Unmanned surface vehicle cluster collaborative hunting method based on navigation risk constraint
By constructing a navigation risk model and optimizing algorithms to determine the optimal encirclement point, the problem of monotonous formation in the collaborative encirclement of unmanned surface vessels was solved, and adaptive formation adjustment and efficient encirclement were achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- DALIAN MARITIME UNIVERSITY
- Filing Date
- 2026-04-10
- Publication Date
- 2026-05-12
AI Technical Summary
Existing methods for collaborative encirclement and capture of unmanned surface vessels (USVs) often suffer from simplistic formations, lack of optimization at capture points, and difficulty in describing the constraints on the target vessel's maneuverability. This results in longer navigation paths, suboptimal capture trajectories, and low collaborative efficiency.
A navigation risk model for the target vessel is constructed, an optimization model for the capture point is established, an optimization algorithm is used to determine the optimal capture point, and the navigation direction is calculated using the artificial potential field method. The capture point is then dynamically updated to form an adaptive formation.
It improves the rationality and reliability of the encirclement and capture judgment, shortens the encirclement and capture completion time, and enhances the efficiency and flexibility of the collaborative encirclement and capture of unmanned surface vessel swarms.
Smart Images
Figure CN122018549A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of collaborative control and decision-making technology for marine unmanned systems, specifically to a collaborative encirclement and capture method for surface unmanned surface vessels based on navigation risk constraints. Background Technology
[0002] With the development of marine development and intelligent maritime equipment technology, unmanned surface vessels (USVs) are increasingly being used in missions such as maritime patrol, target surveillance, coordinated pursuit, and anti-submarine warfare. To improve mission efficiency and system reliability, multiple USVs typically work in swarms, completing complex maritime tasks through information sharing and coordinated control. Coordinated pursuit is a key application scenario for USV swarms, aiming to constrain the movement space of a target vessel through multi-vessel cooperation, thereby achieving effective target control.
[0003] In existing technologies, swarm-based unmanned surface vessels (USVs) typically form an encirclement structure by pre-setting several encirclement points around the target and having each USV reach its corresponding point. While this method achieves basic encirclement functionality, the resulting formation is relatively simplistic and fails to adequately consider the diversity of encirclement point locations and formations. This can lead to problems such as longer USV navigation paths, suboptimal encirclement trajectories, and low coordination efficiency, thereby prolonging the mission completion time and increasing system energy consumption. Furthermore, existing methods struggle to effectively describe the constraints on the target vessel's maneuverability.
[0004] Therefore, there is an urgent need for a collaborative encirclement and capture method for surface unmanned surface vessels that can describe the maneuverability constraints of target ships, optimize the location of the encirclement point, and achieve adaptive formation adjustment. Summary of the Invention
[0005] To address the problems of existing technologies, such as monotonous encirclement formations, lack of optimized encirclement points, and difficulty in describing target maneuver constraints, this invention provides a swarm-based collaborative encirclement method for unmanned surface vessels (USVs) based on navigation risk constraints, specifically including the following steps:
[0006] Obtain the position and course information of the target vessel, and establish a navigation risk model for the target vessel; Based on the aforementioned navigation risk model, the conditions for successful coordinated capture by a swarm of unmanned surface vessels are determined. Based on the conditions for successful coordinated encirclement and capture, an optimization model for the encirclement point is established, and an optimization algorithm is used to determine the optimal encirclement point for each unmanned surface vessel. The navigation direction of each surface unmanned vessel is calculated based on the optimal capture point, and the surface unmanned vessel cluster is controlled to move towards the corresponding optimal capture point. During the encirclement and capture process, the navigation risk model is dynamically updated based on the current motion state of the target vessel, and the corresponding optimal encirclement point and navigation direction are recalculated. This drives the unmanned surface vessels that have not yet reached the optimal encirclement point to continue moving until all unmanned surface vessels reach their corresponding optimal encirclement points, forming a coordinated encirclement and capture formation against the target vessel.
[0007] Furthermore, a navigation risk model is established to describe the safe navigation area and risk distribution characteristics around the target vessel. The formula is:
[0008] in, The location is any point in the area surrounding the target. The location of the target vessel. The course of the target vessel.
[0009] Furthermore, the conditions for successful coordinated encirclement and capture by a swarm of unmanned surface vessels. The formula is:
[0010] in, The set of locations in the area surrounding the target. This is the navigation risk threshold.
[0011] Furthermore, an optimization model for the capture point is established with the goal of minimizing the capture cost. The formula is:
[0012] in, Let the capture cost function be... This is a collection of the locations of unmanned surface vessels. A set of capture points that meet the conditions for successful coordinated capture.
[0013] Furthermore, an optimization algorithm is used to optimize the capture points, determining the optimal capture point for each unmanned surface vessel, and the set of optimal capture points is then established. The formula is: .
[0014] Furthermore, based on the optimal encirclement point, the navigation direction of each surface unmanned vessel is calculated, and the navigation direction... The formula is:
[0015] in, For unmanned surface vessels The corresponding optimal capture point.
[0016] Furthermore, the navigation direction of the unmanned surface vessel is determined by an artificial potential field method. The steps of the artificial potential field method include: calculating the gravitational potential field of the optimal capture point on the unmanned surface vessel; calculating the repulsive potential field of the obstacle on the unmanned surface vessel; superimposing the gravitational potential field and the repulsive potential field to obtain the total potential field and calculating the resultant force direction, which is the navigation direction of the unmanned surface vessel.
[0017] Compared with the prior art, the present invention has the following beneficial effects: (1) This invention constructs a navigation risk model of the target vessel, transforms the navigation safety of the area surrounding the target into a quantifiable risk distribution, and establishes conditions for successful coordinated encirclement on this basis. This allows for a description of the maneuverability constraints of the target vessel from the perspective of navigation risk, giving the conditions for coordinated encirclement a clear mathematical expression and improving the rationality and reliability of the encirclement judgment.
[0018] (2) The present invention establishes an optimization model for the capture point under the constraints of navigation risk, and determines the optimal capture point corresponding to each surface unmanned vessel through the optimization algorithm, so that the capture formation can be adaptively adjusted according to the target status and the distribution of surface unmanned vessels, thereby shortening the capture completion time of surface unmanned vessels and improving the efficiency and flexibility of surface unmanned vessel clusters in performing collaborative capture tasks. Attached Figure Description
[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0020] Figure 1 This is a flowchart of a collaborative encirclement and capture method for unmanned surface vessels based on navigation risk constraints according to the present invention.
[0021] Figure 2 This is a flowchart of a collaborative encirclement and capture method for unmanned surface vessels based on navigation risk constraints in an embodiment of the present invention. Detailed Implementation
[0022] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.
[0023] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0024] As attached Figure 1 As shown, this invention discloses a collaborative encirclement and capture method for unmanned surface vessels (USVs) based on navigation risk constraints, which mainly includes the following steps: S1. Obtain the position and heading information of the target vessel and establish a navigation risk model for the target vessel.
[0025] S2. Based on the navigation risk model, determine the conditions for successful coordinated capture by the unmanned surface vessel swarm.
[0026] S3. Based on the conditions for successful coordinated encirclement and capture, establish an optimization model for the encirclement point and use an optimization algorithm to determine the optimal encirclement point for each unmanned surface vessel.
[0027] S4. Calculate the navigation direction of each surface unmanned vessel based on the optimal capture point, and control the surface unmanned vessel cluster to move towards the corresponding optimal capture point.
[0028] S5. During the encirclement process, based on the current motion state of the target vessel, the navigation risk model is dynamically updated and the corresponding optimal encirclement point and navigation direction are recalculated. The unmanned surface vessels that have not yet reached the optimal encirclement point are driven to continue moving until all unmanned surface vessels reach their corresponding optimal encirclement points, forming a coordinated encirclement formation against the target vessel.
[0029] As a preferred embodiment of this application, a navigation risk model is established to describe the safe navigation area and risk distribution characteristics around the target vessel. The formula is:
[0030] in, The location is any point in the area surrounding the target. The location of the target vessel. The course of the target vessel.
[0031] As a preferred embodiment of this application, the conditions for successful coordinated encirclement and capture by a swarm of unmanned surface vessels are as follows: The formula is:
[0032] in, The set of locations in the area surrounding the target. This is the navigation risk threshold.
[0033] As a preferred embodiment of this application, an optimization model for the capture point is established with the goal of minimizing the capture cost. The formula is:
[0034] in, Let the capture cost function be... This is a collection of the locations of unmanned surface vessels. A set of capture points that meet the conditions for successful coordinated capture.
[0035] As a preferred embodiment of this application, an optimization algorithm is used to optimize the capture points and determine the optimal capture point corresponding to each unmanned surface vessel. The set of the optimal capture points is... The formula is: .
[0036] In a preferred embodiment of this application, the navigation direction of each unmanned surface vessel is calculated based on the optimal encirclement point, wherein the navigation direction... The formula is:
[0037] in, For unmanned surface vessels The corresponding optimal capture point.
[0038] In a preferred embodiment of this application, the navigation direction of the unmanned surface vessel is determined by an artificial potential field method. The steps of the artificial potential field method include: calculating the gravitational potential field of the optimal capture point on the unmanned surface vessel; calculating the repulsive potential field of the obstacle on the unmanned surface vessel; superimposing the gravitational potential field and the repulsive potential field to obtain the total potential field and calculating the resultant force direction, which is the navigation direction of the unmanned surface vessel.
[0039] Example The following is in conjunction with the appendix Figure 2 The present invention will be further described in detail with reference to the embodiments.
[0040] S1. Establish a navigation risk model for the target vessel. Ship navigation risk describes the safety level of a ship during navigation. Higher navigation risk indicates a greater likelihood of collisions or other navigational accidents, and lower navigation safety. To assess ship navigation risk, a ship domain is typically used to describe the safe area surrounding the ship. The steps for establishing a target ship's navigation risk model based on the ship domain are as follows: S11. Calculate the ship's domain for the target vessel. D own ,Right now:
[0041] in, and Let these represent the major and minor axes of the ellipse, respectively. , () represents the coordinates of the geometric center of the ellipse. The geometric center of the ellipse is relative to the position of the target ship. , The relationship between ) is expressed as:
[0042] in, This represents the displacement along the semi-major axis of the ellipse from the geometric center of the ellipse towards the stern of the ship. It represents the displacement along the semi-minor axis of the ellipse from the geometric center of the ellipse toward the port side of the ship.
[0043] S12. Calculate the navigation risk of the target vessel. ,Right now:
[0044] in, Indicates the capture of unmanned boats The location coordinates.
[0045] S2. Determine the conditions for successful coordinated encirclement and capture by a swarm of unmanned surface vessels. When the target vessel sails in any direction, an unmanned surface vessel will enter the target vessel's territorial waters. The text indicates that the coordinated encirclement and capture by the surface unmanned surface vessel swarm has been successfully completed. The conditions for the successful coordinated encirclement and capture by the surface unmanned surface vessel swarm are:
[0046] in, express The ship's domain at any given moment; express The ship's domain at any given time.
[0047] To achieve the conditions for a coordinated encirclement and capture operation by a swarm of unmanned surface vessels, at least three such vessels are required:
[0048] in,( , (Represents the capture of unmanned boats) P i The coordinates.
[0049] S3. Determine the optimal encirclement point for each surface unmanned vessel. The optimal capture point for each surface unmanned surface vessel (USV) that satisfies the conditions for successful swarm-based coordinated capture was found using the particle swarm optimization algorithm. The steps are as follows: S31, Calculation of unmanned surface vessels Corresponding capture points ,Right now:
[0050] in, Indicates unmanned surface vessels The heading angle, It is a capture point The ellipse parameter is calculated using the following formula:
[0051] Among them, the enclosing angle Encirclement point The line connecting to the geometric center of the target ship's domain and the positive x The angle between axes.
[0052] S32. Calculate the objective function ,Right now:
[0053] in, and These are weighting coefficients. Indicates unmanned surface vessels to the encirclement point Time, Indicates unmanned surface vessels to the encirclement point distance, This indicates the number of unmanned surface vessels.
[0054] S33. Calculate the optimal encirclement point for each unmanned surface vessel. ,make
[0055] As the position vector in the particle swarm optimization algorithm, the objective function As the fitness function of the particle swarm optimization algorithm, the objective function is solved using the particle swarm optimization algorithm. The optimal encirclement angle vector corresponding to the minimum value α This yields the optimal capture point for each unmanned surface vessel. for: .
[0056] S4. Determine the course of each surface unmanned surface vessel. Based on the determined optimal capture point for each surface unmanned surface vessel (USV), the navigation direction of each USV is set, and each USV travels in this direction. The steps for calculating the navigation direction of each USV are as follows: S41, Calculation of unmanned surface vessels Corresponding capture points right gravitational potential field :
[0057] in, Gravitational gain coefficient, This indicates the size of an unmanned surface vessel. Arrival at the capture point The Euclidean distance between them, in the direction from the unmanned surface vessel. Pointing to the encirclement point The vector.
[0058] S42, Calculate obstacles unmanned surface vessels repulsive potential field :
[0059] in, The repulsive gain coefficient is... The range of influence of the obstacle. This indicates the size of an unmanned surface vessel. Reach the obstacle location The Euclidean distance between them, in the direction from the location of the obstacle. Pointing to the surface unmanned boat ; S43, Calculation of unmanned surface vessels Affected by the overall external situation : .
[0060] S44, Calculation of unmanned surface vessels The combined force received : .
[0061] S45, Calculation of unmanned surface vessels course : .
[0062] in, and The resultant force along shaft and The component of the force on the axis.
[0063] S5, Controlling Unmanned Surface Vessels With speed along the course Proceed forward; if there are still unmanned surface vessels in the swarm that have not reached their corresponding capture points, return to S1, recalculate the capture points corresponding to each unmanned surface vessel according to S1 to S4, and give the navigation direction of each unmanned surface vessel until all unmanned surface vessels in the swarm have reached their corresponding capture points.
[0064] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for collaborative encirclement and capture of unmanned surface vessels (USVs) based on navigation risk constraints, characterized in that, Includes the following steps: Obtain the position and course information of the target vessel, and establish a navigation risk model for the target vessel; Based on the aforementioned navigation risk model, the conditions for successful coordinated capture by a swarm of unmanned surface vessels are determined. Based on the conditions for successful coordinated encirclement and capture, an optimization model for the encirclement point is established, and an optimization algorithm is used to determine the optimal encirclement point for each unmanned surface vessel. The navigation direction of each surface unmanned vessel is calculated based on the optimal capture point, and the surface unmanned vessel cluster is controlled to move towards the corresponding optimal capture point. During the encirclement and capture process, the navigation risk model is dynamically updated based on the current motion state of the target vessel, and the corresponding optimal encirclement point and navigation direction are recalculated. This drives the unmanned surface vessels that have not yet reached the optimal encirclement point to continue moving until all unmanned surface vessels reach their corresponding optimal encirclement points, forming a coordinated encirclement and capture formation against the target vessel.
2. The method for collaborative encirclement and capture of unmanned surface vessels based on navigation risk constraints according to claim 1, characterized in that, Establish a navigation risk model that describes the safe navigation area and risk distribution characteristics around the target vessel. The formula is: in, The location is any point in the area surrounding the target. The location of the target vessel. The course of the target vessel.
3. The method for coordinated encirclement and capture of unmanned surface vessels based on navigation risk constraints according to claim 2, characterized in that, Conditions for successful coordinated capture by a swarm of unmanned surface vessels The formula is: in, The set of locations in the area surrounding the target. This is the navigation risk threshold.
4. The method for collaborative encirclement and capture of unmanned surface vessels based on navigation risk constraints according to claim 1, characterized in that, An optimization model for the capture point is established with the goal of minimizing the cost of capture. The formula is: in, Let the capture cost function be... This is a collection of the locations of unmanned surface vessels. A set of capture points that meet the conditions for successful coordinated capture.
5. A method for coordinated encirclement and capture of unmanned surface vessels based on navigation risk constraints according to claim 4, characterized in that, An optimization algorithm is used to optimize the capture points, determining the optimal capture point for each unmanned surface vessel. The set of these optimal capture points is... The formula is: 。 6. The method for collaborative encirclement and capture of unmanned surface vessels based on navigation risk constraints according to claim 1, characterized in that, The navigation direction of each unmanned surface vessel is calculated based on the optimal encirclement point. The formula is: in, For unmanned surface vessels The corresponding optimal capture point.
7. The method for collaborative encirclement and capture of unmanned surface vessels based on navigation risk constraints according to claim 1, characterized in that, The navigation direction of the unmanned surface vessel is determined by the artificial potential field method. The steps of the artificial potential field method include: calculating the gravitational potential field of the optimal capture point on the unmanned surface vessel; calculating the repulsive potential field of the obstacle on the unmanned surface vessel; superimposing the gravitational potential field and the repulsive potential field to obtain the total potential field and calculating the resultant force direction, which is the navigation direction of the unmanned surface vessel.