Marine path intelligent planning system and control method thereof

Abstract

The invention provides an ocean path intelligent planning system and a control method thereof. The ocean path intelligent planning system is characterized by comprising an air route planning module and a service interface module which are connected with each other, a dynamic sea area generation mechanism is adopted, full-amount chart loading is abandoned, a local attention area is dynamically generated according to the starting point and the ending point of an air route and the geographic range and the task range of a task area, and then electronic chart data are read in the local attention area, so that on one hand, the memory requirement of a system for embedded hardware can be greatly reduced; and on the other hand, the adaptability of operation coverage can be improved, so that the intelligent planning system can be seamlessly connected with any polygonal operation area planned by the user, and the operation efficiency is improved.

Description

Technical Field

[0001] This invention relates to the technical field of marine path planning, and specifically to an intelligent marine path planning system and its control method. Background Technology

[0002] In existing unmanned vessel operations, marine path planning is typically divided into operational area coverage planning and point-to-point navigation planning. Traditional implementations usually employ a monolithic software architecture, integrating chart data loading, path search algorithms, and navigation control logic into a single process through strong coupling.

[0003] When planning the coverage of the operational area, the ground station or host computer issues a polygonal area composed of multiple latitude and longitude coordinates. The control module inside the unmanned vessel directly generates a round-trip scanning path based on the polygonal area.

[0004] When conducting point-to-point navigation planning, the shortest geometric path is usually found using traditional A* or Dijkstra algorithms based on pre-loaded static nautical chart data.

[0005] The aforementioned existing technical solutions generally suffer from significant drawbacks in practical marine applications, such as poor adaptability to operating areas, lack of kinematic feasibility in path planning, high memory resource consumption and low efficiency, and high degree of architectural coupling.

[0006] Therefore, there is an urgent need to provide a new solution to address the defects and shortcomings of the existing technologies. Summary of the Invention

[0007] To address the deficiencies and shortcomings of the existing technologies, this invention provides an intelligent ocean path planning system and its control method.

[0008] The specific solution provided by this invention is as follows: A marine route intelligent planning system, characterized in that: the system includes interconnected route planning modules and service interface modules, wherein: The route planning module includes a chart data preprocessing unit, a path search unit, and a multi-stage path smoothing optimization unit. The chart data preprocessing unit dynamically delineates the area of ​​interest, reads electronic chart data within the area of ​​interest, analyzes static obstacles, and generates a local raster map. The path search unit defines a three-dimensional state space for the search node, determines an effective extension path in the defined three-dimensional state space, and then adds a cost value to the effective extension path according to influencing factors to form a preliminary search path. The multi-stage path smoothing optimization unit optimizes the initial search path to form the final search path; The service interface module provides a service interface for the route planning module.

[0009] As a further preferred embodiment of the present invention, the nautical chart data preprocessing unit dynamically delineates local areas of interest based on the geographical range of the route start point, end point and mission area, and reads electronic nautical chart data only within the local area of ​​interest, analyzes static obstacles and generates a local raster map.

[0010] As a further preferred embodiment of the present invention, the path search unit includes a state space definition subunit, a node expansion constraint subunit, and a cost function design subunit; wherein... The state space definition sub-unit defines a three-dimensional state space for the search node; The node extension constraint subunit sets constraint conditions to determine the ship trajectory as a valid extension path based on the constraint conditions; The cost function design subunit adds cost value to the effective expansion path based on several influencing factors, and finally forms a preliminary search path.

[0011] As a further preferred embodiment of the present invention, when the state space definition subunit defines a three-dimensional state space for a search node, the coordinates of the search node in the three-dimensional state space are defined as (x, y, θ); where... x represents the x-coordinate of the current position of the search node in the three-dimensional state space; y represents the ordinate of the current position of the search node in the three-dimensional state space; θ represents the heading angle of the current position of the search node in the three-dimensional state space.

[0012] As a further preferred embodiment of the present invention, the constraint conditions set for the node extension constraint subunit are as follows: When the minimum turning radius of the ship's trajectory is greater than the preset radius, the current ship trajectory is determined to be a valid extended path; If the minimum turning radius of the ship's trajectory does not exceed the preset radius, the current ship's trajectory is determined to be an invalid extended path.

[0013] As a further preferred embodiment of the present invention, the cost function design subunit needs to consider several influencing factors when increasing the cost value of the effective extended path, including at least: range distance, distance to obstacles, turning penalty, sea state data and rule restrictions; The cost function design subunit calculates the cost value corresponding to the effective expansion path according to the following formula: J = w1C1+w2C2; Where J is the cost corresponding to the effective extended path; C1 is the basic cost, which includes at least the voyage distance; C2 is the penalty cost, which includes at least the distance to the obstacle, turning penalty, sea state data and rule restrictions; w1 and w2 are the weight coefficients corresponding to the basic cost and penalty cost, respectively. When the cost function design subunit increases the cost value of the effective expansion path based on several influencing factors, it prioritizes increasing the cost value of the upstream navigation path and the sensitive area crossing path.

[0014] As a further preferred embodiment of the present invention, the multi-stage path smoothing optimization unit uses the LOS line-of-sight optimization method to optimize the initial search path once: The initial search path is optimized using the LOS (Line of Sight) optimization method, which includes the following steps: S1: Input: The discrete path point sequence P={p1, p2, ..., p...} obtained from the initial search path. n}; S2: Line of sight detection: S2.1: From the current reference point p start Begin, move towards the target reference point p k Try to connect the lines, and satisfy k > start + 1; S2.2: Check whether the connecting line collides with static obstacles on the nautical chart; S3: Redundancy Removal: S3.1: If the line does not collide with a static obstacle and is not blocked, try to continue connecting the line to the current reference point p. start Compared to a reference point p at a more distant location k+1 ; S3.2: If the connecting line is blocked due to a collision with a static obstacle, the previous safe point p is retained. k-1 As the critical path point, the current reference point p start Updated to p k-1 Repeat the above process and collect all critical path points in the initial search path; S4: Output: Combine all critical path points in the initial search path into a simplified path.

[0015] As a further preferred embodiment of the present invention, the multi-stage path smoothing optimization unit uses cubic spline interpolation smoothing to perform secondary optimization on the initial search path; The secondary optimization of the initial search path using cubic spline interpolation smoothing includes the following steps: S1: Parameterization: The sequence of critical path points obtained after one optimization is used as the model value points, and time t is used as the parameter; S2: Piecewise fitting: at every two adjacent critical path points Pi and P i+1 Construct a cubic polynomial function between them: S i (t)=a i +b i (tt i )+c i (tt i ) 2 +d i (tt i ) 3 ; Among them, S i (t) is a cubic polynomial function constructed with time t as a parameter for the i-th critical path point; a i b i c i d i These are the coefficients for each item; S3: Constraint Solving: Establish a system of equations and solve for coefficient a i b i c i d i The following conditions must be met: S31: Positional constraint: The established equation curve must pass through all critical path points; S32: First derivative continuity: At the connection point, the tangent curvature in the velocity direction is the same; S33: Second derivative continuity: At the connection point, the acceleration curvature is guaranteed to be continuous; S4: Discretized Output: Based on function S i (t) regenerates dense trajectory points at a fixed time step or distance step, and connecting all trajectory points forms the final search path.

[0016] As a further preferred embodiment of the present invention, the service interface module provides at least the following service interfaces to the route planning module: a region creation interface, a list retrieval interface, a planning execution interface, and an extended region retrieval interface.

[0017] Furthermore, the present invention also provides a control method for an intelligent marine path planning system, characterized by comprising the following steps: S100: The chart data preprocessing unit dynamically delineates the area of ​​interest, reads electronic chart data within the area of ​​interest, analyzes static obstacles, and generates a local raster map. S200: The path search unit defines a three-dimensional state space for the search node, determines an effective extension path in the defined three-dimensional state space, and then adds a cost value to the effective extension path according to influencing factors to form a preliminary search path; S300: The multi-stage path smoothing optimization unit optimizes the initial search path.

[0018] Compared with existing technologies, the technical effects that this invention can achieve include: 1) This invention provides an intelligent marine route planning system and its control method. By adopting a dynamic sea area generation mechanism, it abandons the full loading of nautical charts and dynamically generates local areas of interest based on the geographical range of the route start point, end point, and task area. Then, it reads electronic nautical chart data within the local area of ​​interest. On the one hand, it can significantly reduce the system's memory requirements for embedded hardware; on the other hand, it can improve the adaptability of operation coverage, enabling the intelligent planning system to seamlessly connect with any polygonal operation area planned by the user, thereby improving operation efficiency.

[0019] 2) This invention provides an intelligent ocean path planning system and its control method. By setting constraints, the system determines the ship's trajectory as an effective extended path based on the constraints, ensuring that the determined effective extended path strictly adheres to the constraints and avoiding the risk of yaw or loss of control caused by sharp turns in traditional algorithms. At the same time, when defining the three-dimensional state space for the search node, the system synchronously combines the current heading angle information of the search node, fundamentally ensuring that the determined effective extended path is physically executable by the ship, thereby enhancing the safety and reliability of the ship in ocean navigation.

[0020] 3) This invention provides an intelligent marine path planning system and its control method. By setting up a multi-stage path smoothing optimization unit, and combining the LOS line-of-sight optimization method and cubic spline interpolation smoothing method, the initial search path is optimized, and discrete path points are transformed into smooth trajectories with continuous curvature, thereby improving navigation stability and fuel economy. At the same time, path smoothing can also reduce the frequency of servo motor actions, reduce navigation fuel consumption and mechanical wear, and thus improve system operating efficiency.

[0021] 4) This invention provides an intelligent ocean route planning system and its control method. By setting up a service interface module to provide a service interface for the route planning module, the modularization and decoupling of the route planning module are realized, the system integration capability is optimized, and the intelligent planning system can be easily called by different host computer systems, which facilitates the iterative upgrade and distributed deployment of the system. Attached Figure Description

[0022] Figure 1 The diagram shown is a logical structure diagram of the system provided by the present invention.

[0023] Figure 2 The diagram shown is a flowchart of the steps of the method provided by the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] In the description of this invention, it should be noted that the terms "upper," "lower," "inner," "outer," "front end," "rear end," "both ends," "one end," and "the other end," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0026] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installed," "equipped with," "connected," etc., should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0027] [First Embodiment] like Figure 1 As shown, the first embodiment of the present invention provides an intelligent marine path planning system. The system includes an interconnected route planning module and a service interface module. The route planning module provides path planning for ship navigation, and the service interface module provides a service interface for the route planning module. This realizes the modularization and decoupling of the route planning module, optimizes the system integration capability, and enables the intelligent planning system to be easily called by different host computer systems, facilitating system iteration upgrades and distributed deployment.

[0028] like Figure 1 As shown, in this embodiment, the route planning module includes a chart data preprocessing unit, a path search unit, and a multi-stage path smoothing optimization unit. By adopting a hierarchical and progressive path planning strategy, it ensures that the path simultaneously possesses both safety and passability. The nautical chart data preprocessing unit dynamically delineates areas of interest, reads electronic nautical chart data within these areas, analyzes static obstacles, and generates local rasterized maps.

[0029] In this embodiment, the chart data preprocessing unit dynamically delineates local areas of interest based on the geographical scope of the route's starting and ending points and the task area. Electronic chart data is read only within these local areas of interest, static obstacles are analyzed, and a local rasterized map is generated. By employing a dynamic sea area generation mechanism, the full chart loading is eliminated, thus resolving the memory consumption issues that may arise from loading the full chart. Local areas of interest are dynamically generated based on the geographical scope of the route's starting and ending points and the task area, and electronic chart data is then read within these local areas of interest. This significantly reduces the system's memory requirements for embedded hardware and improves the adaptability of operational coverage, enabling the intelligent planning system to seamlessly connect to user-planned arbitrary polygonal operational areas, thereby enhancing operational efficiency.

[0030] In this embodiment, the path search unit defines a three-dimensional state space for the search node, determines an effective expansion path in the defined three-dimensional state space, and then adds a cost value to the effective expansion path according to influencing factors to form a preliminary search path. In this embodiment, the path search unit includes a state space definition subunit, a node expansion constraint subunit, and a cost function design subunit; wherein, The state space definition sub-unit defines a three-dimensional state space for the search node; it is worth noting that when the state space definition sub-unit defines a three-dimensional state space for the search node, the coordinates of the search node in the three-dimensional state space are defined as (x, y, θ); where, x represents the x-coordinate of the current position of the search node in the three-dimensional state space; y represents the ordinate of the current position of the search node in the three-dimensional state space; θ represents the heading angle of the current position of the search node in the three-dimensional state space.

[0031] By combining the current heading angle information of the search node, it is fundamentally guaranteed that the determined effective expansion path is physically feasible for the ship, thereby enhancing the safety and reliability of the ship's navigation at sea.

[0032] The node extension constraint sub-unit sets constraint conditions to determine the ship trajectory as a valid extension path based on the constraint conditions; In this embodiment, the constraint conditions set for the node extension constraint sub-unit are as follows: When the minimum turning radius of the ship's trajectory is greater than the preset radius, the current ship trajectory is determined to be a valid extended path; If the minimum turning radius of the ship's trajectory does not exceed the preset radius, the current ship's trajectory is determined to be an invalid extended path.

[0033] By setting constraints, the ship's trajectory can be determined as an effective extension path based on the constraints. This ensures that the determined effective extension path strictly adheres to the constraints, avoiding the risk of yaw or loss of control caused by sharp turns, which is common with traditional algorithms.

[0034] For example, when a node in the current ship trajectory travels from the initial position (x1, y1, θ1) to the next position (x2, y2, θ2) via the ship trajectory, the curvature of the ship trajectory can be calculated using the change in heading angle Δθ and the displacement. If the calculated minimum turning radius is greater than the ship's physical limit (i.e., the preset radius), it means that the extended path is physically executable and achievable for the ship, and the ship trajectory is determined to be a valid extended path. However, if the calculated minimum turning radius does not exceed the ship's physical limit (i.e., the preset radius), it means that the extended path is physically impossible for the ship to execute or achieve, and the ship trajectory is determined to be an invalid extended path. This ensures the continuity of the ship trajectory path and, as part of the state space, ensures that the tangent direction of the generated path at the connection point is continuous.

[0035] In this embodiment, the cost function design subunit increases the cost value of the effective expansion path based on several influencing factors, and finally forms a preliminary search path.

[0036] In this embodiment, the factors that need to be considered when adding cost value to the effective extended path in the cost function design subunit include at least: range distance, distance to obstacles, turning penalty, sea state data and rule restrictions; The cost function design sub-unit calculates the cost corresponding to the effective expansion path according to the following formula: J = w1C1+w2C2; Where J represents the cost corresponding to the effective extended path; C1 is the basic cost, which includes at least the journey distance, such as Euclidean distance; C2 is the penalty cost, which includes at least the distance to obstacles, turning penalties, sea state data, and rule restrictions; the closer to the obstacle, the greater the cost, and it increases in a stepwise manner (potential field method); in the turning penalty, the larger the change in heading angle Δθ (the sharper or more frequent the turn), the more additional cost will be added to encourage straight-line travel; the more severe the sea state data or the greater the difference from the preset sea state data, the higher the cost will be; and the more the number of times the preset rule restrictions are exceeded or the greater the magnitude of the exceedance, the higher the corresponding cost will be; w1 and w2 are the weighting coefficients corresponding to the basic cost and penalty cost, respectively. When the cost function design subunit increases the cost value of the effective expansion path based on several influencing factors, it prioritizes increasing the cost value of the upstream navigation path and the sensitive area crossing path to achieve optimal economy and compliance.

[0037] In addition, such as Figure 1 As shown, the planning system mentioned in this embodiment also includes a multi-stage path smoothing optimization unit. Although the path generated by the initial search is feasible, there may still be unnecessary minor turns. Therefore, the multi-stage path smoothing optimization unit is used to optimize the initial search path to form the final search path.

[0038] When the multi-stage path smoothing optimization unit optimizes the initial search path: The multi-stage path smoothing optimization unit uses the LOS line-of-sight optimization method to optimize the initial search path once. In this embodiment, optimizing the initial search path using the LOS line-of-sight optimization method includes the following steps: S1: Input: The discrete path point sequence P={p1, p2, ..., pn} obtained from the initial search path; S2: Line of sight detection: S2.1: Starting from the current reference point pstart, attempt to connect to the target reference point pk, and satisfy k>start+1; S2.2: Check whether the connecting line collides with static obstacles on the nautical chart; S3: Redundancy Removal: S3.1: If the connection does not collide with a static obstacle and is not blocked, it means that the intermediate node is redundant and can reach the target reference point pk directly from the current reference point pstart; and try to continue connecting the current reference point pstart with the reference point pk+1 at a more distant location; S3.2: If the connection is blocked due to a collision with a static obstacle, retain the previous safe point pk-1 as the critical path point, update the current reference point pstart to pk-1, and repeat the above process to collect all critical path points in the initial search path. S4: Output: Combines all critical path points in the initial search path into a simplified path, reducing unnecessary fine-tuning and turning.

[0039] Based on this, the multi-stage path smoothing optimization unit further optimizes the initial search path using cubic spline interpolation smoothing.

[0040] The secondary optimization of the initial search path using cubic spline interpolation smoothing includes the following steps: S1: Parameterization: The sequence of critical path points obtained after one optimization is used as the model value points, and time t is used as the parameter; S2: Piecewise fitting: at every two adjacent critical path points P i and P i+1 Construct a cubic polynomial function between them: S i (t)=ai +b i (tt i )+c i (tt i ) 2 +d i (tt i ) 3 ; Among them, S i (t) is a cubic polynomial function constructed with time t as a parameter for the i-th critical path point; a i b i c i d i These are the coefficients for each item; S3: Constraint Solving: Establish a system of equations and solve for coefficient a i b i c i d i The following conditions must be met: S31: Positional constraint: The established equation curve must pass through all critical path points; S32: First derivative continuity: At the connection point, the tangent curvature in the velocity direction is the same; S33: Second derivative continuity: At the connection point, the acceleration curvature is kept continuous to ensure smooth servo control and avoid abrupt changes; S4: Discretized Output: Based on function S i (t) regenerates dense trajectory points at a fixed time step or distance step, and connecting all trajectory points forms the final search path.

[0041] By setting up a multi-stage path smoothing optimization unit, and combining the LOS line-of-sight optimization method and cubic spline interpolation smoothing method to optimize the initial search path, discrete path points are transformed into smooth trajectories with continuous curvature, improving navigation stability and fuel economy. At the same time, path smoothing can also reduce the frequency of servo motor actions, reduce navigation fuel consumption and mechanical wear, thereby improving system operating efficiency.

[0042] In addition, in this embodiment, the service interface module provides the route planning module with at least the following service interfaces: creating region (referring to the aforementioned local area of ​​interest) interface, obtaining list (planned path list) interface, executing planning interface, and obtaining extended region (a certain range extended outward based on the local area of ​​interest, generally used for specific operational scenarios, and its extension method is generally to calculate the minimum bounding rectangle of irregular polygons) interface.

[0043] [Second Embodiment] The second embodiment of the present invention also provides a control method for an intelligent ocean path planning system, comprising the following steps: S100: The chart data preprocessing unit dynamically delineates the area of ​​interest, reads electronic chart data within the area of ​​interest, analyzes static obstacles, and generates a local raster map. S200: The path search unit defines a three-dimensional state space for the search node, determines an effective extension path in the defined three-dimensional state space, and then adds a cost value to the effective extension path according to influencing factors to form a preliminary search path; S300: The multi-stage path smoothing optimization unit optimizes the initial search path.

[0044] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A marine path intelligent planning system, characterized in that: The system includes interconnected route planning modules and service interface modules, wherein: The route planning module includes a chart data preprocessing unit, a path search unit, and a multi-stage path smoothing optimization unit. The chart data preprocessing unit dynamically delineates the area of ​​interest, reads electronic chart data within the area of ​​interest, analyzes static obstacles, and generates a local raster map. The path search unit defines a three-dimensional state space for the search node, determines an effective extension path in the defined three-dimensional state space, and then adds a cost value to the effective extension path according to influencing factors to form a preliminary search path. The multi-stage path smoothing optimization unit optimizes the initial search path to form the final search path; The service interface module provides a service interface for the route planning module.

2. The intelligent ocean path planning system according to claim 1, characterized in that: The chart data preprocessing unit dynamically delineates local areas of interest based on the geographical scope of the route's starting point, ending point, and mission area, and reads electronic chart data only within these local areas of interest, analyzes static obstacles, and generates a local rasterized map.

3. The intelligent ocean path planning system according to claim 1, characterized in that: The path search unit includes a state space definition subunit, a node expansion constraint subunit, and a cost function design subunit; wherein... The state space definition sub-unit defines a three-dimensional state space for the search node; The node extension constraint subunit sets constraint conditions to determine the ship trajectory as a valid extension path based on the constraint conditions; The cost function design subunit adds cost value to the effective expansion path based on several influencing factors, and finally forms a preliminary search path.

4. The intelligent ocean path planning system according to claim 3, characterized in that: When defining a three-dimensional state space for a search node, the state space definition subunit defines the coordinates of the search node in the three-dimensional state space as (x, y, θ); where... x represents the x-coordinate of the current position of the search node in the three-dimensional state space; y represents the ordinate of the current position of the search node in the three-dimensional state space; θ represents the heading angle of the current position of the search node in the three-dimensional state space.

5. The intelligent ocean path planning system according to claim 4, characterized in that: The constraint conditions set for the node extended constraint subunit are as follows: When the minimum turning radius of the ship's trajectory is greater than the preset radius, the current ship trajectory is determined to be a valid extended path; If the minimum turning radius of the ship's trajectory does not exceed the preset radius, the current ship's trajectory is determined to be an invalid extended path.

6. The intelligent ocean path planning system according to claim 3, characterized in that: The factors that need to be considered when adding cost value to the effective extended path in the cost function design subunit include at least: range distance, distance to obstacles, turning penalty, sea state data and rule restrictions; The cost function design subunit calculates the cost value corresponding to the effective expansion path according to the following formula: J = w1C1+w2C2; Where J is the cost corresponding to the effective extended path; C1 is the basic cost, which includes at least the voyage distance; C2 is the penalty cost, which includes at least the distance to obstacles, turning penalties, sea state data, and rule restrictions; w1 and w2 are the weighting coefficients corresponding to the basic cost and penalty cost, respectively. When the cost function design subunit increases the cost value of the effective expansion path based on several influencing factors, it prioritizes increasing the cost value of the upstream navigation path and the sensitive area crossing path.

7. The intelligent ocean path planning system according to claim 1, characterized in that: The multi-stage path smoothing optimization unit uses the LOS line-of-sight optimization method to optimize the initial search path once: The initial search path is optimized using the LOS (Line of Sight) optimization method, which includes the following steps: S1: Input: The discrete path point sequence P={p1, p2, ..., p...} obtained from the initial search path. n }; S2: Line of sight detection: S2.1: From the current reference point p start Begin, move towards the target reference point p k Try to connect the lines, and satisfy k > start + 1; S2.2: Check whether the connecting line collides with static obstacles on the nautical chart; S3: Redundancy Removal: S3.1: If the line does not collide with a static obstacle and is not blocked, try to continue connecting the line to the current reference point p. start Compared to a reference point p at a more distant location k+1 ; S3.2: If the connecting line is blocked due to a collision with a static obstacle, the previous safe point p is retained. k-1 As the critical path point, the current reference point p start Updated to p k-1 Repeat the above process and collect all critical path points in the initial search path; S4: Output: Combine all critical path points in the initial search path into a simplified path.

8. The intelligent ocean path planning system according to claim 7, characterized in that: The multi-stage path smoothing optimization unit uses cubic spline interpolation smoothing to perform secondary optimization on the initial search path; The secondary optimization of the initial search path using cubic spline interpolation smoothing includes the following steps: S1: Parameterization: The sequence of critical path points obtained after one optimization is used as the model value points, and time t is used as the parameter; S2: Piecewise fitting: at every two adjacent critical path points P i and P i+1 Construct a cubic polynomial function between them: S i (t)=a i +b i (t-t i )+c i (t-t i ) 2 +d i (t-t i ) 3 ; Among them, S i (t) is a cubic polynomial function constructed with time t as a parameter for the i-th critical path point; a i b i c i d i These are the coefficients for each item; S3: Constraint Solving: Establish a system of equations and solve for coefficient a i b i c i d i The following conditions must be met: S31: Positional constraint: The established equation curve must pass through all critical path points; S32: First derivative continuity: At the connection point, the tangent curvature in the velocity direction is the same; S33: Second derivative continuity: At the connection point, the acceleration curvature is guaranteed to be continuous; S4: Discretized output: based on function S i (t) regenerates dense trajectory points at a fixed time step or distance step, and connecting all trajectory points forms the final search path.

9. The intelligent ocean path planning system according to claim 1, characterized in that: The service interface module provides at least the following service interfaces to the route planning module: create area interface, get list interface, execute planning interface, and get extended area interface.

10. A control method for an intelligent ocean path planning system according to any one of claims 1-9, characterized in that: Includes the following steps: S100: The chart data preprocessing unit dynamically delineates the area of ​​interest, reads electronic chart data within the area of ​​interest, analyzes static obstacles, and generates a local raster map. S200: The path search unit defines a three-dimensional state space for the search node, determines an effective extension path in the defined three-dimensional state space, and then adds a cost value to the effective extension path according to influencing factors to form a preliminary search path; S300: The multi-stage path smoothing optimization unit optimizes the initial search path.

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