Underwater Robotic Vehicles Research Articles

The Haidou‐1 hybrid underwater vehicle for the Mariana Trench science exploration to 10,908 m depth

AbstractAn unmanned Autonomous and Remotely Operated Vehicle (ARV), Haidou‐1, visited the Challenger Deep in the Mariana Trench, and performed observation, sampling and bathymetric mapping explorations at the trench bottom. The Haidou‐1 vehicle reached a depth of 10,908 m in the west pool of the Challenger Deep and probed a depth of 10,909 m in the east pool. The 2600 kg underwater robotic vehicle could conduct survey missions with full autonomy and can also be remotely operated through a light fiber tether. Haidou‐1 carries an electric manipulator to implement lightweight intervention tasks. The fiber‐optical tether enables long‐distance real‐time high‐bandwidth communication at full‐ocean depth, thereby providing situational awareness and remote intervention. The hybrid concept we defined for the Haidou‐1 vehicle refers to three typical working modes: Autonomous Underwater Vehicle mode, Remotely Operated Vehicle mode, and ARV mode. There is no need to change any structural configuration at sea to meet the needs of multidisciplinary oceanographic investigation. This paper reports the overview design of Haidou‐1. Practical field trials at the Challenger Deep were conducted to validate the feasibility and performance of the developed system. In the aggregate, eight dives exceeded 10,000 m counting all three operation modes. Some of the initial results are presented including the high‐resolution bathymetric map created by Haidou‐1 onboard sonar, and no similar results have been found yet.

Disturbance rejection controller design based on adaptive nonlinear FOPID controller and chaotic WOA with a neuro-fuzzy approximation for URV robot

This paper presents an adaptive neuro-fuzzy-based nonlinear fractional order proportional integral derivative (ANF-NLFOPID) controller to stabilize six degrees of freedom (6-DOF) underwater robotic vehicle (URV). Generally, the stability of the URV system is jammed due to internal and external variations related to unknown uncertainties and disturbances in the URV model, which lead to trajectory tracking problems. Thus, to solve unknown uncertainties and disturbances problems, an ANF network is proposed to estimate unknown uncertainties and disturbances. At the same time, an NLFOPID controller is proposed to minimize the error effect generated by the variation of the URV model parameters. Considering the unknown and unpredictable behavior of the URV system in the presence of uncertainties and disturbances, the ANF-NLFOPID controller parameters are tuned continuously using an improved whale optimization algorithm based on chaotic theory (IWOA-CT). The main working principle of the IWOA-CT is to solve the local minimum (optimum) problem and achieve the global optimum points to deliver the best parameter values for the ANF-NLFOPID controller. A simulation and experimental results are conducted to measure the performance of the ANF-NLFOPID controller compared to other existing works. MATLAB software is used to simulate four trajectory tracking cases, where the first case proved the superiority of the ANF-NLFOPID controller by 52.559%, 70.028%, and 73.83%, the second case shows that the ANF-NLFOPID improves the trajectory tracking performance by 34.399%, 46.094%, and 59.143%, the third case demonstrates the effectiveness of the ANF-NLFOPID controller by 41.922%, 51.205%, and 62.252%, and the fourth case shows that the ANF-NLFOPID enhance the overall trajectory tracking efficiency by 29.356%, 38.413%, and 44.795% compared to adaptive neural network-based nonlinear FOPID (ANNFOPID), adaptive fuzzy-based nonlinear PID (AFNLPID), and disturbance rejection based on adaptive neural network (DR-ANN) controllers respectively. In the end, the experimental results were conducted using a real-world URV model and showed that the ANF-NLFOPID controller presents superior in solving trajectory tracking problems compared to the ANNFOPID controller.

Kinematics, dynamics, and control of underwater robotic snake based on a rigid-soft unified model

ABSTRACT With the advancement of underwater biomimetic robots, many kinds of underwater snake robots have been developed to perform various marine inspection and maintenance operations. This paper introduces an innovative biomimetic extension to underwater robotic vehicles, an underwater rigid-soft snake robot, which is operated by a combination of rigid propulsion modules and soft joint modules. The essential point is how to jointly mathematically model soft joints and rigid modules with different physical property. The Constant Curvature assumption is widely used in modeling of soft module robots. However, the limitation of this assumption is that it can't accurately describe the deformation of soft robots when performing dynamic tasks. We propose a methodology, rigid-soft unified model, for kinematic and dynamic modeling by viewing soft joint as flexible universal joint. The motion analysis of the robot under the influence of water flow in different postures is completed. Furthermore, we develop a closed loop hierarchical trajectory controller for the snake robot. Especially in the part of dynamic control system, we compare the tracking performance of different controllers.

An adaptive neural network with nonlinear FOPID design of underwater robotic vehicle in the presence of disturbances, uncertainty, and obstacles

An adaptive neural network with nonlinear fractional-order PID (ANNFOPID) controller design is proposed for underwater robotic vehicle (URV) to solve the path tracking problem. The path tracking problem is caused by disturbances and unknown uncertainties of the underwater vehicle dynamic model. The disturbances were presented with the URV model to evaluate the performance of the ANNFOPID controller to reject the disturbances. At the same time, an obstacle avoidance model has been presented with ANNFOPID controller to evaluate the controller ability to maneuver around different obstacle locations. A radial base function (RBF) has been used to estimate both of the disturbances and the unknown uncertainties of the dynamic model. An improved slime mould algorithm (ISMA) is presented to invent a new trajectories for the underwater vehicle and enhance the ability of the URV to overcome the obstacles problems. At the end, the results obtained show that the ANNFOPID controller present an outstanding performance in comparison with other existing works to overcome the disturbances, unknown uncertainties, and obstacles problems effectively.

3D Path Following Control of an Autonomous Underwater Robotic Vehicle Using Backstepping Approach Based Robust State Feedback Optimal Control Law

This work renders the design of a robust state feedback optimal control strategy for an Autonomous Underwater Robotic Vehicle (AURV). The control strategy is developed using a polytopic approach based on hydrodynamic parameter variation. Besides, a backstepping approach is designed to control the kinematics of the system. However, the dynamics of the AURV system are controlled by a robust optimal control technique. In this work, the decoupled systems for both horizontal and vertical dynamics of AURV are used for the development of the control algorithms. Furthermore, the 3-D path following is achieved by integrating the control algorithms of both horizontal and vertical dynamics of AURV. The proposed controller is formulated using semi-definite programming (SDP). To track the 3-D path, it is intended to track both the desired depth and desired yaw in diving and steering planes. The simulation studies are conducted through MATLAB/Simulink environment using the YALMIP tool. Furthermore, the robust behavior of the proposed control algorithm is verified by considering the uncertain hydrodynamic parameters.

A novel technique for modelling of an Underwater Robotic Vehicle

A novel technique for modelling of an Underwater Robotic Vehicle

Three-Dimensional Hydrodynamic Analysis of a Flexible Caudal Fin

A 3D fluid–structure coupled simulation of a square flexible flapper, the basic model of a caudal fin, is performed to visualize the flow field around the caudal fin. A plate immersed in a water tank is driven to oscillate vertically by its leading edge. A quantitative analysis of the thrust generated by the plate, which is difficult to explore experimentally, is performed over a range of non-dimensional flapping frequencies 0.93 <f*< 1.47 to explore the mechanism of thrust generation in more detail. Comparisons are made between three different flapping frequencies around the structural resonance. Numerical results at different flapping frequencies provide a reasonable estimate of the trailing edge amplitude and phase lag of the motion of the plate’s leading and trailing edges. The pressure distribution and deformation of the plate are analyzed to estimate the time evolution of the maximum and minimum thrust generation during the flapping period. Variations in pressure distribution on the plate surface are mainly due to the displacement of the trailing edge relative to the leading edge. Thrust is mainly provided by the pressure difference at the trailing edge. The maximum thrust was found to correspond to the maximum relative deformation of the trailing edge. The optimum frequency f* = 1.2 corresponding to the maximum thrust generation does not coincide with the structural resonance frequency, but remains at a frequency slightly higher than the resonance. These results indicate that the relative deformation of the plate plays an important role in the estimation of the flow field and the associated thrust generation. The numerical results may provide new guidelines for the design of robotic underwater vehicles.

Dynamic Modeling of Underwater Snake Robot by Hybrid Rigid-Soft Actuation

For decades, underwater vehicles have been performing underwater operations, which are critical to the development and upgrading of underwater robots. With the advancement of technology, various types of robots have been developed. The underwater robotic snake is a bioinspired addition to the family of underwater robotic vehicles. In this paper, we propose an innovative underwater snake robot actuated by rigid propulsions and soft joints, which can improve the swimming efficiency and flexibility of the robot and reduce the probability of collision leading to damage. Existing math models of robotic snakes typically incorporate only planar motion, rarely considering spatial motion. So, we formulate a complete three-dimensional dynamic model for the robotic snake, which is extended by deriving expressions for the geometric Jacobians. This modeling approach is well suited since it provides compact matrix expressions and easy implementation. We use the constant curvature method to describe the configuration of the soft joint, use the Lagrangian method to obtain its dynamic characteristics, and focus on deriving the visco-hyperelastic mechanical energy of the soft material. Next, the local dynamics of soft members are extended as a nonholonomic constraint form for modeling the snake robot. Finally, the multi-modal swimming behavior of the robot has been verified by simulations, including forward and backward rectilinear motion, yaw turning, pitch motion, and spiral rising motion. The overall results demonstrate the effectiveness and the versatility of the developed dynamic model in the prediction of the robot trajectory, position, orientation, and velocity.

Disturbance rejection based on adaptive neural network controller design for underwater robotic vehicle

Disturbance rejection based on adaptive neural network controller design for underwater robotic vehicle

An Adaptive Nonlinear PID Design for 6-DOF Underwater Robotic Vehicle

An Adaptive Nonlinear PID (ANLPID) controller for six Degrees of Freedom (6-DOF) Underwater Robotic Vehicle (URV) model is proposed to solve the path tracking problem. The path tracking problem is mainly caused by external environmental disturbances and the unknown uncertainties of the URV model. The ANLPID controller is used to estimate both the external disturbances and the unknown URV uncertainties. The performance of the ANLPID controller was evaluated by comparing the ANLPID controller with other existing works that are Nonlinear PID (NLPID) controller and Nonlinear Fractional PID (NLFOPID) controller. The system stability is proved by utilizing the Lyapunov function. At the end, the results obtained show the proficiency of the ANLPID controller, where the ANLPID controller improved the performance of the URV by 41.4185% compared to the NLPID controller and by 54.6479% compared to the NLFOPID controller.

Benthic megafauna habitats, community structure and environmental drivers at Rio Grande Rise (SW Atlantic)

The Rio Grande Rise (RGR) is a large and geomorphologically complex feature located in the Southwest Atlantic, with great commercial and scientific interest due to its potential for mining rare earth elements that are critical for low-carbon technologies. Brazilian interest in this area led to the submission of a petition to the UN Commission on the Limits of the Continental Shelf in 2018 to include RGR on the limits of its continental shelf beyond 200 nautical miles. However, mining activities are potentially harmful to deep-sea ecosystems and will likely cause some extent of biodiversity loss. Thus, baseline and continuous environmental studies in the RGR are important to address potential conflicts between mineral extraction and the conservation of deep-sea biodiversity. The RGR is characterized by a series of summit plateaus of ∼600 m deep divided NE-SW by a rift valley, up to 2000 m deep. In 2018, the plateaus and rift of a small area in RGR (30°35′S – 31°03′S, 35°36′W – 36°16′W) were explored through 13 dives of the robotic underwater vehicle (RUV) HyBIS. Videos were analyzed for the description of structuring factors (topography and habitat types) and to record benthic megafauna occurrences. Video transects revealed highly heterogeneous and rapidly changing habitats. Eleven habitats, five in the rift and six in the plateaus are proposed based on geomorphology, slope, and substrate textures. We recorded 17,008 megabenthic organisms classified in 83 morphotypes and six different phyla, from which Porifera (42.7%) and Cnidaria (41.5%) were the most representative. Samples were characterized by a high dominance and the dissimilarities result chiefly from differences in abundance scores. PERMANOVA tests indicated that Habitat and Region variables were the most important to explain structure within the community data, followed by depth and slope. The rift floor exhibited a low abundance of megabenthic epifauna, except in a sinkhole in the northern part of the rift. The lower and upper rift wall were characterized by different communities delimited by the transition between the Antarctic Intermediate Water and the Upper Circumpolar Deep Water. The habitats formed by Fe–Mn deposits were dominated by distinct communities, which were rarely observed elsewhere. Additionally, we found variations in community structure at regional scales (20–30 km), with distinct communities on each side of the rift and at the southwest of the study area. Our results contribute toward understanding the diversity, biogeography, and environmental drivers of the RGR. Fauna distribution is patchy, linked to habitats with potential mining resources, and dominated by Vulnerable Marine Ecosystems (VMEs) indicator taxa. Extensive community analysis should occur at a given site prior to consideration for the exploitation of natural resources.

Disturbance Rejection for Underwater robotic vehicle based on adaptive fuzzy with nonlinear PID controller

In this paper, an adaptive fuzzy with a nonlinear PID (AFNLPID) controller is suggested to solve and eliminate the effect of the disturbances regularly caused by the ocean currents and the unknown uncertainties of the underwater robotic vehicle (URV) dynamics. The main principle of the AFNLPID controller is to estimate the unknown dynamics parameters of the URV and estimate the unknown disturbances. Two types of disturbances are presented that are deepwater wave disturbances and near-surface shallow water wave disturbances. The outstanding properties of the AFNLPID were evaluated by comparing the designed controller with other existing works that are adaptive fuzzy PID (AFPID, AFPID2) controllers, conventional PID controllers, and nonlinear fractional-order PID (NLFOPID) controllers. At the end, the collected results show that the AFNLPID controller improved the efficiency of the URV for deepwater disturbances by 42.0663%, 37.0490%, 24.4449%, 64.7356%, and 51.7643% for AFPID, AFPID2, AFNLPID2, PID, and NLFOPID controllers, respectively. At the same time, the AFNLPID improved the efficiency of the URV for near-surface wave disturbances by 45.0911%, 32.2492%, 20.3839%, 56.5498%, and 51.3964% for AFPID, AFPID2, AFNLPID2, PID, and NLFOPID controllers, respectively.

ПІДВИЩЕННЯ ЕФЕКТИВНОСТІ ЗАСТОСУВАННЯ БЕЗЕКІПАЖНИХ ПІДВОДНИХ АПАРАТІВ ДЛЯ ПОТРЕБ ВІЙСЬКОВО-МОРСЬКИХ СИЛ ЗБРОЙНИХ СИЛ УКРАЇНИ

The article considers the problems related to the need to use unmanned submarines for the needs of the Navy of the Armed Forces of Ukraine with the possibility of using the latest information technologies, namely,  study of acoustic means of monitoring physical processes in the marine environment, which are the most effective technologies , which significantly supplement and expand the possibilities of contact methods for measuring environmental indicators in technical solutions for underwater monitoring. Methods of solving the tasks on the basis of optimal use of sonar underwater monitoring are proposed in order to increase the overall sensitivity of the sonar system to the useful signal and reduce the sensitivity to "natural" background or intentional interference by using small multi-beam sonar MEMS technology using. Modular design of underwater robotic vehicles, which are one of the promising areas of development of naval equipment, based on the principle of open architecture involves the construction of their components as integral functional elements of the modular type. Therefore, there is a need to create cheap, easy to manufacture and install small hydroacoustic blocks-modules based on the use of MEMS technology, which reduces the overall cost and increases the survivability of the BPA as a whole. It should be noted that the modular design of underwater robotic vehicles, which are one of the promising areas of development of naval equipment, based on the principle of open architecture involves the construction of their components (basic elements) as integral functional elements of the modular type. It is proposed to use the obtained results in the course of further research within the framework of research and development on the creation of promising mobile unmanned aerial vehicles for underwater monitoring and surveillance. Keywords: unmanned underwater vehicle, robotic search and observation technologies, marine situation, underwater situation, microelectromechanical systems.

An Innovative Low Cost Educational Underwater Robotics Platform for Promoting Engineering Interest among Secondary School Students

The presented article describes the design features of an educational robotics project addressed for secondary school students and carried out at the University of Girona (UdG). The project, called Underwater Robotics Workshop, is about the students building an underwater exploration robotic vehicle using low-cost materials. Its ultimate objective is to promote engineering interest among students and motivate them to direct their future studies towards engineering degrees. The main purpose of this article is to describe this activity and to promote it. Versatility and adaptation are key values as the activity has been designed to be adapted to convenience or replicated. It is a continuation work of a previously published articles, now describing different technological adaptations related to the design of the vehicle’s controller, and the gathered experiences from added workshop celebrations in the recent years. The workshop has been defined as a project-based learning approach where the students learn about physics, engineering, electronics, programming, and robotics, as well as to use all kinds of working tools, according to the maker philosophy. To date, the opinions collected from the participants encourage continuation of the activity and, at the same time, ask for the introduction of novelties to keep the workshop updated with the contents of the subjects related to technology and sciences. This project is being held for more than 13 years in the UdG. More than 800 secondary school students have participated in the activity, building about 200 underwater vehicles in more than 50 editions of the workshop.

MODEL PREDICTIVE CONTROL OF AN AUV USING DE-COUPLED APPROACH

This paper considers the decoupled dynamics and control of an Autonomous Underwater Vehicle (AUV). The decoupled model consists of speed, steering and depth subsystems. Generally AUV model is unstable and nonlinear. The central theme of this paper is the development of model predictive control (MPC) for underwater robotic vehicle for ocean survey applications. The proposed MPC for decoupled structure can have simple implementation. Simulation results have been presented which confirm satisfactory performance. Decoupled approach is well suitable for applying control.

Controller design for underwater robotic vehicle based on improved whale optimization algorithm

This paper presents the impact of introducing a two-controller on the linearized autonomous underwater vehicle (AUV) for vertical motion control. These controllers are presented to overcome the sensor noise of the AUV control model that effect on the tolerance and stability of the depth motion control. Linear quadratic Gaussian (LQG) controller is cascaded with AUV model to adapt the tolerance and the stability of the system and compared with FOPID established by the improved whale optimization algorithm (IWOA) to identify which controlling method can make the system more harmonize and tolerable. The developed algorithm is based on improving the original WOA by reshaping a specific detail on WOA to earn a warranty that the new IWOA will have values for the update position lower than the identified lower-bound (LB), and upper-bound (UB). Furthermore, the algorithm is examined by a set of test functions that include (unimodal, multimodal and fixed dimension multimodal functions). The privileges of applying IWOA are reducing the executing time and obtaining the semi-optimal objective function as compared with the original WOA algorithm and other popular swarm-intelligence optimization algorithms.

Performance Analysis of Ice-Relative Upward-Looking Doppler Navigation of Underwater Vehicles Beneath Moving Sea Ice

This paper addresses the problem of ice-relative underwater robotic vehicle navigation relative to moving or stationary contiguous sea ice. A review of previously-reported under-ice navigation methods is given, as well as motivation for the use of under-ice robotic vehicles with precision navigation capabilities. We then describe our proposed approach, which employs two or more satellite navigation beacons atop the sea ice along with other precision vehicle and ship mounted navigation sensors to estimate vehicle, ice, and ship states by means of an Extended Kalman Filter. A performances sensitivity analysis for a simulated 7.7 km under ice survey is reported. The number and the location of ice deployed satellite beacons, rotational and translational ice velocity, and separation of ship-based acoustic range sensors are varied, and their effects on estimate error and uncertainty are examined. Results suggest that increasing the number and/or separation of ice-deployed satellite beacons reduces estimate uncertainty, whereas increasing separation of ship-based acoustic range sensors has little impact on estimate uncertainty. Decreasing ice velocity is also correlated with reduced estimate uncertainty. Our analysis suggests that the proposed method is feasible and can offer scientifically useful navigation accuracy over a range of operating conditions.

Self-Organizing Neuro-Fuzzy Control for Underwater Robotic Vehicles.(Dept.E)

Underwater robotic vehicles have become an important tool for various underwater tasks because they have greater speed, endurance and depth capability, as well as a higher factor of safety, than human divers. However, most vehicle control system designs have been based on a simplified vehicle model, which has often resulted in poor performance because the nonlinear and time-varying vehicle dynamics lave parameters uncertainty. It is desirable to have an advanced control system with the capability of learning and adapting to change in the vehicle dynamies and parameters. The proposed system is possessing neural network's learning ability. There are no rules initially in the proposed system. They are created and adapted as on-line leaning proceeds via simultaneous structure and parameter identification. The identification process of the controller includes both structure and parameter learning.

Watertight integrity of underwater robotic vehicles by self-healing mechanism

Self-healing mechanism (SHM) application has attracted interest due to ability to self-heal as response to damage situations in various conditions, and is being actively explored. However, the application of SHM that can be autonomously triggered for temporarily keeping structural integrity of underwater robotic vehicle (URV) under flooding condition is still scarce publicly. This paper describes an investigation in watertight integrity performance of URV’s hull under damaged stability criteria. The main goal is to investigate the characterization of a rapid SHM through an experiment for identifying progressive flooding in a damaged URV’s hull. Here, it is demonstrated that the effectiveness of sodium polyacrylate, a kind of superabsorbent polymers (SAP), had been studied by applying the polymer on an experimental model of damaged URV’s hull. A comparison is studied for the stability of the flooded URV and the mass of water accumulated inside the URV’s hull between the cases of before and after applying the SHM in the damaged model under different damaged conditions. The results showed that the SHM application had rapidly blocked the damaged leak hole and prevented severe water flow ingress in the damaged URV’s hull. Swift recovery of buoyancy was obtained, as the volume of absorbed water by SHM was converted into equivalent buoyancy loss. These findings are establishing a fundamental knowledge for implementation of SHM in underwater robotic structures.

Scientific Challenges and Present Capabilities in Underwater Robotic Vehicle Design and Navigation for Oceanographic Exploration Under-Ice

This paper reviews the scientific motivation and challenges, development, and use of underwater robotic vehicles designed for use in ice-covered waters, with special attention paid to the navigation systems employed for under-ice deployments. Scientific needs for routine access under fixed and moving ice by underwater robotic vehicles are reviewed in the contexts of geology and geophysics, biology, sea ice and climate, ice shelves, and seafloor mapping. The challenges of under-ice vehicle design and navigation are summarized. The paper reviews all known under-ice robotic vehicles and their associated navigation systems, categorizing them by vehicle type (tethered, untethered, hybrid, and glider) and by the type of ice they were designed for (fixed glacial or sea ice and moving sea ice).