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In order to promote and guide the development of autonomous underwater vehicles (AUVs) in China, this paper summarizes the research status of AUVs at home and abroad, and puts forward the development trends of serialization, grouping, systematization and large-scale development. Key AUV technologies such as overall multidisciplinary optimal design, structure and material design, power and propulsion, navigation and control, detection and communication are discussed. Finally, development opinions are put forward on how to make better use of AUVs to navigate the oceans and achieve the strategic goals of "ocean entry, ocean exploration and ocean utilization".
Large ships and submarines are the main equipment and mobile platforms supporting three-dimensional naval space operations. However, with the increasing damage power and strike accuracy of warheads, plus the diversity of destroying elements, their living environment is facing increasingly severe threats. It is thus necessary to work on the damage and protection of naval vessels subjected to blast loading. The blast-induced damage and protection of naval vessels is an interdisciplinary issue that involves the integration of explosion mechanics, fluid mechanics, structural mechanics, materials science and other disciplines in which many challenges are yet to be addressed. In view of some of the key issues involved, this paper systematically summarizes the research progress on blast load characteristics, damage mechanisms and protection technologies and equipment at home and abroad in recent years. The shortcomings of the current research are pointed out and the development trends of ship explosion damage and protection are predicted. This study can provide valuable references for future research on the efficient damage and protection of naval vessels.
Intelligent unmanned system combat is moving from concepts to actual combat applications. The military applications of intelligent unmanned systems are emphasized by focusing on the needs of the combat missions that they will undertake on future battlefields and summarizing the development statuses of land, air and maritime unmanned systems. Aiming at the key problems faced by intelligent unmanned systems and the practical difficulties that will be faced on the battlefield in the future, we analyze the key technologies required for intelligent unmanned systems, including autonomous perception and understanding in complex environments, behavioral decision-making and trajectory planning, autonomous navigation and positioning, multi-scenario autonomous skill learning and intelligent control, unmanned cluster cooperative control, natural human-computer interaction, etc. At the same time, aiming at the problems that will be encountered in the further development of intelligent unmanned systems on the battlefield in the future, we start with individual enhancement and cluster enhancement, and conduct a detailed analysis of the development trends of intelligent unmanned systems.
The toroidal propeller can effectively reduce tip vortex leakage due to its unique shape, which is beneficial for reducing hydrodynamic noise and improving propulsion efficiency. However, its complex shape also makes it challenging to model its geometric shape using conventional mathematical expression methods. Therefore, it is necessary to study the mathematical expression of the toroidal propeller.
First, the structural characteristics and advantages of the toroidal propeller are introduced in detail. Next, by referring to the mathematical expression of conventional propeller geometry, geometric parameters such as axis span, lateral angle, roll angle and vertical angle are introduced, and a detailed 3D coordinate formula for the toroidal propeller is derived by distributing the geometric parameters in the axis span direction, thereby establishing the mathematical expression method for toroidal propellers. Finally, taking the offset of a certain toroidal propeller as an example, the feasibility of the proposed mathematical expression method for toroidal propellers is verified.
The results show that the proposed method can smoothly establish the geometric shape of a toroidal propeller.
The proposed method can facilitate the rapid 3D modeling of toroidal propellers, laying a solid foundation for further research on the physical characteristics and scientific problems associated with toroidal propellers.
The swarm operation of unmanned marine vehicle (UMV) has been developed and evolved from concept to practical application. In view of the mission requirements of UMV swarms, this paper summarizes the development of the UMV swarm concepts of unmanned aerial vehicle (UAV), unmanned surface vehicle (USV) and unmanned underwater vehicle (UUV), and cross-domain swarm operations of UMV in naval warfare. It then analyzes the key technologies of UMV swarm cooperative engagement, including self-organizing communication, collaborative situational awareness, tasking, path planning, formation control and virtual testing. Finally, the main research ideas, representative algorithms and development trends of the related algorithms are summarized systematically. This study can provide valuable references for research on UMV swarm operation technology.
This paper reviews the research status of intelligent ship berthing technology at home and abroad in recent years. The hotspots and applications of berthing technology are summarized in the three aspects of berthing mode, mathematical model and control algorithm. The remaining problems in this field are analyzed in terms of autonomy, modeling accuracy, path planning, control algorithm, energy-saving effect and system test. Based on actual navigation needs, it is proposed that the next step is to make breakthroughs in core theories and key technical problems such as information fusion, online modeling, intelligent decision-making, optimization algorithms, green energy conservation and testing technology. The autonomy, robustness, rapidity and "toughness" of berthing technology should be improved so as to realize safe, green and efficient intelligent shipping.
This paper introduces the development background of intelligent ships and their remote control. Based on introducing current applications of the remote control unmanned ship and analyzing the demands and scenarios of remote control cargo ships, this paper proposes a remote control framework for cargo ships based on man-machine integration. The corresponding technical levels and related key technologies of different remote control patterns are expounded upon. A review of the importance and development status of key technologies for the remote control of cargo ships is then conducted with reference to major ship network control system achievements. Moreover, regarding the operation and maintenance characteristics of shipping, three considerations are proposed for utilizing perception technologies in ways that can be beneficial for realizing the remote control of cargo ships.
The future trends of marine operations will be intelligent, networked and swarmed marine vehicles. One of the main trends of future marine operations will be joint operations through the coordination of multiple unmanned surface vehicles (USVs). As an introduction to the mathematical model of USVs, this paper presents the key problems and fundamental challenges of motion controlling multiple USVs. Regarding different mission scenarios of USVs, the existing results will be classified into trajectory-guided, path-guided, and target-guided coordinated control. In conclusion, we discussed and summarized the future trends of the coordinated control of multiple USVs.
As a salient feature of smart ships, autonomous navigation has attracted the increasing attention of industrial and maritime enterprises. To grasp the status and development direction of autonomous navigation, this paper carries out an investigation and review of the relevant key technology by analyzing domestic and foreign state-of-the-art research into autonomous navigation technology over the past three years. Aiming at key technologies such as situational awareness of navigation , cognitive computing, collision avoidance decision-making, navigation control and cyber security, the technical connotations, research status and application situations are analyzed. Considering the current status and technical requirements of key technologies for intelligent navigation, this paper provides the future outlook of situational awareness, cognition, decision-making, control and security for the autonomous navigation of ships.
The artificial bee colony (ABC) algorithm has such characteristics as few control parameters, strong local optimization ability and fast convergence speed. However, when solving path optimization problems, it can easily fall into local optimal solutions. In order to solve the problem of pipeline routing in a ship pipeline system, an improved artificial bee colony (IABC) algorithm is proposed.
Based on the traditional artificial bee colony algorithm, the crossover operation of genetic operators is introduced into the update mechanism of following bees, and an adaptive strategy is adopted for the crossover probability of the crossover operator. The crossover operation on the population is used to find new solutions in the global range. The way scout bees search for new paths is improved from updating the points that the path passes to updating the "road sections" in the path. This paper proposes an artificial bee colony co-evolution algorithm for solving the optimization of branch pipeline paths.
Compared with the standard artificial bee colony algorithm, the improved algorithm can improve the path layout effect by 32.3%–37.4% and the convergence speed by 17.7%–29.9%.
The improved artificial bee colony algorithm proposed herein has higher solution quality, faster convergence speed and better stability than the traditional artificial bee colony algorithm for a single pipe or branch pipe.
The shock resistance capability of ship power equipment is an important guarantee for the safe and stable operation of ships, and a reasonable evaluation method can be more convenient for obtaining the prediction results of power equipment shock resistance. First, the impact processes are divided into the low/high speed collision impact process and non-contact explosion impact process, and the non-integrated and integrated shock resistance methods of ship equipment are described in terms of the master-slave system. The research progress is then summarized and key research technologies in the field of shock resistance for ship power equipment are put forward. The non-integrated methods of ship equipment are divided into three categories, namely the equivalent static method, dynamic design analysis method and time-domain analysis method, and combined with the characteristics of integrated methods. It is concluded that the equivalent static method is only applicable to structurally simple power equipment with low frequency effects; the dynamic design analysis method neglects the effects of adjacent equipment, vibration isolation system and hull structure on impact input loads; and the time-domain analysis method is only applicable to specific scenarios or shock signal inputs such as explosive shocks. The integration of ship equipment takes into account the multi-degree-of-freedom system formed by the hull structure–base–vibration isolation system–equipment, and the calculation results are closer to the actual working condition data, but a large amount of resources is consumed in the modelling and calculation process. Finally, the author forecasts and summarizes important development directions for ship power equipment shock resistance, including the accurate selection of evaluation methods, reasonable improvement of shock resistance test rigs, extraction and analysis of impact response signals, analysis of the multi-field coupling effects of power equipment, simplification study of the physical models of power equipment, research on the equivalent substitution of internal flow media, and the combination of data mining and deep learning methods.
This paper aims to investigate the complex influence of environmental disturbances on unmanned surface vehicles (USVs) under real ocean conditions, and control USVs to overcome disturbances and realize path following.
An improved active disturbance rejection controller (ADRC) based on the model-free adaptive control (MFAC) law (ADRC−MFAC) is proposed to establish the non-linear relationship between the input data (rudder angle) and output data (heading angle, angular velocity), and identify the unknown disturbances of the system. In this way, stable heading control can be achieved. Combined with the adaptive line-of-sight (LOS) guidance law, it achieves accurate tracking control through dynamic heading control.
The simulation results show that the controller can control USVs to approach the preset path quickly and achieve a desirable tracking control effect under complex disturbances.
The research results do not depend on the specific model of USV and can provide valuable references for ship tracking control.
In recent years, the route optimization of intelligent ships has attracted increasing attention in academic and industrial circles. Aiming at the problem of intelligent ship route optimization, this paper expounds upon the characteristics of various route design methods and route optimization algorithms. Combined with the latest research results over the past five years, the development status of intelligent ship route optimization technology at home and abroad is analyzed, and route optimization design methods are summarized into three kinds, namely those based on meteorological data, fuel consumption models and route/waypoint databases, and the technical connotations and applications are analyzed. The characteristics and shortcomings of the improved isochrony method, dynamic programming method, graph search algorithm, intelligent algorithm and artificial intelligence/machine learning algorithm are analyzed in depth, and the main problems existing in the application of various algorithms to intelligent ship route optimization are summarized. Finally, the development trend of intelligent ship route optimization is briefly predicted to provide ideas for future research in this field.
The extra-large unmanned underwater vehicle (XLUUV), as an underwater unmanned combat platform capable of carrying a large number of mission payloads, holds significant research value. This paper aims to provide a comprehensive understanding of the current research status of XLUUVs abroad and to offer insights for their development and application in China. It systematically analyzes the development status and future trends of the five main types of XLUUVs: ordinary, submersible, submarine-like, packable, and container types. The paper explores key technologies such as modularization, multi-domain communication, underwater detection, positioning and navigation, autonomous control, and energy power. It also studies their combat applications in reconnaissance and surveillance, underwater mine laying, underwater attack and defense, and underwater delivery. Research indicates that XLUUVs are trending towards ethnic, remote, fully deepened, and intelligent development. They are capable of multi-dimensional detection, sealing off important maritime routes, conducting asymmetric strikes, and covert delivery, which will be crucial in future underwater confrontations.
Underwater vehicles (UVs) not only play an important role in civilian fields, but have also been widely used in military fields and have broad application prospects. However, they are susceptible to the influence of the ocean current environment during underwater navigation, which makes their hydrodynamic parameters uncertain and in turn leads to difficulties in motion attitude control, navigation deviation and increased navigation cost, and even affects the completion of underwater combat tasks and the occurrence of collision accidents, thereby endangering navigation safety. Building on a summary of the current status of hydrodynamic research regarding different UVs in ocean currents and UV control methods for dealing with ocean current interference, we propose several perspectives on the development direction of UVs under ocean currents intended to provide references for the study of the influence mechanisms of complex ocean currents on the hydrodynamic parameters of UVs and the design of controllers.
As an important component of future naval campaigns, the unmanned surface vehicle (USV) swarm is an important direction for the development of unmanned maritime assets in various counties. This paper first summarizes the current strategic planning and application status of USV swarms in foreign countries, then dissects the research progress of USV swarms in such aspects as cluster communication, battlefield situation awareness and cooperative task assignment. At the same time, the typical combat operation modes and main benefits of USV swarms are analyzed and assessed. Finally, current challenges that need to be tackled in USV swarm combat operation are analyzed, and countermeasures that can be taken against the technological development of USV swarm combat operation are predicted.
This paper starts with the importance and basic physical phenomena of underwater explosion, explaining the background and significance of ship damage and protection research under underwater explosion loads, research progress and status, as well as key challenges. To address these challenges, the paper elaborates on popular underwater explosion theories, models and methods. In terms of theoretical and computational research, a unified theory of bubble dynamics is presented, as well as a transient strong non-linear gas-liquid-solid fully coupled model and numerical method for underwater explosion, which have been used to develop a fundamental industrial software FSLAB capable of solving practical problems in fluid-structure interaction. In terms of experimental research, underwater explosion surrogate experimental methods and model testing methods are elaborated. Based on this, theoretical analysis, computational and experimental results in the field of ship damage and protection under underwater explosion loads are presented and discussed, aiming to provide references for underwater explosion-related research.
In order to improve the economy and safety of ship navigation path in actual sea environment, this paper proposes a ship global path planning method with an improved Deep Q-Network (DQN) algorithm.
First, a prioritized experience replay （PER） mechanism is introduced to the DQN to give higher weights to important samples and improve learning efficiency. Next, its network structure is improved through a duel network and noise network, enabling it to evaluate the values of specific states and actions more accurately and generalization capabilities.
An experiment is carried out in the marine environment near Manila, and the results show that compared with the A* algorithm and DQN algorithm, the improved algorithm reduces the path length by 1.9% and 1.0% respectively, and the number of turning points by 62.5% and 25% respectively.
It is verified that the improved DQN algorithm can plan the effective path more economically and rationally.
In order to improve the accuracy and efficiency of ship trajectory anomaly detection, and solve the problems of traditional anomaly detection methods such as limited feature characterization ability, insufficient compensation accuracy, gradient disappearance and overfitting, an unsupervised ship trajectory anomaly detection method based on the Transformer_LSTM codec module is proposed.
Based on the encoder decoder architecture, the Transformer_LSTM module replaces the traditional neural network to achieve track feature extraction and track reconstruction. By embedding the transformer into the recursive mechanism of LSTM, combined with the cyclic unit and attention mechanism, self-attention and cross-attention can be used to calculate the state vector of the cyclic unit and effectively construct the long sequence model. By minimizing the difference between the reconstructed output and original input, the model learns the characteristics and motion mode of the general trajectory, and trajectories with a reconstruction error greater than the abnormal threshold are judged as abnormal trajectories.
AIS data collected in January 2021 is adopted. The results show that the accuracy, precesion and recall rate of the model are significantly improved compared with those of LOF, DBSCAN, VAE, LSTM, etc. The F1 score is improved by 8.11% compared with that of the VAE_LSTM model.
The anomaly detection performance of the proposed method is significantly superior to the traditional algorithm in various indexes, and the model can be effectively and reliably applied to the trajectory anomaly detection of ships at sea.
Autonomous unmanned surface vessels (USVs) are drawing increasing attention. The intelligent technology of the engine room is the basis of USVs that feature long voyage course and fully autonomous operation, and it ensures that the goals of the USV can be achieved. First, this paper reviews the development status at home and abroad. The scope of the intelligent objectives of the engine room is then proposed, and five ability target images of engine room intelligent technology are identified. Next, the Application-Control-Onsite technology application solution, components and path are presented. Finally, several development key points of engine room intelligent technology are discussed. This work can provide valuable references for the general technological R&D of USVs.
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