV) and an unmanned underwater vehicle (UUV). The UAV discovers marine debris that cannot be observed by the UUV owing to its limited view, and the UUV is used for collection. However, for application of such a system, problems related to target detection, UUV navigation, and target collection must be solved. In the proposed system, the following components are developed: a graphical user interface to select the collection target, controller for the UUV to navigate to the target, and a collecting motion generator. We tested and evaluated the proposed cooperative system using a dynamic simulator and physical robots. As a result, we confirm that our system can achieve efficient debris collection in complex topographies, is easy to use, will reduced workload, and can be applied practically.

A Novel Adaptive H-Infinity Cubature Kalman Filter Algorithm Based on Sage-Husa Estimator for Unmanned Underwater Vehicle

In the navigation of unmanned underwater vehicle (UUV), a filtering algorithm suitable for the working conditions is required. Due to the disturbance from the environment and maneuverability, outliers and noise with time-varying statistical properties always exist, which greatly affect the positioning accuracy and stability of the navigation system. In this paper, we present a novel nonlinear state estimation algorithm named AH∞CKF based on the combination of H∞CKF and Sage-Husa estimator. The recently developed H∞CKF provides nonlinear filtering good robustness, and Sage-Husa estimator could timely modify the statistical properties of noise. The novel algorithm is superior to H∞CKF in accuracy by combining Sage-Husa estimator with the H∞CKF while ensuring robustness. The effectiveness of the novel AH∞CKF is verified by lake experiment and simulation.

Polar Transversal Initial Alignment Algorithm for UUV with a Large Misalignment Angle.

The conventional initial alignment algorithms are invalid in the polar region. This is caused by the rapid convergence of the Earth meridians in the high-latitude areas. However, the initial alignment algorithms are important for the accurate navigation of Unmanned Underwater Vehicles. The polar transversal initial alignment algorithm is proposed to overcome this problem. In the polar transversal initial alignment algorithm, the transversal geographic frame is chosen as the navigation frame. The polar region in the conventional frames is equivalent to the equatorial region in the transversal frames. Therefore, the polar transversal initial can be effectively applied in the polar region. According to the complex environment in the polar region, a large misalignment angle is considered in this paper. Based on the large misalignment angle condition, the non-linear dynamics models are established. In addition, the simplified unscented Kalman filter (UKF) is chosen to realize the data fusion. Two comparison simulations and an experiment are performed to verify the performance of the proposed algorithm. The simulation and experiment results indicate the validity of the proposed algorithm, especially when large misalignment angles occur.

A Polar Initial Alignment Algorithm for Unmanned Underwater Vehicles.

Due to its highly autonomy, the strapdown inertial navigation system (SINS) is widely used in unmanned underwater vehicles (UUV) navigation. Initial alignment is crucial because the initial alignment results will be used as the initial SINS value, which might affect the subsequent SINS results. Due to the rapid convergence of Earth meridians, there is a calculation overflow in conventional initial alignment algorithms, making conventional initial algorithms are invalid for polar UUV navigation. To overcome these problems, a polar initial alignment algorithm for UUV is proposed in this paper, which consists of coarse and fine alignment algorithms. Based on the principle of the conical slow drift of gravity, the coarse alignment algorithm is derived under the grid frame. By choosing the velocity and attitude as the measurement, the fine alignment with the Kalman filter (KF) is derived under the grid frame. Simulation and experiment are realized among polar, conventional and transversal initial alignment algorithms for polar UUV navigation. Results demonstrate that the proposed polar initial alignment algorithm can complete the initial alignment of UUV in the polar region rapidly and accurately.

Study on Hardware-in-the-Loop Simulation System for Navigation and Control of UUV

The Unmanned Underwater Vehicle (UUV) is used more and more widely in military and non-military areas. Since UUVs navigation and motion control system is highly complex, a Hardware-In-the-Loop Simulation (HILS) system is designed and implemented to help research and development of its navigation and motion control system. The HILS system is mainly composed of real-time simulation computer, main control compute, GPS/Beidou satellite signal simulator, three-axis turntable, actuator load simulator, water pressure simulator, acceleration simulation unit, visual computer and interface devices. Performance specifications are allocated to each components of the HILS system according to dynamic characteristics of the UUV under complicated disturbances. Proximity between the results of the UUVs HILS and sea trial demonstrates the validity of the HILS system elementarily.

Survey of Conventional UUV Navigation Mapping Technique in Development of AQUA-X UUV

Unmanned Underwater Vehicles (UUV) are devices that perform task with slight or no human interaction. These tasks are predefined set of commands called navigation methods, that are used to achieve desired mission goals. The navigation control system plays an important role in maneuvering of UUV and without it UUV cannot perform any mission task. In this research article a survey of different navigation techniques are presented for new design of Underwater mobile robot named as AQUA-X Robot, which uses four (4) propellers placed in cartesian coordinate configuration with parallel arrangement which help it in batter navigation maneuvering. The detail working principles, advantages and problems in different navigation techniques are thoroughly discussed. Besides that, their implementation on UUV on a ranged mission situation are also briefly described. Finally the accuracy of the different navigation techniques are compared and based on this comparison a most suitable navigation method is selected for developing AQUA-X UUV for better navigation.

Multibeam Sonar-Based Navigation of Small UUVs for MCM Purposes

AbstractAutonomous vehicles (AxV), surface (ASV) and underwater (AUV), are being considered for the following maritime security missions: Mine Countermeasures (MCM) and Harbor Protection (HP). Applicable threats include attack swimmers/divers, bottom and moored mines, mines or improvised explosive devices placed on pilings, quays, or hulls of ships at anchor or in port. This article focuses on solutions for mine reacquisition and neutralization (RN). One concept for an overall RN system is two collaborating vehicles, an AxV and a unmanned underwater vehicle (UUV). The main task of the RN AxV is to reacquire a bottom target with multibeam imaging sonar, maintain distance while pointing at the target, and perform circular inspection around a target while varying the circle diameter. The main task of the RN UUV is to converge towards the desired line once deployed from the AxV. UUV guiding is accomplished by automatically processing sonar imagery onboard of the AxV and passing sonar position, and UUV range and bearing information to the UUV which processes this information to drive itself to the desired location.

Experimental Setups for Vision-Based Navigation of Unmanned Underwater Vehicles in Near Intervention Operations

In the last decade, vision systems have become an instrumental sensor in the development of accurate control and navigation systems for unmanned underwater vehicles. Unfortunately testing of new vision based techniques in actual underwater environments is a difficult and expensive proposition. This paper details the development and evaluates the potential performance of two novel methods for underwater vehicle vision based control and navigation systems testing; physical simulation and virtual simulation. The paper also details the experimental setup for test tank trials utilizing a seabed poster representation. This setup is evaluated based on results from a previously developed real-time vision based navigation system. The experimental setup for sea trials of the University of Limericks newly developed thrusted pontoon/ROV is also presented.

Intelligent behaviour-based team UUVs cooperation and navigation in a water flow environment

This paper considers the problem of intelligent behaviour-based team unmanned underwater vehicles (UUVs) cooperation and navigation, especially in a water flow environment. Animals often have behaviour which aims to maintain them living as groups. We learn from animals’ typical group behaviour and develop behaviour-based rules for team cooperation of UUVs. We create simulation scenarios in which a team of vehicles cooperate to track a target in a water current environment. This paper customises several behaviour-based rules to satisfy the requirement of the desired scenarios. We use fuzzy logic controllers to set different priority weights for each rule on-line according to the situation that the vehicles meet. The decision of the vehicle's next step steering direction is made by the combination of these rules multiplied by the relative priority weights. The line-of-sight guidance law is modified as the navigation rule in a water flow environment. The dynamic manoeuvring model of a real small UUV, SUBZERO III, is used in the simulation. The simulation results indicate that the entire system is successful in reaching the target without any collision within the scenario. The different trajectories and travel times are compared and discussed when normal and modified line-of-sight guidance rules are applied.