Autonomous Unmanned Underwater Vehicles Research Articles

Synthetic data formation for machine learning recognition of underwater objects

The main problem of machine learning for control systems of unmanned underwater vehicles is objectively very small samples of real data. The study aim was to develop an approach to the creation of synthetic data describing underwater objects for as the samples for training and validation in machine learning of control systems for auton-omous unmanned underwater vehicles. The subject of the study was a variety of underwater objects because real information about the shape, size and their external images is very limited. The data augmentation method was used, which makes it possible to obtain additional data on underdetermined objects of observation from the initial data while maintaining the classification features. Eight models have been developed that imitate the influence of various factors of the aquatic environment and allow using various augmentation methods (changing the position, adding noise, glare to the image, defocusing to create fuzziness; fragmentation, etc.) to obtain an almost unlimited number of images of any objects of man-made activity immersed in underwater environment, to varying degrees similar to the reference. Examples of the use of augmentation models that take into account changes in illumina-tion, transparency and the presence of an underwater landscape are given. Such synthetic (model) images may be the basis of a training set for machine learning to recognize and identify underwater objects. The trained model can be used as the basis of a decision support system for operators of remote-controlled unmanned underwater vehicles and as the basis for building control systems for autonomous uninhabited underwater vehicles for moni-toring underwater spaces.

Comparative study on real-time pose estimation of vision-based unmanned underwater vehicles

Background: Navigation and localization are key to the successful execution of autonomous unmanned underwater vehicles (UUVs) in marine environmental monitoring, underwater 3D mapping, and ocean resource surveys. The estimation of the position and the orientation of autonomous UUVs are a long-standing challenging and fundamental problem. As one of the underwater sensors, camera has always been the focus of attention due to its advantages of low cost and rich content information in low visibility waters, especially in the fields of visual perception of the underwater environment, target recognition and tracking. At present, the visual real-time pose estimation technology that can be used for UUVs is mainly divided into geometry-based visual positioning algorithms and deep learning-based visual positioning algorithms. Methods: In order to compare the performance of different positioning algorithms and strategies, this paper uses C++ and python, takes the ORB-SLAM3 algorithm and DF-VO algorithm as representatives to conduct a comparative experiment and analysis. Results: The geometry-based algorithm ORB-SLAM3 is less affected by illumination, performs more stably in different underwater environments, and has a shorter calculation time, but its robustness is poor in complex environments. The visual positioning algorithm DF-VO based on deep learning takes longer time to compute, and the positioning accuracy is more easily affected by illumination, especially in dark conditions. However, its robustness is better in unstructured environments such as large-scale image rotation and dynamic object interference. Conclusions: In general, the deep learning-based algorithm is more robust, but multiple deep learning networks make it need more time to compute. The geometry-based method costs less time and is more accurate in low-light and turbid underwater conditions. However, in real underwater situations, these two methods can be connected as binocular vision or methods of multi-sensor combined pose estimation.

ANALYSIS OF AUTOMATIC CONTROL SYSTEMS OF A MULTIPURPOSE AUTONOMOUS UNMANNED UNDERWATER VEHICLE WITH COMPLEX MOTION DYNAMICS

The overview article is devoted to the analysis of control systems of autonomous unmanned underwater vehicles, which belong to robotic underwater complexes and are used to provide search and deep-sea emergency and rescue operations, survey of various underwater objects (main pipelines, bottom structures, ship hulls, etc.), conducting scientific oceanographic surveys research, monitoring of the marine environment. The work examines scientific literary sources, which provide the results of development and research of orientation, navigation and motion control systems of multi-purpose autonomous unmanned underwater vehicles with complex movement dynamics, in particular when performing missions in a limited space with movement along complex trajectories. Special attention is focused on such modes of movement of devices as trajectory tracking, path-following and way point tracking. An analysis of the means of navigation and control, which can be used to ensure different modes of movement, was carried out, as well as the directions of development of both the unmanned underwater vehicles themselves and their control systems were considered.
 In order to substantiate the development of a control system for a multi-purpose maneuverable mini-class autonomous vehicle, the main requirements are formulated. It is proposed to conduct a synthesis and research of the control system based on the simulation of the dynamics of the movement of the mini-vehicle for different modes of movement in terms of parameters and trajectories, to develop algorithms for the adaptive control of the vehicle, to improve the system orientation and navigation, built on the basis of MEMS sensors. An information model of the development process is proposed and substantiated, which specifies the sequence of determining important parameters and characteristics of the vehicle and performing important stages of synthesis and analysis of the control system.

Filtering of Wind-wave Effects in Controlling the Depth of Stabilization of an Autonomous Unmanned Underwater Vehicle

Autonomous underwater vehicles (AUVs) and robots play an essential role in underwater technology. The tasks that these machines are required to do often involve submerging to a certain depth, where the object of work or research is located. The success of the mission and the accuracy of control at that depth largely relies upon the precision and immunity to interference of the pressure sensors, which are used to measure the depth of the underwater device. This work presents a method for addressing issues caused by external disturbances, internal interference and inaccuracies in the instrumentation used for measurement. The research was conducted to see if the Kalman filter could be used to make systems more resistant to noise. To do this, the structure and algorithm of Kalman filtering of wind wave impact as a random stationary process was developed. The theories of automatic control, the theory of filtering of probabilistic signals, and the methods of computer modeling were used in the research

Моделювання та аналіз складного руху автономного безпілотного підводного апарата

Ensuring autonomy, maneuverability and organization of movement control along complex trajectories of a maneuverable multi-purpose autonomous unmanned underwater vehicle (AUUV) is a complex scientific research and engineering task, for the solution of which it is necessary to know the behavior of the vehicle in the environment and the influence of the environment on the dynamics of the vehicle. Plots of the distribution of speed, pressure and kinetic energy of turbulence during the complex movement of the AUUV were obtained, in accordance with the chosen trajectories. Simulation and numerical modeling of AUUV under complex motion was carried out. The obtained results were compared with the results of rectilinear movement. showed that the construction of the ABPA model is acceptable both for straight-line movement and for movement along complex trajectories. A comparative analysis of the obtained values of speed, pressure and kinetic energy of turbulence shows the ability of the developed model of the device to perform quick maneuvers in limited areas (turning around, avoiding obstacles, etc.). The selected and designed ABPA model is suitable for further research in order to develop an automatic control system for a maneuverable multi-purpose AUUV.

Comparative study on real-time pose estimation of vision-based unmanned underwater vehicles

Background: Navigation and localization are key to the successful execution of autonomous unmanned underwater vehicles (UUVs) in marine environmental monitoring, underwater 3D mapping, and ocean resource surveys. The estimation of the position and the orientation of autonomous UUVs are a long-standing challenging and fundamental problem. As one of the underwater sensors, camera has always been the focus of attention due to its advantages of low cost and rich content information in visibility waters, especially in the fields of visual perception of the underwater environment, target recognition and tracking. At present, the visual real-time pose estimation technology that can be used for UUVs is mainly divided into geometry-based visual positioning algorithms and deep learning-based visual positioning algorithms. Methods: In order to compare the performance of different positioning algorithms and strategies, this paper uses C++ and python, takes the ORB-SLAM3 algorithm and DF-VO algorithm as representatives to conduct a comparative experiment and analysis. Results: The geometry-based algorithm ORB-SLAM3 is less affected by illumination, performs more stably in different underwater environments, and has a shorter calculation time, but its robustness is poor in complex environments. The visual positioning algorithm DF-VO based on deep learning takes longer time to compute, and the positioning accuracy is more easily affected by illumination, especially in dark conditions. However, its robustness is better in unstructured environments such as large-scale image rotation and dynamic object interference. Conclusions: In general, the deep learning-based algorithm is more robust, but multiple deep learning networks make it need more time to compute. The geometry-based method costs less time and is more accurate in low-light and turbid underwater conditions. However, in real underwater situations, these two methods can be connected as binocular vision or methods of multi-sensor combined pose estimation.

Resilient sliding mode control of multiple autonomous underwater vehicles under stochastic DoS attack

This paper is concerned with the security sliding mode-based leader-following control of multiple autonomous unmanned underwater vehicles (AUVs) system subject to stochastic DoS attacks. Firstly, a Bernoulli variable is used to describe the phenomenon of stochastic DoS attacks between controllers and actuators, and the attack probability is known for controller design. Secondly, the closed-loop system is established by taking the integral sliding mode control scheme and stochastic DoS attacks into account. Then, the conditions of stochastic stability for system are given by using the stochastic systems analysis method and the model decomposition technique. In the simulation part, a group of AUVs models is used to verify the validity of the proposed state consensus control scheme. The simulation example shows that all the state can achieve consensus even in presence of randomly launched DoS attack.

Promising high-tech export-oriented and demanded by the domestic market areas of marine robotics

In order to develop the Arctic zone of the Russian Federation, in the decree of the President of the Russian Federation, areas related to the development of the Northern Sea Route, environmental protection of the Arctic zone, an increase in the growth rate of geological research and the development of monitoring systems for the Arctic region were separately noted. Also in this document, the main tasks were identified that require careful study, namely: the development and implementation of technologies and equipment for use in Arctic conditions, the improvement of the environmental monitoring system, the use of modern information and communication technologies and communication systems for measurements from satellites, marine and ice platforms, research vessels, ground points and from observatories. These problems and tasks are already being successfully solved abroad with the help of the development of modern systems and devices used as part of marine robotic complexes (MRTC). This article provides a comprehensive analysis of the use of autonomous unmanned underwater vehicles (AUVs) as part of underwater resident systems. Particular attention is paid to the projects already implemented in the external market in the oil and gas industry. The authors present the implemented developments in the field of marine resident robotics in the Russian Federation. In conclusion, the authors for-mulated proposals for the development of the direction of marine robotics, including for solving problems associated with long-term monitoring and operation of the bottom oil and gas infrastructure. Key words Marine robotic complexes, AUV, resident robotics, seabed stations, underwater service work, underwater monitoring.

АЛГОРИТМЫ УПРАВЛЕНИЯ ЭЛЕКТРИЧЕСКОЙ СЕТЬЮ ГИБРИДНОЙ СИСТЕМЫ ЭНЕРГООБЕСПЕЧЕНИЯ АНПА

The aim of the research was to control the electrical network of a hybrid power supply systemfor an autonomous underwater vehicle designed to travel over ultra-long distances over tensof thousands of kilometers. To overcome ultra-long distances, the urgent task is to minimize thespecific consumption of electricity, provided that all consumers are provided with electricity. Therelevance of the work is determined by the novelty of using a hybrid power supply system in autonomousunmanned underwater vehicles, consisting of heterogeneous sources of electricity operatingon different physical principles. Due to the lack of research to date, related to the control ofthe hybrid power supply system, coordinated with the modes of motion of the vehicle in a wide range of speeds, the problem arose of developing control algorithms for the hybrid power supplysystem. To solve the problem, the reasons for the change in current consumption during themovement of the device were analyzed, the necessary conditions for connecting consumers to thebus ducts were formed, including providing all consumers with electricity in full, excluding theexcess of the rated currents of each bus duct with consumption currents, minimizing electricitylosses when passing through the conductor and through the equipment. In this regard, the possibleconfigurations of the construction of the electrical network using conductors and equipment wereanalyzed, and losses on the current conductors and on the equipment used were estimated. Basedon the results of the research, a graph of consumers' connections to the conductors was formed,and to determine the way of connecting each consumer to the energy source through the powergrid, a connection path was determined that minimizes losses. The problem was formalized asfinding the shortest path in a graph, and Dijkstra's algorithm was used as a basis to solve it. Basedon the research results, algorithms were formed for the formation of ways to connect consumers toelectricity sources through the power grid and an algorithm for controlling the switching of keysin the power grid when the consumption currents change. The developed algorithms were implementedin software, and a numerical experiment was carried out using a simulation model. Theresults of the experiment showed the correctness of the developed algorithms, and can be furtherused for implementation in the devices under development for moving over ultra-long distances.

Directions of Development of the Autonomous Unmanned Underwater Vehicles. A Review

Abstract In the paper review of unmanned underwater vehicle (AUV) is presented. The description of main systems is depicted with focus on autonomous single vehicle as well as a swarm. As a consequence of development of AUV technology, research centers are focused on issues related to increasing the degree of their autonomy. Nowadays, mostly navigation and communication as well as high-efficient propeller systems are being developed. There are problems linking this issues. Their solutions includes development of new control laws containing algorithms to prevent collisions - for unmanned vehicles with elements of the underwater environment and for several underwater vehicles cooperating with each other in a swarm.

Fault Tree Analysis of Sensor Technologies for Autonomous UUV Navigation

Autonomous unmanned underwater vehicles (UUVs) are increasingly used for inspection and cleaning tasks. While automating these tasks could greatly reduce the cost, it requires reliable feedback from position and surroundings. Both internal effects and different physical properties affect sensors, resulting in inaccurate feedback if not handled correctly by the navigation system. In this study, an overview of these effects and properties are examined for the most common sensor technologies used for underwater navigation. A fault tree analysis (FTA) is conducted to get knowledge about how the sensor faults, as a result of these effects, affect automated near-structure and off-structure missions, respectively. Moreover, experiments are carried out with a high-resolution sonar and stereo camera to compare the measurement accuracy at different distances. The sensor comparing test shows that cameras can, in some cases, be insufficient to use as the only sensor for obstacle avoidance. It is concluded that the sensor criticality is case-specific; in general, especially faults on attitude feedback are severe for an acceptably-working navigation system and should therefore have high priority when selecting the robotic sensors.

An autonomous unmanned underwater control test vehicle: platform description and experiments

An autonomous unmanned underwater control test vehicle: platform description and experiments

Onboard computing environment of autonomous unmanned underwater vehicles: possible design technologies and their comparative analysis

The paper considers the main tasks of autonomous unmanned underwater vehicles (AUV), lists the requirements for the onboard computing environment. Comparative analysis of central processing unit (CPU), graphics processing unit (GPU), field-programmable gate array (FPGA) and application‐specific integrated circuit (ASIC) has been carried out. The FPGA was considered in more detail as the basis of the AUV onboard computing environment. The given example of designing a device that calculates an arithmetic function demonstrates the high performance of an FPGA and the complexity of developing a simple device in comparison with a similar task on a CPU.

Development of an effective hybrid system for generation and distribution of electric power for autonomous unmanned underwater vehicles

The problem of coordinated operation of a hybrid system for generation and distribution of electric power to provide motion for an underwater vehicle is addressed. The architecture of a multi-agent vehicle system is chosen, the optimum distribution of consumers to electric lines is defined, effective switching of consumers between electric lines, with due regard to the functional and non-functional requirements for the system, is developed.

Co-Design of Fault Detection and Consensus Control Protocol for Multi-Agent Systems Under Hidden DoS Attack

This article is concerned with the co-design of fault detection and consensus control protocol for a class of multi-agent systems (MASs) subject to Denial-of-Service attack, where the attack behavior is hidden to the defender as the adversary may launch the attack with different durations but the defender may not know the real situation at each time instant. Due to the complicated attack behavior, a hidden semi-Markov process is introduced where only the observed attack modes emitted by the inaccessible ones are available. The probability density functions of sojourn time and the semi-Markov kernel are adopted to help analyze the combined fault detection and consensus control system. Sufficient conditions on the σ-error mean square stability of MASs with mixed H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> /H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-</sub> performance are established by using a set of Lyapunov functions that depend on the hidden and the observed attack modes. Moreover, the gain matrices of controller and detector are obtained by solving an optimization problem with some matrix inequality constraints. Finally, the simulation of autonomous unmanned underwater vehicles is used to show the effectiveness of the proposed results.

Analysis of the Effectiveness of Autonomous Unmanned Underwater Vehicle Mine Search Operation by Side Scan Sonar Characteristics

Analysis of the Effectiveness of Autonomous Unmanned Underwater Vehicle Mine Search Operation by Side Scan Sonar Characteristics

Mathematical modeling and synthesis of docking process control for autonomous unmanned underwater vehicle

The paper considers a problem of synthesis of the docking process control of the AUV with the container which belongs to the class of terminal control problems. The method for the synthesis of a two-level control system based on the selection of the dominant component of the state vector and predicting the dynamics of the remaining components at each control step is proposed. In this case, according to the results of the extrapolation of the dynamics to the terminal point, the value of the restriction on the derivative of the dominant component is determined. We synthesize a two-level control system for vertical docking for a specific pair of AUV - container. A thorough analysis of the synthesized control system based on the developed mathematical model is carried out.

Application of Passive Underwater Landmarks for Autonomous Unmanned Underwater Vehicles Navigation

The article describes the design of passive underwater landmarks (PUL) and their use for navigation of autonomous unmanned underwater vehicles (AUV). The procedure of AUV observation using PUL is considered. It is shown that with proper maneuvering of the AUV during observation, the accuracy of determining its coordinates is limited only by the accuracy of the PUL positioning during installation. This accuracy also affects the distance between neighboring PULs installed along the AUV’s route. If the AUV is equipped with a high-precision autonomous navigation system, the PULs can be installed at the intervals of several hundred kilometers.

Correction Algorithm for the Navigation System of an Autonomous Unmanned Underwater Vehicle.

More accurate navigation systems are always required for autonomous unmanned underwater vehicles (AUUV)s under various circumstances. In this paper, a measuring complex of a heavy unmanned underwater vehicle (UUV) was investigated. The measuring complex consists of an inertial navigation platform system, a Doppler lag (DL) and an estimation algorithm. During a relatively long-term voyage of an UUV without surfacing and correction from buoys and stationary stations, errors of the measuring complex will increase over time. The increase in errors is caused by an increase in the deviation angles of the gyro platform relative to the accompanying trihedron of the selected coordinate system. To reduce these angles, correction is used in the structure of the inertial navigation system (INS) using a linear regulator. To increase accuracy, it is proposed to take into account the nonlinear features of INS errors; an adaptive nonlinear Kalman filter and a nonlinear controller were used in the correction scheme. Considering that, a modified nonlinear Kalman filter and a regulator in the measuring complex are proposed to improve the accuracy of the measurement information, and modification of the nonlinear Kalman filter was performed through a genetic algorithm, in which the regulator was developed by the State Dependent Coefficient (SDC) method of the formulated model. Modeling combined with a semi-natural experiment with a real inertial navigation system for the UUV demonstrated the efficiency and effectiveness of the proposed algorithms.

Применение подводных пассивных ориентиров для навигации автономных необитаемых подводных аппаратов

The article describes the design of passive underwater landmarks (PUL) and their use for navigation of autonomous unmanned underwater vehicles (AUV). The procedure of AUV observation using PUL is considered. It is shown that with proper maneuvering of the AUV during observation, the accuracy of determining its coordinates is limited only by the accuracy of the PUL positioning during installation. This accuracy also affects the distance between neighboring PULs installed along the AUV’s route. If the AUV is equipped with a high-precision autonomous navigation system, the PULs can be installed at the intervals of several hundred kilometers.