Dynamics Modeling and Motion Simulation of USV/UUV with Linked Underwater Cable

With the development of technologies related to unmanned vehicles, including unmanned aerial vehicle and unmanned surface vehicle, unmanned vehicles play a pivotal role in maritime management and cruise activities. Meanwhile, lots of evidence shows that a single unmanned vehicle is not qualified for operation under complex environment, whereas the unmanned aerial vehicle–unmanned surface vehicle formation consists of multiple unmanned aerial vehicles and unmanned surface vehicles, which can enhance the performance of the single unmanned vehicle significantly. However, the cooperative operation performance of the unmanned aerial vehicle–unmanned surface vehicle formation is constrained by its communication capacity. Consequently, a cooperative communication framework is designed for the unmanned aerial vehicle–unmanned surface vehicle formation. A distributed dynamic network topology is constructed for fulfilling effective communication for the unmanned aerial vehicle–unmanned surface vehicle formation based on ad hoc network. Experiments are carried out by employing the built unmanned aerial vehicle–unmanned surface vehicle formation platform. Results verify the superiority of the designed cooperative communication framework for the unmanned aerial vehicle–unmanned surface vehicle formation.

This paper focuses on motion analysis of a coupled unmanned surface vehicle (USV)–umbilical cable (UC)–unmanned underwater vehicle (UUV) system to investigate the interaction behavior between the vehicles and the UC in the ocean environment. For this, a new dynamic modeling method for investigating a multi-body dynamics system of this coupling system is employed. Firstly, the structure and hardware composition of the proposed system are presented. The USV and UUV are modeled as rigid-body vehicles, and the flexible UC is discretized using the catenary equation. In order to solve the nonlinear coupled dynamics of the vehicles and flexible UC, the fourth-order Runge–Kutta numerical method is implemented. In modeling the flexible UC dynamics, the shooting method is applied to solve a two-point boundary value problem of the catenary equation. The interaction between the UC and the USV–UUV system is investigated through numerical simulations in the time domain. Through the computer simulation, the behavior of the coupled USV–UC–UUV system is analyzed for three situations which can occur. In particular, variation of the UC forces and moments at the tow points and the configuration of the UC in the water are investigated.

Based on the application of important water area blockade, a new discontinuous guidance approach of an unmanned underwater vehicle (UUV) perpendicularly towards side of surface ship is proposed, and a hardware-in-the-loop simulation (HILS) system is established to demonstrate this guidance approach. This approach can be described as follows: a near-surface straight trajectory which is perpendicular to the predicted ship trajectory is figured out by detection device of UUV which is hidden underwater after the ship target is located. When the horizontal distance between UUV and the ship target meets start-up condition, UUV climbs to a certain depth near the sea surface and then runs along the horizontal straight trajectory. During its motion, UUV periodically measures the sight line between the UUV and ship target. In order to restrain the horizontal rotation of the sight line, a discontinuous guidance approach is proposed by using the deviation of the two adjacent sight lines and the distance between the UUV and the ship target to adjust the UUV’s velocity. After certain times of adjustment of the UUV’s velocity, UUV impacts the side of ship target perpendicularly with required accuracy. This near-surface discontinuous guidance approach makes it possible for UUV to be guided through optical or radar detection. Further discussions are made including miss distance caused by this proposed guidance approach, cycle of sight line detection, UUV’s non-attack zone and UUV start-up condition. Finally, a set of HILS is carried out to demonstrate the performance of the discontinuous guidance approach on an experimentally validated UUV model.

With the development of the unmanned marine systems, autonomous recovery of Unmanned Underwater Vehicles(UUV) based on the Unmanned Surface Vehicles(USV) has become an important research field. Comparatively analyzing the current mainstream recovery methods, this paper proposes a new recovery scheme based on the previous research results. In this scheme, one end of the cable is connected to a winch fixed to the USV and the other is connected to the V-shaped wing, which can provide downward pressure to keep the line tight, and the rudders mounted on it can be adjusted to assure the attitude stability, which facilitate Docking and Line Capture Line Recovery(LCLR) of the UUV. After structure optimization, the V-shaped wing was modeled in hydrodynamic software STAR-CCM+. The numerical simulation shows that the improved V-shaped wing can provide about 20N downward pressure when the towing speed is 2 knots. In order to improve the reliability of the LCLR system and reduce mechanism sticking, a new type of capture mechanism is designed and it is driven by two motor respectively instead of just one. Besides, the LED beacon ranging tests were conducted in the Xiu Lake. It shows the accuracy of optical guidance algorithm is 2%, and the maximum optical recognition distance is 16m in the air and 10m in the clean water, which satisfies the docking accuracy. From October 2018, two Lake tests were carried out in Xiu Lake in Shenyang and Qiandao Lake in Hangzhou. The performance of the LCLR system was tested, and the V-shaped wing was towed at different speeds range from 1 to 1.5 knots and the length of the cable is 8m. The results show the V-shaped wing can maintain depth and attitude stability. Finally, through the improved acousto-optic joint guidance algorithm, the docking process is successfully completed and the Towed Line and Cable were captured by the UUV line capture mechanism on nose. The feasibility of the presented recovery scheme was indicated by the results from the two trials, which has a certain guiding significance for the dynamic recovery of an UUV in the future.

Underwater operating platforms face difficulties regarding power supply and communications. To overcome these difficulties, this study proposes a hybrid surface and underwater vehicle (HSUV) and presents the development of the platform, control algorithms, and results of field tests. The HSUV is capable of supplying reliable power to the unmanned underwater vehicle (UUV) and obtaining data in real time by using a tether cable between the UUV and the unmanned surface vehicle (USV). The HSUV uses global positioning system (GPS) and ultra-short base line sensors to determine the relative location of the UUV. Way point (WP) and dynamic positioning (DP) algorithms were developed to enable the HSUV to perform unmanned exploration. After reaching the target point using the WP algorithm, the DP algorithm enables USV to maintain position while withstanding environmental disturbances. To ensure the navigation performance at sea, performance tests of GPS, attitude/heading reference system, and side scan sonar were conducted. Based on these results, manual operation, WP, and DP tests were conducted at sea. WP and DP test results and side scan sonar images during the sea trials are presented.

Trajectory tracking control refers to the movement of an unmanned underwater vehicle (UUV) along a desired trajectory, which is a critical technology for the underwater tasks of UUVs. However, in actual scenarios, the reaction torque of propellers induces roll motion in UUVs, and the communication resource and computational resource of UUVs are limited, which affects the trajectory tracking performance of UUVs severely. Hence, this paper introduces an event triggering mechanism to design the double-loop integrated sliding mode control (EDLISMC), which is used for the trajectory tracking control of UUVs. This method designs the kinematic model and dynamic model of 6 degree of freedom (DoF) UUVs under the influence of reaction torque. Then, this method derives the dual loop integral sliding mode controller and designs the event triggering mechanism based on the relative threshold to reduce unnecessary control signals and improve the control efficiency of UUVs. In addition, this method uses a positive lower bound method to verify that the proposed event triggering mechanism does not have Zeno behavior and adopts the Lyapunov theorem to analyze the stability of EDLISMC. Finally, this paper conducts simulations on the simulink component of MATLAB. The relevant simulation proves that the proposed method can complete the trajectory tracking control of UUVs under the influence of reaction torque and it is superior to other methods in terms of resource consumption.

Researchers are currently conducting several studies in the field of navigation systems and sensors. Even in the past, there was a lot of research regarding the field of velocity sensors for unmanned underwater vehicles (UUVs). UUVs have various services and significance in the military, scientific research, and many commercial applications due to their autonomy mechanism. So, it’s very crucial for the proper maintenance of the navigation system. Reliable navigation of unmanned underwater vehicles depends on the quality of their state determination. There are so many navigation systems available, like position determination, depth information, etc. Among them, velocity determination is now one of the most important navigational criteria for UUVs. The key source of navigational aids for different deep-sea research projects is water currents. These days, many different sensors are available to monitor the UUV’s velocity. In recent times, there have been five primary types of sensors utilized for UUV velocity forecasts. These include Doppler Velocity Logger sensors, paddlewheel sensors, optical sensors, electromagnetic sensors, and ultrasonic sensors. The most popular sensing sensor for estimating velocity at the moment is the Doppler Velocity Logger (DVL) sensor. DVL sensor is the most fully developed sensor for UUVs in recent years. In this work, we offer an overview of the field of navigation systems and sensors (especially velocity) developed for UUVs with respect to their use with tidal current sensing in the UUV setting, including their history, evolution, current research initiatives, and anticipated future.

Unmanned underwater vehicles (UUVs) have become increasingly popular in recent years due to their use in various applications. The motivations for using UUVs include the exploration of difficult and dangerous underwater environments, military tasks in mine detection, intelligence gathering and surveillance, the inspection of offshore oil and gas infrastructure in the oil and gas industry, scientific research for studying marine life, and the search and rescue of missing persons or submerged airplanes or boats in underwater environments. UUVs offer many advantages in achieving the desired applications with increased safety, efficiency, and cost-effectiveness. However, there are also several challenges associated with their communication, navigation, power requirements, maintenance, and payload limitations. These types of vehicles are also prone to various disturbances caused by currents of the ocean, propulsion systems, and unmolded uncertainties. Practically, it is a challenging task to design a controller that will ensure optimal performance under these conditions. Therefore, the control system design is of prime importance in the overall development of UUVs. Also, the UUV controller receives input from different sensors, and the data from these sensors are used by the controller to perform different tasks. The control systems of UUVs should take into account all uncertainties and make them stable so that all sensors can perform optimally. This paper presents a complete review of different control system design algorithms for UUVs. The basic logic designs of several control system algorithms are also presented. A comparison is made based on reliability, robustness, precession, and the ability of the controller to handle the nonlinearity that is faced by UUVs during their missions. Simulation and experimental results are thoroughly studied to gain insight into each algorithm. The advantages and disadvantages of each algorithm are also presented, which will facilitate the selection of a suitable algorithm for the control system design of UUVs.

In this study, a survey on control allocation algorithms in tactical level control for path tracking unmanned surface vehicles (USV) is conducted. The strategic goal in the path tracking problem is to assist navigation solution of an unmanned underwater vehicle (UUV). USV with the help of its onboard acoustic sensors, tracks UUV according to constant bearing guidance rule. The survey on tactical controllers comprises comparisons of tracking performances of USVs under proportional-integral-derivative, pole placement, feedback linearization and sliding mode controllers according to the strategic goal. The parameters of the controllers are tuned with a common elitist genetic algorithm optimization infrastructure. The disturbance rejection capabilities of the controllers are discussed through Monte Carlo simulations of USVs within various wave disturbances as well.

This paper will discuss development work for a Navy unmanned surface vehicle called NIX for its use in multi-platform collaborative autonomy for S&T development efforts. The NIX platform is an 80” long by 40” wide M-Hull design. The M-Hull concept includes two full-length slats in its design which provides enhanced inherent tracking stability. Currently, the NIX is being outfitted with an optical imaging receiver to support high-resolution bottom imaging when paired with an unmanned underwater vehicle (UUV) that is outfitted with a laser illuminator. Together, the NIX and the UUV will form a complete bistatic laser imaging system. The bistatic imaging architecture is optimized for use in multi-platform collaborative autonomy. Precision tracking within a specific conical volume of the UUV is critical for optimal performance of the imaging system.

Advances in robotic mapping, planning, and perception have spurred applications-based robotics research in the domain of infrastructure inspection and preservation. Though a significant portion of this research has centered around the use of unmanned aerial, ground, and underwater vehicles, research in the use of unmanned surface vehicles (USVs) is limited. USVs present a unique opportunity to capture combined maps above and below water, which is essential for the inspection of waterspanning bridges, harbors, dams, and levees. In this paper, we investigate the use of USVs for infrastructure inspection by outfitting a USV platform with a multibeam sonar, horizontally and vertically mounted lidars, several ruggedized RGB cameras, and a high-rate inertial measurement unit (IMU). By time-synchronizing all sensors, we are able to fuse information collected from lidar, camera, and IMU units via tightly-coupled lidar-visual-inertial (LVI) simultaneous mapping and localization (SLAM). We validate our methodology by collecting sensory data of an abandoned quarry and by generating a combined 3D point cloud map using lidar data, multibeam sonar data, and maximum a posteriori trajectory from the LVI SLAM approach. Experiments validate the performance of the proposed USV system, highlighting challenges in extrinsic calibration of non-overlapping sensors, sonar denoising, and refined inter-keyframe pose estimation for key-frame based SLAM approaches.

Unmanned underwater vehicles require a hull resistant to immersion and, therefore, to hydrostatic pressure, which places high demands on its design, manufacture and inspection, where dimensional control is a fundamental part of the verification of the shapes of the structure. In this research, a comparison is made of the dimensional control techniques currently used for the naval sector and their viability in the field of unmanned underwater vehicles. A cylindrical body steel model will be measured, with the characteristic dimensions of the unmanned underwater vehicles, executing tests using three measurement techniques, such as the optical measurement of surface points, the surface probing technology and the surface laser scanner with large volume of points. Experimental data will be provided in terms of mean diameter of the sections that make up the hull, defect of circularity and position of the optimum centre, which will lead to the development of a guide of good practices for selecting and using each technique depending on the requirements and demands of the unmanned underwater vehicle under study.

In modern marine warfare, unmanned underwater vehicles (UUVs) have fast and efficient attack capabilities. However, existing research on UUV attack strategies is relatively limited, often ignoring the requirement for the effective allocation of different strategic value areas, which restricts its performance in the marine combat environment. To this end, this paper proposes an innovative UUV task allocation and saturation attack strategy. The strategy first divides the area according to the distribution density of enemy UUVs, and then reasonably allocates tasks according to the enemy’s regional value and the attack capability of our UUVs. Our UUVs then sail to the enemy area and are evenly distributed in the encirclement to ensure accurate saturation attacks. In the task allocation link, the grey wolf optimizer is improved by introducing Logistic chaos mapping and differential evolution mechanism, which improves the search efficiency and allocation accuracy. At the same time, the combination of the optimal matching algorithm and Bezier curve dynamic path control ensures the accuracy and flexibility of a coordinated attack. The simulation experimental results show that the strategy shows high attack efficiency and practicality in marine combat scenarios, providing an effective solution for UUV attack tasks in complex marine environments.

Focusing on coordination and consensus, this paper, addresses a control problem for a group of unmanned underwater vehicles (UUVs) by tracking a maneuvering target with varying velocity and time delays. To realize coordinated target tracking, consensus control of multiple UUVs requires neighboring UUV state information, detected target state information, and estimated target acceleration information. At least one UUV is assumed to be capable of obtaining information about the target, and the communication topology graph of the vehicle is assumed to be undirected connected. We consider the convergence analysis of this multi-UUV system for two conditions: information interaction between the target and an UUV with time delays and information interaction between the target and an UUV without time delays. Sufficient conditions for the uniform ultimate boundedness of the tracking errors and estimation errors are obtained by utilizing a Lyapnov-Krasovskii functional. Two simulations are presented to demonstrate the effectiveness of the proposed method.

As the use of unmanned surface and underwater vehicles (USVs and UUVs) increases, the acoustic signature and self-noise of these vehicles become important for certain type of applications. For low-detection probability the UUV or USV must have a low-acoustic signature. Furthermore, the self-noise of the UUV or USV may interfere with on-board sonar sensors, especially as more sophisticated sonar systems are being developed. As the concept of the USV or UUV is to design for low cost and low weight, with low availability of power, it is important to address the mitigation of the acoustic signature during the design phase through estimation techniques based on modeling and component level selection. Additionally during the test and integration phase, methods to measure the acoustic signature without resorting to expensive offshore measurements in “quiet” acoustic test ranges are required. In this presentation some of the approaches available for modeling and testing are discussed, together with the challenges faced by noise control engineers working these type problems and the type of noise sources that have to be addressed.