Unmanned ship navigation route planning method and system based on artificial intelligence

Abstract

The invention discloses an unmanned ship navigation route planning method and system based on artificial intelligence, and belongs to the technical field of route planning, and the method comprises the following steps: firstly, obtaining the information of an environment; according to the method, the process for further optimizing the planned navigation route is set in the method, after the route is generated, the route information can be further adjusted and optimized according to the real-time multi-dimensional information on the sea, the scientificity and safety of the route can be further improved, and the method is suitable for popularization and application. Meanwhile, early warning strategies aiming at multiple dimensions on the route are set in the method, rapid early warning response can be carried out when the unmanned ship encounters an emergency in the sailing process, meanwhile, a simulation and evaluation process aiming at the route is set in the method, simulation processing can be carried out on the finally generated route information, and the accuracy of the route information is improved. And targeted improvement is carried out according to the final evaluation result, the effectiveness and accuracy of the route information can be further improved, and the actual application effect of the whole method is good.

Description

Technical Field

[0001] The present invention belongs to the technical field of route planning, and in particular relates to an unmanned ship navigation route planning method and system based on artificial intelligence. Background Art

[0002] Route planning, as the name implies, is the process of planning a route. It is a process of determining the best path through algorithms and techniques. It is usually used in geographic information systems (GIS) and navigation applications to help users find the best route from the starting point to the destination. When some unmanned ships are sailing, route planning is required so that the unmanned ships can safely sail along the route.

[0003] The Chinese patent (CN114935933A) discloses a route planning method, system and storage medium for unmanned boats, which can effectively improve the convergence speed of the algorithm, optimize the planned route, and effectively improve the navigation safety performance and efficiency of unmanned boats. The method includes: obtaining AIS data, and clustering the AIS data to obtain cluster points; constructing an undirected connected graph according to the cluster points; calculating the initial path according to the undirected connected graph; constructing a navigation area according to the navigation points on the initial path; wherein the cluster points on the initial path are used as navigation points; sampling and branch expansion are performed according to the navigation area to obtain a first planned route; path compression is performed on the first planned route according to the DP trajectory compression algorithm to obtain a second planned route; determining that the curvature change of the first path segment of the second planned route is greater than the preset curvature, and optimizing the corner of the first path segment to obtain a second path segment; obtaining a target planned route according to the second planned route and the second path segment. Although the current route planning method system can also realize route planning, it can only generate some safe routes with shorter distances, but does not further optimize the generated routes, and cannot adjust the route information according to the real-time maritime conditions. At the same time, there is no supporting early warning strategy, and it is impossible to respond quickly after an emergency occurs. The application effect of the overall method system is not good. In order to solve this problem, an unmanned ship navigation route planning method and system based on artificial intelligence is urgently needed. Summary of the invention

[0004] The purpose of the present invention is to solve the problem that although the current route planning method system can also realize route planning, it can only generate some safe routes with shorter distances, but does not further optimize the generated routes, and cannot adjust the route information according to the real-time marine conditions. At the same time, it is not equipped with an early warning strategy, and cannot quickly respond to emergencies. The application effect of the overall method system is not good. A method and system for unmanned ship navigation route planning based on artificial intelligence is proposed.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a method for planning a navigation route of an unmanned ship based on artificial intelligence, comprising the following steps:

[0006] S1. First obtain information about the environment;

[0007] S2. It is conducive to the establishment of water space model by remote sensing technology;

[0008] S3, determining the starting point and end point of the unmanned ship route;

[0009] S4, find a suitable route planning algorithm from the data model;

[0010] S5, automatically plan the navigation route;

[0011] S6. Automatically further optimize the navigation route;

[0012] S7, automatically generate early warning strategies;

[0013] S8. Simulate and evaluate the navigation route.

[0014] As a further description of the above technical solution:

[0015] In S1, information about the environment is first acquired, and the acquired information includes geographical location information of the water area, water depth information of the water area, flow velocity information of the water area, meteorological information of the water area and flow direction information of the water area.

[0016] As a further description of the above technical solution:

[0017] In S2, remote sensing technology is used to establish a water area space model. The specific steps are: first use remote sensing technology to monitor the water area, mark obstacles in the water area, mark small islands in the water area, import the information into the environmental integration system, and form a water area space model.

[0018] As a further description of the above technical solution:

[0019] In S3, the starting point and the end point of the unmanned ship route are determined, and the positions of the starting point and the end point are selected to ensure that there is no signal shielding or interference within 7-10 nautical miles around the two points.

[0020] As a further description of the above technical solution:

[0021] In S4, a suitable route planning algorithm is found from the data model, and the route planning algorithm is one or more of Dijkstra algorithm, A algorithm, Floyd algorithm, ant colony algorithm, particle swarm optimization algorithm and genetic algorithm.

[0022] As a further description of the above technical solution:

[0023] In the above-mentioned S5, the navigation route is automatically planned, and the specific steps are as follows: importing the selected planning algorithm, importing the starting point and end point information of the route, inputting the constraint conditions within the route, and automatically generating the navigation route. The number of generated routes is 5-8.

[0024] As a further description of the above technical solution:

[0025] In S6, the navigation route is further optimized automatically, and the parameters that need to be referred to in the optimization process include real-time weather, real-time route busyness, real-time water area wind and wave conditions, and real-time water flow conditions.

[0026] As a further description of the above technical solution:

[0027] In S7, an early warning strategy is automatically generated, and the generated early warning strategy includes an emergency obstacle avoidance strategy for obstacles that suddenly appear on the route, an emergency handling strategy for collision between the hull and external objects during navigation, and an emergency handling strategy for information loss during navigation.

[0028] As a further description of the above technical solution:

[0029] In the above S8, the navigation route is simulated and evaluated. The specific steps are as follows: the navigation route is imported into the simulation system, the simulation system is used to perform simulation analysis on the route, and the simulation result is evaluated. The evaluation result is divided into three categories: excellent, good and poor. When the evaluation result is good or poor, targeted suggestions for improving the navigation route can be automatically generated and exported.

[0030] The present invention also discloses an unmanned ship navigation route planning system based on artificial intelligence, comprising an environmental information acquisition module, the output end of the environmental information acquisition module is connected to the input end of a water area space model establishment module, the output end of the water area space model establishment module is connected to the input end of a route starting point and end point determination module, the output end of the route starting point and end point determination module is connected to the input end of a route planning algorithm search module, the output end of the route planning algorithm search module is connected to the input end of a navigation route automatic planning module, the output end of the navigation route automatic planning module is connected to the input end of a navigation route automatic optimization module, the output end of the navigation route automatic optimization module is connected to the input end of an early warning strategy automatic generation module, and the output end of the early warning strategy automatic generation module is connected to the input end of a navigation route simulation and evaluation module.

[0031] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0032] In the present invention, the method is provided with a process for further optimizing the planned navigation route. After the route is generated, the route information can be further adjusted and optimized according to real-time multi-dimensional information at sea, which can further improve the scientificity and safety of the route. At the same time, the method is also provided with early warning strategies for multiple dimensions on the route, which can quickly warn and respond to emergencies encountered during the navigation of the unmanned ship, thereby reducing losses and ensuring the safety of the hull as much as possible. At the same time, the method is also provided with a simulation and evaluation process for the route, which can simulate the finally generated route information, and make targeted improvements according to the final evaluation results, which can further improve the effectiveness and accuracy of the route information, and the overall method has good practical application effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 The flowchart is a method for unmanned ship navigation route planning based on artificial intelligence.

[0034] Figure 2 This is a schematic diagram of the module structure of an unmanned ship navigation route planning system based on artificial intelligence. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Example 1

[0037] See also Figure 1 The present invention provides a technical solution: an unmanned ship navigation route planning method based on artificial intelligence, comprising the following steps:

[0038] S1. First, obtain information about the environment, including geographical location information of the water area, water depth information of the water area, flow velocity information of the water area, meteorological information of the water area, and flow direction information of the water area;

[0039] S2. Use remote sensing technology to establish a water area spatial model. The specific steps are: first use remote sensing technology to monitor the water area, mark obstacles in the water area, mark small islands in the water area, import the information into the environmental integration system, and form a water area spatial model;

[0040] S3. Determine the starting point and end point of the unmanned ship route, and ensure that there is no signal shielding or interference within 10 nautical miles of the two points when selecting the locations of the starting point and the end point;

[0041] S4, finding a suitable route planning algorithm from the data model, the route planning algorithm is Dijkstra algorithm;

[0042] S5, automatically planning the navigation route, the specific steps are: importing the selected planning algorithm, importing the starting point and end point information of the route, inputting the constraint conditions within the route, automatically generating the navigation route, and generating 5 routes;

[0043] S6. Automatically further optimize the navigation route. The parameters that need to be referred to in the optimization process include real-time weather, real-time route busyness, real-time water area wind and wave conditions, and real-time water flow conditions;

[0044] S7, automatically generate warning strategies, including emergency obstacle avoidance strategies for obstacles that suddenly appear on the route, emergency handling strategies for collisions between the hull and external objects during navigation, and emergency handling strategies for information loss during navigation;

[0045] S8. Simulate and evaluate the navigation route. The specific steps are: import the navigation route into the simulation system, use the simulation system to simulate and analyze the route, and evaluate the simulation results. The evaluation results are divided into three categories: excellent, good, and poor. When the evaluation results are good or poor, targeted suggestions for improving the navigation route can be automatically generated and exported.

[0046] See also Figure 2 The present invention also provides an unmanned ship navigation route planning system based on artificial intelligence, including an environmental information acquisition module, the output end of the environmental information acquisition module is connected to the input end of the water space model establishment module, the output end of the water space model establishment module is connected to the input end of the route starting point and end point determination module, the output end of the route starting point and end point determination module is connected to the input end of the route planning algorithm search module, the output end of the route planning algorithm search module is connected to the input end of the navigation route automatic planning module, the output end of the navigation route automatic planning module is connected to the input end of the navigation route automatic optimization module, the output end of the navigation route automatic optimization module is connected to the input end of the early warning strategy automatic generation module, and the output end of the early warning strategy automatic generation module is connected to the input end of the navigation route simulation and evaluation module.

[0047] In this embodiment, the method is provided with a process for further optimizing the planned sailing route. After the route is generated, the route information can be further adjusted and optimized according to real-time multi-dimensional information at sea, which can further improve the scientificity and safety of the route.

[0048] Example 2

[0049] See also Figure 1The present invention provides a technical solution: an unmanned ship navigation route planning method based on artificial intelligence, comprising the following steps:

[0050] S1. First, obtain information about the environment, including geographical location information of the water area, water depth information of the water area, flow velocity information of the water area, meteorological information of the water area, and flow direction information of the water area;

[0051] S2. Use remote sensing technology to establish a water area spatial model. The specific steps are: first use remote sensing technology to monitor the water area, mark obstacles in the water area, mark small islands in the water area, import the information into the environmental integration system, and form a water area spatial model;

[0052] S3. Determine the starting point and end point of the unmanned ship route, and ensure that there is no signal shielding or interference within 7 nautical miles of the two points when selecting the locations of the starting point and the end point;

[0053] S4, finding a suitable route planning algorithm from the data model, the route planning algorithms are Dijkstra algorithm, particle swarm optimization algorithm and genetic algorithm;

[0054] S5, automatically planning the navigation route, the specific steps are: importing the selected planning algorithm, importing the starting point and end point information of the route, inputting the constraint conditions within the route, automatically generating the navigation route, and generating 8 routes;

[0055] S6. Automatically further optimize the navigation route. The parameters that need to be referred to in the optimization process include real-time weather, real-time route busyness, real-time water area wind and wave conditions, and real-time water flow conditions;

[0056] S7, automatically generate warning strategies, including emergency obstacle avoidance strategies for obstacles that suddenly appear on the route, emergency handling strategies for collisions between the hull and external objects during navigation, and emergency handling strategies for information loss during navigation;

[0057] S8. Simulate and evaluate the navigation route. The specific steps are: import the navigation route into the simulation system, use the simulation system to simulate and analyze the route, and evaluate the simulation results. The evaluation results are divided into three categories: excellent, good, and poor. When the evaluation results are good or poor, targeted suggestions for improving the navigation route can be automatically generated and exported.

[0058] See also Figure 2The present invention also provides an unmanned ship navigation route planning system based on artificial intelligence, including an environmental information acquisition module, the output end of the environmental information acquisition module is connected to the input end of the water space model establishment module, the output end of the water space model establishment module is connected to the input end of the route starting point and end point determination module, the output end of the route starting point and end point determination module is connected to the input end of the route planning algorithm search module, the output end of the route planning algorithm search module is connected to the input end of the navigation route automatic planning module, the output end of the navigation route automatic planning module is connected to the input end of the navigation route automatic optimization module, the output end of the navigation route automatic optimization module is connected to the input end of the early warning strategy automatic generation module, and the output end of the early warning strategy automatic generation module is connected to the input end of the navigation route simulation and evaluation module.

[0059] In this embodiment, the method also includes a simulation and evaluation process for the route, which can simulate the route information finally generated and make targeted improvements based on the final evaluation results, thereby further improving the effectiveness and accuracy of the route information. The overall method has good practical application effect.

[0060] Example 3

[0061] See also Figure 1 The present invention provides a technical solution: an unmanned ship navigation route planning method based on artificial intelligence, comprising the following steps:

[0062] S1. First, obtain information about the environment, including geographical location information of the water area, water depth information of the water area, flow velocity information of the water area, meteorological information of the water area, and flow direction information of the water area;

[0063] S2. Use remote sensing technology to establish a water area spatial model. The specific steps are: first use remote sensing technology to monitor the water area, mark obstacles in the water area, mark small islands in the water area, import the information into the environmental integration system, and form a water area spatial model;

[0064] S3. Determine the starting point and the end point of the unmanned ship route, and ensure that there is no signal shielding or interference within 9 nautical miles of the two points when selecting the locations of the starting point and the end point;

[0065] S4. Find a suitable route planning algorithm from the data model. The route planning algorithms are Floyd algorithm and ant colony algorithm.

[0066] S5, automatically planning the navigation route, the specific steps are: importing the selected planning algorithm, importing the starting point and end point information of the route, inputting the constraint conditions within the route, automatically generating the navigation route, and generating 7 routes;

[0067] S6. Automatically further optimize the navigation route. The parameters that need to be referred to in the optimization process include real-time weather, real-time route busyness, real-time water area wind and wave conditions, and real-time water flow conditions;

[0068] S7, automatically generate warning strategies, including emergency obstacle avoidance strategies for obstacles that suddenly appear on the route, emergency handling strategies for collisions between the hull and external objects during navigation, and emergency handling strategies for information loss during navigation;

[0069] S8. Simulate and evaluate the navigation route. The specific steps are: import the navigation route into the simulation system, use the simulation system to simulate and analyze the route, and evaluate the simulation results. The evaluation results are divided into three categories: excellent, good, and poor. When the evaluation results are good or poor, targeted suggestions for improving the navigation route can be automatically generated and exported.

[0070] See also Figure 2 The present invention also provides an unmanned ship navigation route planning system based on artificial intelligence, including an environmental information acquisition module, the output end of the environmental information acquisition module is connected to the input end of the water space model establishment module, the output end of the water space model establishment module is connected to the input end of the route starting point and end point determination module, the output end of the route starting point and end point determination module is connected to the input end of the route planning algorithm search module, the output end of the route planning algorithm search module is connected to the input end of the navigation route automatic planning module, the output end of the navigation route automatic planning module is connected to the input end of the navigation route automatic optimization module, the output end of the navigation route automatic optimization module is connected to the input end of the early warning strategy automatic generation module, and the output end of the early warning strategy automatic generation module is connected to the input end of the navigation route simulation and evaluation module.

[0071] In this embodiment, the method is also provided with early warning strategies for multiple dimensions on the route, which can provide rapid early warning responses when an emergency occurs during the navigation of the unmanned ship, thereby reducing losses and ensuring the safety of the ship as much as possible.

[0072] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for unmanned ship navigation route planning based on artificial intelligence, characterized in that: The steps include: S1. First obtain information about the environment; S2. It is conducive to the establishment of water space model by remote sensing technology; S3, determining the starting point and end point of the unmanned ship route; S4, find a suitable route planning algorithm from the data model; S5, automatically plan the navigation route; S6. Automatically further optimize the navigation route; S7, automatically generate early warning strategies; S8. Simulate and evaluate the navigation route.

2. The method for planning a navigation route for an unmanned ship based on artificial intelligence according to claim 1, characterized in that: In S1, information about the environment is first acquired, and the acquired information includes geographical location information of the water area, water depth information of the water area, flow velocity information of the water area, meteorological information of the water area and flow direction information of the water area.

3. The method for planning a navigation route for an unmanned ship based on artificial intelligence according to claim 1, characterized in that: In S2, remote sensing technology is used to establish a water area space model. The specific steps are: first use remote sensing technology to monitor the water area, mark obstacles in the water area, mark small islands in the water area, import the information into the environmental integration system, and form a water area space model.

4. The method for planning a navigation route for an unmanned ship based on artificial intelligence according to claim 1, characterized in that: In S3, the starting point and the end point of the unmanned ship route are determined, and the positions of the starting point and the end point are selected to ensure that there is no signal shielding or interference within 7-10 nautical miles around the two points.

5. The method for planning a navigation route for an unmanned ship based on artificial intelligence according to claim 1, characterized in that: In S4, a suitable route planning algorithm is found from the data model, and the route planning algorithm is one or more of Dijkstra algorithm, A algorithm, Floyd algorithm, ant colony algorithm, particle swarm optimization algorithm and genetic algorithm.

6. The method for planning a navigation route for an unmanned ship based on artificial intelligence according to claim 1, characterized in that: In the above-mentioned S5, the navigation route is automatically planned, and the specific steps are as follows: importing the selected planning algorithm, importing the starting point and end point information of the route, inputting the constraint conditions within the route, and automatically generating the navigation route. The number of generated routes is 5-8.

7. The method for planning a navigation route for an unmanned ship based on artificial intelligence according to claim 1, characterized in that: In S6, the navigation route is further optimized automatically, and the parameters that need to be referred to in the optimization process include real-time weather, real-time route busyness, real-time water area wind and wave conditions, and real-time water flow conditions.

8. The method for planning a navigation route for an unmanned ship based on artificial intelligence according to claim 1, characterized in that: In S7, an early warning strategy is automatically generated, and the generated early warning strategy includes an emergency obstacle avoidance strategy for obstacles that suddenly appear on the route, an emergency handling strategy for collision between the hull and external objects during navigation, and an emergency handling strategy for information loss during navigation.

9. The method for planning a navigation route for an unmanned ship based on artificial intelligence according to claim 1, characterized in that: In the above S8, the navigation route is simulated and evaluated. The specific steps are as follows: the navigation route is imported into the simulation system, the simulation system is used to perform simulation analysis on the route, and the simulation result is evaluated. The evaluation result is divided into three categories: excellent, good and poor. When the evaluation result is good or poor, targeted suggestions for improving the navigation route can be automatically generated and exported.

10. An unmanned ship navigation route planning system based on artificial intelligence, characterized in that: It includes an environmental information acquisition module, the output end of the environmental information acquisition module is connected to the input end of the water area space model establishment module, the output end of the water area space model establishment module is connected to the input end of the route starting point and end point determination module, the output end of the route starting point and end point determination module is connected to the input end of the route planning algorithm search module, the output end of the route planning algorithm search module is connected to the input end of the navigation route automatic planning module, the output end of the navigation route automatic planning module is connected to the input end of the navigation route automatic optimization module, the output end of the navigation route automatic optimization module is connected to the input end of the early warning strategy automatic generation module, and the output end of the early warning strategy automatic generation module is connected to the input end of the navigation route simulation and evaluation module.

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