Unmanned Vessel Research Articles

Features of ensuring high-quality work of modern electrical power systems of unmanned vessels

Unmanned seagoing vessels are increasingly being used. In the paper the dump scow Rabochaya is considered as an example of an unmanned vessel. An extended marine control system, a video surveillance subsystem, a surveillance and search engine are additionally installed on the scow to carry out industrial tasks in unmanned mode. The correct operation of these systems and the whole vessel depends on the high-quality operation of the ship's electrical power system. The aim of the study is to identify abnormal modes of parallel operation of marine diesel generator sets and to develop methods and means for their elimination. The results of the experimental research and mathematical modeling have revealed the existence of power exchange oscillations when the ship generators operating in parallel. Power exchange oscillations can be detected with the help of generator current oscillations. It has been proposed to introduce a unit for eliminating power exchange oscillations (EPEO) into the automatic control system of ship electrical power systems for eliminating such oscillations. An algorithm for the operation of the EPEO unit has been developed, it controls the settings of the rotational speed regulators of diesel-generator sets. The proposed methods and tools reduce the amplitude of power exchange oscillations to an acceptable value, and therefore contribute to the high-quality operation of the ship's electrical power system and control systems in unmanned mode. The results obtained make it possible to ensure reliable and trouble-free operation of any autonomous electrical power system during the operation mode without maintenance personnel.

Investigation of the influence of measurement errors of navigation parameters on the quality of the control process an unmanned vessel

Much attention is paid to the problems of creating vessels with the implementation of remote or autonomous control. For vessels of this type, it qualitatively changes the requirements for ship systems for measuring, processing and transmitting navigation parameters. The importance of this problem is determined by the possible significant damage in the event of emergency situations when making management decisions based on erroneous information arising in the measurement channels. The article considers the errors arising in the measurement channels of navigation parameters on the example of a vessel with a wheeled propulsion and steering complex. The mathematical model of the vessel made it possible to investigate the influence of measurement errors of navigation parameters on the qualitative indicators of the ship management process when implementing various control algorithms. The results of studies of the influence of measurement errors of navigation parameters on the process of keeping the vessel on a given trajectory under external wind influences are presented.

Identification and Assessment of Groundwater and Soil Contamination from an Informal Landfill Site

Landfills are a potential source of local environmental pollution of all kinds, and the gradual destruction of seepage-proof structures in informal landfills will lead to contamination of the surrounding soil and groundwater environment. In this study, an informal landfill site in eastern China is used as the research object. Using technologies such as unmanned vessels and monitoring well imaging to delineate the amount and distribution of polluting media, sampling of the surrounding soil, sediment, groundwater, and surface water for testing, analysis, and evaluation is carried out visually and finely for heavy metals, petroleum hydrocarbons, volatile organic compounds (VOCs), semi-volatile organic compounds (SVOCs), and other indicators. The test results show that volatile phenols are the main contaminant species in the shallow groundwater, chlorinated hydrocarbons and benzene were prevalent in the deep groundwater, hexachlorobenzene and lead in the surface soil, and di(2-Ethylhexyl) phthalate in the deep soil (5.5 m), with a maximum exceedance of 1.24 times. Nearly 10 years have passed since the waste dumping incident at the landfill, but characteristic contaminants are still detected in the topsoil of the dumping area, which shows the long-term nature of the environmental impact of illegal dumping on the site. The study recommends that when developing a comprehensive remediation plan, the persistence of the environmental impact of the waste should be considered and appropriate remediation measures should be screened.

AUTOMATED APPROACH FOR SOLVING THE PROBLEM OF DETERMINING THE MARITIME AUTONOMOUS SURFACE SHIP OPERATION AREA

Every year the need for automation of the most diverse spheres of human activity is growing. In various areas of industry, services, logistics systems, there is a global trend towards autonomy of production and transport processes. In the field of maritime navigation, the most promising solution for automation is the use of marine autonomous surface ships. A maritime autonomous surface vessel is a vessel that is capable of functioning to varying degrees without interaction with a human operator. The complete or at least partial absence of the crew on the route of the vessel significantly reduces the costs of transport companies. However, any operation of an object is always preceded by a thorough analysis of the area of use; therefore, the main criteria for the classification of unmanned vessels, which allow determining the main design features of the vessel, are presented in the paper. A large number of criteria for classifying a surface object according to various conditions creates certain problems with the selection of the unmanned vessel operation area, therefore, a method that takes into account all the proposed classifications, allowing to determine the area of operation of marine autonomous surface ships using the example of the waters of Peter the Great Bay, is proposed in the paper. The application of an automated approach to solving the problem of classifying an object using a specially developed software product makes it possible to increase the visibility of the method results and the convenience of its use. A software tool that requires the input criteria of the designed MANS for successful operation is proposed. The result of the work is a map, where the proposed vessel operation area is marked in color, and there is also a function for viewing information about the local environment for the use of a manned object. The interface of the software tool, as well as the results of its work on the example of the water area of Peter the Great Bay, are presented.

Empathy from Afar? Towards Empathy for Future Maritime Designers and Remote Operators

Having empathy and being able to empathize refer to the ability to understand, view or feel the experiences and perspectives of others. In a work context, the ability of different actors to empathize with others can have positive effects in the design, organization and operations of complex systems. This article explores the value of empathy within safety-critical work systems and discusses the role of empathy as an entry point for user-centred approaches. We use the maritime domain to illustrate why developing empathic skills and knowledge has relevance and added-value for (1) maritime design and designers, and (2) future remote maritime operations and operators of unmanned vessels. We detail our emerging approaches and methods for developing empathy as a tool to enhance interdisciplinary understanding and knowledge sharing with the overall goal of improving Human Factors utilization in applied work contexts.

Data augmentation using image translation for underwater sonar image segmentation

In underwater environment, the study of object recognition is an important basis for implementing an underwater unmanned vessel. For this purpose, abundant experimental data to train deep learning model is required. However, it is very difficult to obtain these data because the underwater experiment itself is very limited in terms of preparation time and resources. In this study, the image transformation model, Pix2Pix is utilized to generate data similar to experimental one obtained by our ROV named SPARUS between the pool and reservoir. These generated data are applied to train the other deep learning model, FCN for a pixel segmentation of images. The original sonar image and its mask image have to be prepared for all training data to train the image segmentation model and it takes a lot of effort to do it what if all training data are supposed to be real sonar images. Fortunately, this burden can be released here, for the pairs of mask image and synthesized sonar image are already consisted in the image transformation step. The validity of the proposed procedures is verified from the performance of the image segmentation result. In this study, when only real sonar images are used for training, the mean accuracy is 0.7525 and the mean IoU is 0.7275. When the both synthetic and real data is used for training, the mean accuracy is 0.81 and the mean IoU is 0.7225. Comparing the results, the performance of mean accuracy increase to 6%, performance of the mean IoU is similar value.

무인 수상선의 수중 추진기 고장 진단 연구를 위한 고장 특성 인자 선정 및 실험

As interest in unmanned vessel research has increased, emphasis on autonomous navigation capability and the sustainability of normal operation has been highlighted. However, research on fault detection and diagnosis (FDD) for unmanned surface vehicles (USVs) is insufficient compared with research on land machinery or unmanned aerial vehicles. Among prior studies on USV FDD, intensive analysis or diagnostics for individual elements with high failure probability were barely conducted. This study focus on fault detecting features of a USV thruster, one of the most failure-prone elements other than internal causes or software malfunctions. A hypothesis for thruster fault detecting features was made based on general thruster-related equations; the features were tested on a stand-alone thruster test to assess the feature’s acceptability. However, a stand-alone thruster test lacks important effects such as structural vibratory influence of an actual USV, thruster load difference due to inflow velocity and wave-induced vibrations as the USV slides on the water’s surface. Hence, USV capable of acquiring fine quality real-time data for FDD practice was developed, and a surface driving test in a water basin was conducted to confirm the eligibility of the selected features.

Data-Driven system identification of 6-DoF ship motion in waves with neural networks

Critical evaluation of ship responses in the ocean is important for not only the design and engineering of future platforms but also the operation and safety of those that are currently deployed. Short-term temporal predictions of ship responses given the current wave environment and ship state would enable enhanced decision-making onboard and reduce the overall risk for both manned and unmanned vessels, especially as the marine industry trends towards more autonomy. However, state-of-the-art numerical hydrodynamic simulation tools are too computationally expensive to be employed for real-time ship motion forecasting. Thus, a methodology is needed to provide fast predictions with levels of accuracy closer to the higher-fidelity tools. A methodology is developed with long short-term memory (LSTM) neural networks to represent the motions of a free running David Taylor Model Basin (DTMB) 5415 destroyer operating at 20 knots in Sea State 7 stern-quartering long-crested irregular seas. Case studies are performed for both course-keeping and turning circle scenarios. An estimate of the vessel’s encounter frame is made with the trajectories observed in the training dataset. Wave elevation time histories are given by artificial wave probes that travel with the estimated encounter frame and serve as input into the neural network, while the output is the 6-DOF temporal ship motion response. Overall, the neural network is able to predict the temporal response of the ship due to unseen wave sequences accurately. The methodology, the dependence of model accuracy on wave probe and training data quantity and the estimated encounter frame are all detailed.

Safety challenges related to autonomous ships in mixed navigational environments

Digitalization and technological advancements have accelerated the development and emergence of autonomous and remotely controlled ships in the maritime transport sector. This type of vessels consists of highly intelligent and adaptive functionalities, equipped with a variety of external sensors and actuators to gain situation awareness, automated control and adaptive maneuvering for achieving more efficient and sustainable operations. There are, however, many safety and reliability assurance challenges in autonomous operational and navigation systems due to their complex, adaptive, and non-deterministic nature. The issue of a mixed navigational environment where conventionally manned, remotely controlled, and unmanned vessels are interacting at the same sea area can be considered as one of the major obstacles in adopting of autonomous ships. Vulnerabilities can increase due to the potential divergence of vessel state awareness between autonomous operational systems and humans in such situations. Little research to date has dealt with such safety issues that a mix of human-operated, remotely controlled, and autonomous vessels will bring. This study explores the potential safety challenges related to autonomous ship operations in a mixed navigational environment and discusses several possible ways to reduce the same issues related to the identified safety risks, while including a discussion for possible future practice and research interests in ship navigation.

Automatic Object Detection and Direction Prediction of Unmanned Vessels Based on Multiple Convolutional Neural Network Technology

This study aims to detect objects quickly and accurately and then start the necessary obstacle avoidance procedure when the uncrewed vessel is at sea. This study uses a multivariate convolutional neural network (CNN) to perform automatic object detection and direction prediction for uncrewed vessels. This study is divided into three parts for processing. The first part of this process uses camera calibration technology to correct the image. Discrete cosine transform (DCT) is then used to detect sea level. Finally, this study uses Kalman filtering and affine transformation to stabilize images taken by uncrewed vessels at sea. The second part of the processing system uses a CNN to detect sea objects automatically. The third part of the process uses the dual-lens camera installed on the vessel to detect the distance and direction of objects at sea. In the experiment, the detection rate can reach more than 91% in this study method. In the experiment on image stabilization, this study’s method can also effectively improve video instability. In the experiment involving the distance and direction of the object, the experimental results show that the distance and direction of the object obtained by this study method have a distance error value of less than 10%, and the prediction results have a good effect no matter whether the object is at a short or long distance. It is hoped that this paper’s method can be applied to the automatic obstacle avoidance of unmanned vessels.

UK PERSPECTIVE ON DEVELOPING REGULATIONS FOR AUTONOMOUS SHIPS

The scope of this paper is the development of regulation for remotely operated and autonomous ships. From a UK perspective, it discusses an enquiry into the United Nations Conventions for the Law of the Sea and the impact of autonomy. It explores the outcome of the International Maritime Organisation’s Regulatory Scoping Exercises on Maritime Autonomous Surface Ships and the next steps. The paper shares the regulatory developments at the different UK domestic legislative levels. The Future of Transport consultation is discussed, which includes potential new definitions for use in primary legislation. The Workboat Code is being updated to include emerging technologies, the paper touches on the methodology used to support the inclusion of remotely operated unmanned vessels as a new Annex. Finally, the current approach for managing the certification of remote operated and autonomous ships is discussed.

Determination of the Minimum Safe Distance between a USV and a Hydro-Engineering Structure in a Restricted Water Region Sounding

Bathymetric surveys performed using small, unmanned vessels are increasingly used in coastal areas and regions difficult to access by hydrographic motorboats. Their geometric dimensions, manoeuvring parameters, low labour intensity, and costs of survey execution have allowed the unmanned survey vessel (USV) to be a commonly recognised surveying platform. It is equipped with a navigation system for positioning, maintaining a course or survey line, determining spatial orientation, and measuring depths. The operation zone of the global navigation satellite system (GNSS) in coastal water regions enables geodetic positioning in land-based surveys and of moving objects, also including, for example, a sounding vessel. Under difficult observational conditions, the positioning is limited by the obscuration of the upper hemisphere, i.e., the visibility of satellites and the reflection from high field buildings. This poses a threat to a small vessel operating at a very short distance from a hydro-engineering structure. Based on a study performed in a marina, the article presents the determination of the minimum safe distance of the planned survey line to the quay in terms of the USV’s dimensions under good sounding conditions. These include low and constant velocity and good observational conditions for a GNSS receiver. The analysis was conducted on survey lines perpendicular to the quay, which was approached twice at distances of 1–5 m, with a 0.5 m interval. A 1 m distance between the end of the survey line and the quay has been determined for the safety of USV’s navigation and continuity of geospatial data collection during bathymetric surveys.

Pengembangan Teknologi Kapal Tanpa Awak Guna Mendukung Operasi dan Latihan Tni Angkatan Laut

Ship resistance is an important factor in ship design. Technological developments are carried out to reduce the magnitude of the ship's resistance. By reducing the drag of the ship, it can improve the performance of the ship with the same engine power as the previous design. In this study, we will redesign the hull of the Indonesian Navy's unmanned vessel in order to increase the performance of the ship's speed. The process of redesigning the hull of this unmanned ship uses the numerical method using Maxsurf software in analyzing hydrodynamic performance. The results of the drag analysis carried out with a redesign show a decrease in the value of the ship's resistance by 1143 KN and the required power of 9.98 HP. From the results that this study obtained compared to the initial design of 60%.

The Assessment of Unmanned Vessel Operation in Heavy Traffic Areas. Case Study of the North Sea Crossing by Unmanned Surface Vessel Sea-Kit

Abstract The continuous development of autonomous and unmanned technology is accelerating the adoption of unmanned vessels for various maritime operations. Despite the technological developments there is still a lack of clear regulatory and organizational frameworks for testing and exploiting the potential of unmanned surface vessels (USVs) in real-world maritime conditions. Such real-world testing becomes ever more complex when operating in multiple nations territorial waters. In May 2019 USV ‘Maxlimer’ crossed the North Sea from the United Kingdom to Belgium and back, carrying goods, to demonstrate the ability of unmanned surface vessels to interact with real marine traffic in an uncontrolled environment. The paper presents this mission in light of the current state of marine autonomy projects as well as the regulatory works conducted by various organizations worldwide.

Redesign of Unmanned Surface Vessel (USV) Hull to Increase the Performance and to Support Naval Operations

The Indonesian Navy's current unmanned vessel is the first unmanned ship made by the Indonesian Navy's Research and Development Service. This vessel is not optimal, it is necessary to redesign the hull using the model simulation method with the assistance of Maxsurf software. By using this maxsurf software, it will be easier to analyze hydrodynamic performance, one of which is the vessel's resistance. The redesign shows the results that there is a reduction in ship resistance. By redesigning, the hull of the Indonesian Navy's unmanned vessel by using the model simulation method with the assistance of the Maxsurf software in analyzing hydrodynamic performance, we get the resistance value at maximum speed. Meanwhile, the power required by the ship is at maximum speed so that the speed shows an increase in maximum ship speed, thereby fulfilling the operational requirements and producing good maneuverability. Therefore, it can be concluded that the ship after being redesigned can be better.

Bathymetric Measurements of the Vistula Smiala River Mouth with the Use of a Hydrographic Manned Vessel

The purpose of this paper was to determine the usability of unmanned hydrographic drones and photogrammetric techniques during the conduct of work, the results of which are potentially to serve as navigational materials in areas that, due to their characteristics, make it impossible to carry out research using crew vessels and direct shoreline determination. In order to prepare and carry out the measurement campaign with the greatest possible accuracy and safety, the authors of the article decided to determine the shoreline of the analyzed reservoir using photogrammetric methods. The use of satellite images allowed the border between land and water to be identified as precisely as possible, which had a direct impact on the accuracy of relating depth data to their location on Earth's globe. Use of unmanned vessels and orthophotos can find practical application when navigating vessels during maneuvers required high precision.

Bathymetric Measurements of a Retention Reservoir Using Integrated Hydrographic and Photogrammetric Techniques

The purpose of this paper was to determine the usability of unmanned hydrographic drones and photogrammetric techniques during the conduct of work, the results of which are potentially to serve as navigational materials in areas that, due to their characteristics, make it impossible to carry out research using crew vessels and direct shoreline determination. In order to prepare and carry out the measurement campaign with the greatest possible accuracy and safety, the authors of the article decided to determine the shoreline of the analyzed reservoir using photogrammetric methods. The use of satellite images allowed the border between land and water to be identified as precisely as possible, which had a direct impact on the accuracy of relating depth data to their location on Earth's globe. Use of unmanned vessels and orthophotos can find practical application when navigating vessels during maneuvers required high precision.

Navigation Multisensor Fault Diagnosis Approach for an Unmanned Surface Vessel Adopted Particle-Filter Method

Fault diagnosis (FD) of unmanned surface vessels (USVs) is an important and challenging task for ensuring system safety and reliability. In this study, a robust navigation strategy with FD based on an adaptive particle-filter (PF) method is designed for USVs, with consideration of multiple fault modes involving sensors and propellers. This paper utilizes the switching-mode hidden Markov model to describe an unmanned vessel with probable fault modes. Then, to implement FD and robust navigation, an adaptive PF including self-evaluation algorithm and adaptive weight-adjustment method is run on the fault model. The self-evaluation algorithm is used to extend the posterior distribution, whereas the adaptive weight-adjustment method is used to enrich the particle diversity and process the particles with small weight. The proposed method is tested via sea trial to demonstrate the effectiveness of the fault model under failure of various sensors and propeller conditions. The results indicate that the proposed approach can realize better FD and generate more accurate state estimation, even when faults occur.

Unmanned Navigation Development Prospects Based on Structural Analysis of Automated Vessel Control System

The reduction of vessel crew counts and increased automation have been observed in marine and river vessels for several decades. These processes are based, firstly, on the development of modern technology and, secondly, on the urge to reduce the so-called human factor, which is recognized today as one of the key causes of water transport emergencies. It is expected that unmanned navigation will help reduce operational costs, increase the carrying capacity of vessels, and reduce the impact of the human factor on the safety of navigation. This, in its turn, requires the development of a reliable and safe automated control system for unmanned vessels. This article aims to assess the development prospects of unmanned navigation based on the structural analysis of such systems. In the first part of this article, the authors review the classification of control systems depending on the degree of vessel autonomy and the generalized structure of the unmanned vessel control system. In the second part, the authors review the control system structure for a remote-control unmanned vessel and that for an autonomous unmanned vessel.

A method for unmanned vessel autonomous collision avoidance based on model predictive control

Aiming at the problem of autonomous collision avoidance of unmanned vessels in the case of multiple vessels encountering at sea, this paper proposes a method for collision avoidance of vessels in open water based on the Mathematical Model Group (MMG) vessel motion mathematical model. This method uses Model Predictive Control (MPC) model algorithm, and considers vessel maneuverability and the International Regulations for Preventing Collision at Sea, 1972 (COLREGs), and uses fuzzy mathematics to analyze the collision risk of vessels during navigation, and then constructs the evaluation function of the collision avoidance algorithm. The vessel's autonomous collision avoidance is realized. The simulation results show that the algorithm can solve the problem of autonomous vessel collision avoidance in the case of multi-vessel encounters in open water, which verifies the effectiveness of the algorithm.