Automatic obstacle avoidance and intelligent navigation control system for ship

Abstract

The invention belongs to the field of ship navigation, and provides a ship automatic obstacle avoidance and intelligent navigation control system which comprises an environment sensing module used for collecting environment information around a ship, a data processing module used for analyzing data collected by the environment sensing module, an obstacle detection module used for identifying potential navigation obstacles and a route planning module. The navigation path planning module is used for planning a safe navigation path based on obstacle information, the navigation execution module is used for controlling a ship to travel according to a planned route, and the monitoring and feedback module is used for monitoring the state of the ship in real time and providing feedback; by integrating an advanced environment sensing module and an obstacle detection algorithm, the surrounding environment of the ship can be monitored in real time, and potential navigation obstacles can be accurately identified. And by combining an intelligent route planning and automatic navigation execution module, the system can automatically avoid risks, and the collision and accident risks caused by human factors or environmental changes are remarkably reduced.

Description

Technical Field

[0001] The invention belongs to the field of ship navigation, in particular to an automatic obstacle avoidance and intelligent navigation control system for ships. Background Art

[0002] Maritime navigation technology has been at the core of maritime transportation and exploration since ancient times. From ancient astronomical navigation to modern electronic navigation systems, ship navigation technology has undergone great development. However, with the increasing number of maritime activities, traditional navigation methods have been unable to meet the high requirements of safety, efficiency and environmental friendliness in the modern maritime field. At present, most ships rely on manual operation and basic automatic navigation systems to avoid collisions and cope with complex navigation conditions. These systems usually include radar, sonar and global positioning system (GPS), which provide crews with basic information about the surrounding environment. However, these systems often lack sufficient intelligence and automation levels and cannot provide effective decision support in high-risk or low-visibility situations.

[0003] The main problems with existing technologies include: high manual dependence: in complex or emergency situations, the crew's judgment and response may not be quick or accurate enough, increasing the risk of collisions and accidents; limited navigation system functions: many existing navigation systems are unable to process and analyze large amounts of environmental data in real time, and have difficulty coping with rapidly changing marine environments.

[0004] To this end, those skilled in the art have proposed an automatic obstacle avoidance and intelligent navigation control system for ships to solve the problems raised by the background technology. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a ship automatic obstacle avoidance and intelligent navigation control system to solve the problems of strong manual dependence and limited navigation system functions in the prior art.

[0006] A ship automatic obstacle avoidance and intelligent navigation control system, including an environment perception module for collecting environmental information around the ship;

[0007] A data processing module, used to analyze the data collected by the environment perception module;

[0008] Obstacle detection module, used to identify potential navigation obstacles;

[0009] Route planning module, used to plan safe navigation paths based on obstacle information;

[0010] The navigation execution module is used to control the ship to sail according to the planned route;

[0011] Monitoring and feedback module, used to monitor the ship status in real time and provide feedback.

[0012] Preferably, the environment perception module also includes the following submodules and functions:

[0013] Ocean current meters, which measure the speed and direction of the current in the surrounding waters, providing data to assist in route planning and obstacle avoidance decisions;

[0014] Meteorological sensors are used to collect meteorological data such as wind speed, wind direction, temperature and humidity to adapt to environmental changes;

[0015] The Electronic Horizon system, which combines satellite data with terrain information, provides the vessel's precise position relative to land and obstacles.

[0016] Preferably, the data processing module uses the following algorithm formula to process the collected data to extract useful information and perform data fusion:

[0017] Data_Processed=f(Data_Raw, Environmental_Factors, Historical_Data)=Data_Filter(Data_Raw)Data_Enhance(Environmental_Factors)+Data_Analyze(Historical_Data),

[0018] Among them, f is a comprehensive function, Data_Filter represents the filter function, which is used to remove noise. The formula is,

[0019] Data_Enhance represents a data enhancement function, which is used to highlight important features. The formula is Data_Enhance(χ)=αχ+β, where α and β are coefficients adjusted according to environmental factors.

[0020] Preferably, the obstacle detection module uses the following algorithm formula to identify obstacles, combining machine learning and image processing technology:

[0021] Obstacle_Detected=g(Data_Processed)=max(Object_Scores)-Threshold_Value,

[0022] Among them, g is the obstacle detection function, Object_Scores is the obstacle score set output by the object recognition algorithm, and Threshold_Value is the threshold for obstacle detection.

[0023] Preferably, the route planning module uses the following algorithm formula to plan the route, taking into account obstacle locations, ship performance and environmental factors:

[0024] Where h is the route planning function, Obstacle_Detected: This is the output of the obstacle detection module, which contains the location, size and possible type of obstacles, Destination: This is the destination of the ship, which can be a longitude and latitude coordinate or a vector relative to the current position, Vessel_Performance: This is the performance parameter of the ship, including maximum speed, turning radius, acceleration limit, Path_Length is the path length, and Path_Risk is a risk assessment function based on obstacle detection.

[0025] Preferably, the navigation execution module can automatically adjust the heading and speed of the ship according to the output of the route planning module and the real-time status of the ship, using the following control algorithm:

[0026] Navigation_Commands=k(Route,Vessel_State)=

[0027] PID_Controller(Desired_Course,Current_Course)×

[0028] Speed_Optimizer(Desired_Speed,Current_Speed)

[0029] Among them, k is the navigation command generation function, PID_Controller is the proportional-integral-derivative controller, the formula is, Where K P , K i , K d are controller parameters and e(t) is the deviation between the desired heading and the current heading.

[0030] Preferably, the monitoring and feedback module can monitor the position, speed, attitude and surrounding environment of the ship in real time, and automatically adjust the route according to the monitoring results and preset safety standards, using the following feedback control algorithm

[0031] Feedback_Adjustment=l(Monitored_Data, Safety_Standards)=Deviation_Analysis(Monitored_Data)×Safety_Evaluation(Safety_Standards),

[0032] Where l is the feedback adjustment function,

[0033] Deviation_AnalysisDeviation_Analysis is a deviation analysis function, which is used to calculate the deviation between the actual route and the planned route. Safety_EvaluationSafety_Evaluation is a safety evaluation function, which is used to determine whether the current route meets the safety standards.

[0034] Preferably, the system also includes a user interface, an interactive map display that allows the user to view the vessel's current position, planned route and surrounding obstacles, a destination setting function, where the user can set the destination by clicking on the map or entering coordinates, a navigation parameter adjustment tool, where the user can manually adjust the vessel's speed, heading and other navigation characteristics, and a real-time status monitoring dashboard that displays the vessel's speed, heading, engine status and other key performance indicators.

[0035] Preferably, the system can exchange data with other ships or coastal facilities through a wireless communication module, using the following communication protocol:

[0036] Data_Exchange=m(Local_Data,Remote_Request)=Data_Compression(Local_Data)×Encryption()+Data_Decoding(Remote_Request) Where m is the data exchange function,

[0037] Data_CompressionData_Compression is a data compression function used to reduce the amount of data transmitted, and EncryptionEncryption is an encryption function to ensure data security;

[0038] Data_DecodingData_Decoding is a decoding function used to parse the received data.

[0039] Preferably, the system further comprises an emergency obstacle avoidance module, which can automatically take obstacle avoidance measures when an emergency situation is detected, such as emergency stopping, emergency turning or releasing life-saving equipment.

[0040] Through the above technical solution,

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] 1. The present invention integrates advanced environmental perception modules and obstacle detection algorithms to monitor the ship's surroundings in real time and accurately identify potential navigation obstacles. Combined with intelligent route planning and automatic navigation execution modules, the system can automatically avoid risks and significantly reduce the risk of collisions and accidents caused by human factors or environmental changes.

[0043] 2. This system uses an optimization algorithm to dynamically plan the route, taking into account the location of obstacles, ship performance and environmental conditions, and calculates the shortest and safest path. Compared with traditional manual planning, the present invention can respond to environmental changes more quickly and accurately, reduce unnecessary voyage and time delays, thereby improving navigation efficiency and reducing operating costs.

[0044] 3. The intelligent navigation control system of the present invention has a high degree of autonomy and can operate stably in various complex and changing marine environments. The system can automatically adapt to changes in sea conditions, weather and other external conditions, and adjust navigation strategies in a timely manner to ensure the safety of ships in extreme or unknown situations. In addition, the system's user interface provides interaction between operators and the automated system, making it easy to perform manual intervention and parameter adjustments when necessary. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic diagram of the overall structure of the present invention;

[0046] Figure 2 It is a flow chart of the system in the present invention; DETAILED DESCRIPTION

[0047] The following is a further detailed description of the embodiments of the present invention in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0048] Embodiment 1: As shown in the attached Figure 1 To Attachment Figure 2 As shown: The present invention provides a ship automatic obstacle avoidance and intelligent navigation control system, including an environment perception module for collecting environmental information around the ship, the module further includes a satellite navigation system, such as a global positioning system (GPS) or a Beidou navigation system, to provide accurate global positioning information, and an integrated ship status monitoring sensor for real-time collection of ship speed, heading, draft, tilt angle and other status information;

[0049] A data processing module for analyzing the data collected by the environmental perception module. The module further includes a data fusion algorithm for integrating data sources from different sensors to provide more accurate and comprehensive environmental perception, and introduces a data security mechanism to ensure data integrity and confidentiality during processing;

[0050] An obstacle detection module for identifying potential navigation obstacles, which further includes a machine learning classifier for improving the accuracy of obstacle identification and reducing the false alarm rate, adding an obstacle behavior prediction function to predict the future position and movement trajectory of obstacles;

[0051] A route planning module is used to plan a safe navigation path based on obstacle information. The module further includes a multi-path planning algorithm to adapt to different navigation conditions and priority settings, introduce a route planning strategy that minimizes environmental impact and reduces negative impacts on marine ecology;

[0052] The navigation execution module is used to control the ship to sail along the planned route. The module further includes an automatic track control system to ensure that the ship sails stably along the planned route and adds a ship performance adaptive adjustment function to dynamically adjust the navigation parameters according to the actual performance of the ship.

[0053] The monitoring and feedback module is used to monitor the ship status in real time and provide feedback. The module further includes a system health monitoring system to monitor the status of key components of the ship in real time, predict potential failures, introduce an intelligent diagnosis system, automatically diagnose detected abnormal conditions and propose solutions.

[0054] Preferably, the environmental perception module also includes the following sub-modules and functions: an ocean current meter for measuring the velocity and direction of the surrounding waters to provide data to assist route planning and obstacle avoidance decisions; a meteorological sensor for collecting meteorological data such as wind speed, wind direction, temperature and humidity to adapt to environmental changes; and an electronic horizon system that combines satellite data and terrain information to provide the precise position of the ship relative to land and obstacles.

[0055] Embodiment 2: As shown in the attached Figure 1 To Attachment Figure 2 As shown: This embodiment is basically the same as the previous embodiment, except that the data processing module uses the following algorithm formula to process the collected data to extract useful information and perform data fusion:

[0056] Data_Processed=f(Data_Raw, Environmental_Factors, Historical_Data)=Data_Filter(Data_Raw)Data_Enhance(Environmental_Factors)+Data_Analyze(Historical_Data),

[0057] Among them, f is a comprehensive function, Data_Filter represents the filter function, which is used to remove noise. The formula is,

[0058] Data_Enhance represents a data enhancement function, which is used to highlight important features. The formula is Data_Enhance(χ)=αχ+β, where α and β are coefficients adjusted according to environmental factors.

[0059] Furthermore, the data processing module may also adopt advanced signal processing algorithms, such as wavelet transform and Fourier transform, to enhance the time-frequency analysis capability of the data, and perform feature extraction and pattern recognition through deep learning networks, such as convolutional neural networks (CNN), to improve the accuracy and efficiency of data processing.

[0060] Preferably, the obstacle detection module uses the following algorithm formula to identify obstacles, combining machine learning and image processing technology:

[0061] Obstacle_Detected=g(Data_Processed)=max(Object_Scores)-Threshold_Value, where g is the obstacle detection function, Object_Scores is the obstacle score set output by the object recognition algorithm, and Threshold_Value is the threshold for obstacle detection.

[0062] Furthermore, the route planning module uses the following algorithm formula to plan the route, taking into account obstacle locations, ship performance and environmental factors:

[0063] Among them, h is the route planning function, Obstacle_Detected: This is the output of the obstacle detection module, which contains the location, size and possible type of obstacles, Destination: This is the destination of the ship, which can be a longitude and latitude coordinate or a vector relative to the current position, Vessel_Performance: This is the performance parameter of the ship, including maximum speed, turning radius, acceleration limit, Path_Length is the path length, Path_Risk is the risk assessment function based on obstacle detection, path optimization: argmin Path It means finding the path that minimizes a function. In this context, the function is Path_Length+Path_RiskPath_Length+Path_Risk.

[0064] Path Length: This is the straight-line distance or actual navigation distance from the current location to the destination, depending on the accuracy and requirements of the route planning.

[0065] Path_Risk: This is a risk function based on obstacle information assessment, which may take into account the location, size, type of obstacle, and the relative speed and direction between the ship and the obstacle. Risk assessment may use different algorithms or heuristics, for example, Where n is the number of obstacles, Risk_Factor iis the contribution of each obstacle to the navigation risk, which may be weighted according to the characteristics of the obstacle and the navigation status of the ship. The whole optimization goal is to minimize the sum of path length and path risk, which means that the algorithm will find a route that is both short and safe. This optimization problem can be implemented by a variety of algorithms, including but not limited to genetic algorithms, simulated annealing, ant colony optimization, graph search algorithms (such as A* or Dijkstra algorithm), etc.

[0066] Preferably, the obstacle detection module further includes a machine learning-based classification system capable of distinguishing different types of obstacles, such as ships, buoys, icebergs and other marine life, as well as assessing the size, shape and movement speed of obstacles.

[0067] Embodiment 3: As shown in the attached Figure 1 To Attachment Figure 2 As shown: Based on the first embodiment, the navigation execution module can automatically adjust the heading and speed of the ship according to the output of the route planning module and the real-time status of the ship, using the following control algorithm:

[0068] Navigation_Commands=k(Route,Vessel_State)=

[0069] PID_Controller(Desired_Course,Current_Course)×

[0070] Speed_Optimizer(Desired_Speed,Current_Speed)

[0071] Among them, k is the navigation command generation function, PID_Controller is the proportional-integral-derivative controller, the formula is, Where K P , K i , K d are controller parameters and e(t) is the deviation between the desired heading and the current heading.

[0072] Specifically, the navigation execution module also includes an adaptive control system that can dynamically adjust control parameters based on the ship's real-time performance feedback and external environmental disturbances to ensure that the ship sails stably along the scheduled route.

[0073] Furthermore, the monitoring and feedback module can monitor the position, speed, attitude and surrounding environment of the ship in real time, and automatically adjust the route according to the monitoring results and preset safety standards, using the following feedback control algorithm

[0074] Feedback_Adjustment=l(Monitored_Data, Safety_Standards)=Deviation_Analysis(Monitored_Data)×Safety_Evaluation(Safety_Standards),

[0075] Where l is the feedback adjustment function,

[0076] Deviation_AnalysisDeviation_Analysis is a deviation analysis function, which is used to calculate the deviation between the actual route and the planned route. Safety_EvaluationSafety_Evaluation is a safety evaluation function, which is used to determine whether the current route meets the safety standards.

[0077] Preferably, the monitoring and feedback module also includes a predictive maintenance system, which analyzes the operating data of key components of the ship to predict potential failures and performance degradation, so as to perform maintenance and adjustments in advance.

[0078] Furthermore, the route planning module can adopt AI-based optimization algorithms, such as genetic algorithms or particle swarm optimization (PSO), to search for the optimal route under multiple constraints and take into account the dynamic performance of the ship and real-time environmental changes.

[0079] Preferably, the system further comprises a user interface, an interactive map display, allowing the user to view the current position of the vessel, the planned route and surrounding obstacles, a destination setting function, where the user can set the destination by clicking on the map or entering coordinates, a navigation parameter adjustment tool, where the user can manually adjust the speed, heading and other navigation characteristics of the vessel, a real-time status monitoring dashboard, displaying the speed, heading, engine status and other key performance indicators of the vessel, and interactive logic between user instructions and system feedback, using the following algorithm to process user input:

[0080] System_Response=φ(User_Input,Vessel_State,Route_Status)

[0081] Where φ is the system response function, which calculates the action that the system should take based on user input, ship status and route status.

[0082] Furthermore, the user interface also includes a multi-mode interaction system that supports multiple interaction methods such as touch screen, voice command and gesture control, providing intuitive navigation information display and user-friendly operation experience.

[0083] Specifically, the system can exchange data with other ships or coastal facilities through a wireless communication module, using the following communication protocol:

[0084] Data_Exchange=m(Local_Data,Remote_Request)=Data_Compression(Local_Data)×Encryption()+Data_Decoding(Remote_Request) Where m is the data exchange function,

[0085] Data_CompressionData_Compression is a data compression function used to reduce the amount of data transmitted, and EncryptionEncryption is an encryption function to ensure data security;

[0086] Data_DecodingData_Decoding is a decoding function used to parse the received data.

[0087] Preferably, the wireless communication module further adopts an encrypted communication protocol, such as the Advanced Encryption Standard (AES), to ensure the security and privacy of data exchange, and optimizes communication quality through automatic frequency selection and signal strength adjustment.

[0088] Furthermore, the system also includes an emergency obstacle avoidance module, which can automatically take obstacle avoidance measures when an emergency situation is detected, such as emergency stopping, emergency turning or releasing life-saving equipment. Specifically, it includes a real-time threat assessment system that continuously assesses the potential threats posed by the surrounding environment to the ship, a dynamic obstacle avoidance strategy generator that generates an obstacle avoidance strategy based on the assessment results and the status of the ship, and an automatic control system that executes the obstacle avoidance strategy, including emergency stopping, emergency turning or releasing life-saving equipment.

[0089] The emergency obstacle avoidance algorithm uses the following formula to calculate the obstacle avoidance action:

[0090] Evasive_Action=ψ(Threat_Level, Vessel_Speed, Maneuverability_Index)

[0091] Among them, ψ is the obstacle avoidance action calculation function, Threat_LevelThreat_Level is the threat level, Vessel_SpeedVessel_Speed ​​is the ship speed, and Maneuverability_Index is the ship's maneuverability index.

[0092] Furthermore, the emergency obstacle avoidance module also includes a mechanism for automatically releasing life-saving equipment, such as an automatically inflated life raft or lifeboat, and a system for automatic alarm and communication with the Coast Guard and nearby ships to quickly respond to emergencies.

[0093] As can be seen from the above, when in use, the system is started, the environmental perception module begins to collect environmental data around the ship, the raw data is received through the data processing module, and filtering, enhancement and fusion processing are performed, the obstacle detection module analyzes the processed data, identifies obstacles and assesses risks, the route planning module plans the optimal route according to obstacle information, ship performance and environmental conditions, the navigation execution module receives the route information, and automatically adjusts the ship's heading and speed to perform navigation tasks, the monitoring and feedback module monitors the ship's status and environmental changes in real time, and adjusts the route or issues warnings when necessary, and the user interface provides an interactive interface between the operator and the system, allowing manual input and adjustment of navigation parameters.

[0094] The embodiments of the present invention are provided for the purpose of illustration and description. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present invention. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present invention.

[0095] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the utility model. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

Claims

1. A ship automatic obstacle avoidance and intelligent navigation control system, characterized in that: include: Environmental perception module, used to collect environmental information around the ship; A data processing module, used to analyze the data collected by the environment perception module; Obstacle detection module, used to identify potential navigation obstacles; Route planning module, used to plan safe navigation paths based on obstacle information; The navigation execution module is used to control the ship to sail according to the planned route; Monitoring and feedback module, used to monitor the ship status in real time and provide feedback.

2. The automatic obstacle avoidance and intelligent navigation control system for ships as claimed in claim 1, characterized in that: The environment perception module also includes the following submodules and functions: Ocean current meters, which measure the speed and direction of the current in the surrounding waters, providing data to assist in route planning and obstacle avoidance decisions; Meteorological sensors are used to collect meteorological data such as wind speed, wind direction, temperature and humidity to adapt to environmental changes; The Electronic Horizon system, which combines satellite data with terrain information, provides the vessel's precise position relative to land and obstacles.

3. The automatic obstacle avoidance and intelligent navigation control system for ships as claimed in claim 1, characterized in that: The data processing module uses the following algorithm formula to process the collected data to extract useful information and perform data fusion: Data_Processed=f(Data_Raw, Environmental_Factors, Historical_Data)=Data_Filter(Data_Raw)Data_Enhance(Environmenta l_Factors)+Data_Analyze(Historical_Data), Among them, f is a comprehensive function, Data_Filter represents the filter function, which is used to remove noise. The formula is: Data_Enhance represents a data enhancement function, which is used to highlight important features. The formula is Data_Enhance(χ)=αχ+β, where α and β are coefficients adjusted according to environmental factors.

4. The automatic obstacle avoidance and intelligent navigation control system for ships as claimed in claim 1, characterized in that: The obstacle detection module uses the following algorithm formula to identify obstacles, combining machine learning and image processing technology: Obstacle_Detected=g(Data_Processed)=max(Object_Scores)-Threshold_Value, Among them, g is the obstacle detection function, Object_Scores is the obstacle score set output by the object recognition algorithm, and Threshold_Value is the threshold for obstacle detection.

5. The automatic obstacle avoidance and intelligent navigation control system for ships as claimed in claim 1, characterized in that: The route planning module uses the following algorithm formula to plan the route, taking into account obstacle locations, ship performance and environmental factors: Where h is the route planning function, Obstacle_Detected: This is the output of the obstacle detection module, which contains the location, size and possible type of obstacles, Destination: This is the destination of the ship, which can be a longitude and latitude coordinate or a vector relative to the current position, Vessel_Performance: This is the performance parameter of the ship, including maximum speed, turning radius, acceleration limit, Path_Length is the path length, and Path_Risk is a risk assessment function based on obstacle detection.

6. The automatic obstacle avoidance and intelligent navigation control system for ships as claimed in claim 1, characterized in that: The navigation execution module can automatically adjust the ship's heading and speed according to the output of the route planning module and the real-time status of the ship, using the following control algorithm: Navigation_Commands=k(Route,Vessel_State)= PID_Controller(Desired_Course,Current_Course)× Speed_Optimizer(Desired_Speed,Current_Speed) Among them, k is the navigation command generation function, PID_Controller is the proportional-integral-derivative controller, the formula is, Where K P , K i , K d are controller parameters and e(t) is the deviation between the desired heading and the current heading.

7. The automatic obstacle avoidance and intelligent navigation control system for ships as claimed in claim 1, characterized in that: The monitoring and feedback module can monitor the position, speed, attitude and surrounding environment of the ship in real time, and automatically adjust the route according to the monitoring results and preset safety standards, using the following feedback control algorithm Feedback_Adjustment=l(Monitored_Data, Safety_Standards)=Deviation_Analysis(Monitored_Data)×Safety_Evaluation(Safety_Standards), Where l is the feedback adjustment function, Deviation_AnalysisDeviation_Analysis is a deviation analysis function, which is used to calculate the deviation between the actual route and the planned route. Safety_EvaluationSafety_Evaluation is a safety evaluation function, which is used to determine whether the current route meets the safety standards.

8. The ship automatic obstacle avoidance and intelligent navigation control system as claimed in claim 1, characterized in that: The system also includes a user interface, an interactive map display that allows the user to view the vessel's current position, planned route and surrounding obstacles, a destination setting function, where the user can set the destination by clicking on the map or entering coordinates, a navigation parameter adjustment tool, where the user can manually adjust the vessel's speed, heading and other navigation characteristics, and a real-time status monitoring dashboard that displays the vessel's speed, heading, engine status and other key performance indicators.

9. The ship automatic obstacle avoidance and intelligent navigation control system as claimed in claim 1, characterized in that: The system can exchange data with other ships or coastal facilities through wireless communication modules, using the following communication protocols: Data_Exchange=m(Local_Data,Remote_Request)=Data_Compression(Local_Data)×Encryption()+Data_Decoding(Remote_Request) Where m is the data exchange function, Data_CompressionData_Compression is a data compression function used to reduce the amount of data transmitted, and EncryptionEncryption is an encryption function to ensure data security; Data_DecodingData_Decoding is a decoding function used to parse the received data.

10. The ship automatic obstacle avoidance and intelligent navigation control system as claimed in claim 1, characterized in that: The system also includes an emergency obstacle avoidance module that can automatically take obstacle avoidance measures when an emergency is detected, such as emergency stopping, emergency turning, or releasing life-saving equipment.

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