CN-122018549-A - Navigation risk constraint-based water surface unmanned ship cluster collaborative capturing method

CN122018549ACN 122018549 ACN122018549 ACN 122018549ACN-122018549-A

Abstract

The invention relates to the technical field of cooperative control and decision-making of a marine unmanned system, in particular to a water surface unmanned ship cluster cooperative capture method based on navigation risk constraint, which comprises the following steps of obtaining position and heading information of a target ship and establishing a navigation risk model; the method comprises the steps of determining successful cooperative trapping conditions of the water surface unmanned vessels, establishing a trapping point optimization model, determining optimal trapping points corresponding to all the water surface unmanned vessels by adopting an optimization algorithm, calculating the navigation direction of all the water surface unmanned vessels, controlling the water surface unmanned vessels to move towards the corresponding optimal trapping points, dynamically updating a navigation risk model, and recalculating the corresponding optimal trapping points and navigation directions until all the water surface unmanned vessels reach the corresponding optimal trapping points, so as to form cooperative trapping forms for target vessels. The invention solves the problems of single formation of the capturing formation, lack of optimization of capturing points and difficulty in describing the maneuvering constraint of the target in the prior art, and realizes efficient, dynamic and safe cluster collaborative capturing.

Inventors

ZHENG KAI
GAO QIQIANG
LIANG XIAO
JIANG YI
Guo Fengbei
GAO BOWEN

Assignees

大连海事大学

Dates

Publication Date: 20260512
Application Date: 20260410

Claims (7)

1. The water surface unmanned ship cluster collaborative trapping method based on navigation risk constraint is characterized by comprising the following steps of: acquiring position and heading information of a target ship, and establishing a navigation risk model of the target ship; based on the navigation risk model, determining successful conditions of cooperative capturing of the unmanned surface vehicle clusters; Establishing a trapping point optimization model based on the cooperative trapping success condition, and determining the optimal trapping points corresponding to the unmanned vessels on the water surface by adopting an optimization algorithm; calculating the navigation direction of each water surface unmanned ship based on the optimal trapping points, and controlling the water surface unmanned ship clusters to move towards the corresponding optimal trapping points; in the process of capturing, based on the motion state of the target ship at the current moment, dynamically updating the navigation risk model, recalculating the corresponding optimal capturing point and navigation direction, and driving the unmanned water surface vessels which do not reach the optimal capturing point to continuously move until all the unmanned water surface vessels reach the corresponding optimal capturing point, so as to form a cooperative capturing formation for the target ship.
2. The method for collaborative trapping of a water unmanned ship cluster based on voyage risk constraints of claim 1, wherein voyage risk models describing safe voyage areas and risk distribution characteristics around target ships are established, and the voyage risk models are The formula of (2) is: Wherein, the For the location of any point in the area around the target, As the location of the target vessel, Is the heading of the target ship.
3. The water surface unmanned ship cluster cooperative capturing method based on navigation risk constraint of claim 2, wherein the water surface unmanned ship cluster cooperative capturing success condition is that The formula of (2) is: Wherein, the For a set of locations of the area surrounding the target, Is a voyage risk threshold.
4. The method for collaborative trapping of a water surface unmanned ship cluster based on navigation risk constraint according to claim 1, wherein a trapping point optimization model is built by taking a minimum trapping cost as an optimization target, and the trapping point optimization model is The formula of (2) is: Wherein, the In order to capture the cost function in a round, Is a collection of unmanned boats on the water surface, A set of trapping points to satisfy a synergistic trapping success condition.
5. The method for collaborative trapping of the unmanned surface vehicle clusters based on navigation risk constraint according to claim 4, wherein an optimization algorithm is adopted to optimize trapping points, an optimal trapping point corresponding to each unmanned surface vehicle is determined, and the set of the optimal trapping points is determined The formula of (2) is: 。
6. The method for collaborative trapping of a water surface unmanned aerial vehicle cluster based on navigation risk constraint according to claim 1, wherein the navigation direction of each water surface unmanned aerial vehicle is calculated based on the optimal trapping point, and the navigation direction is calculated based on the optimal trapping point The formula of (2) is: Wherein, the Unmanned surface vessel Corresponding optimal trapping points.
7. The water surface unmanned ship cluster collaborative trapping method based on navigation risk constraint according to claim 1 is characterized in that a manual potential field method is adopted to determine the navigation direction of the water surface unmanned ship, and the manual potential field method comprises the steps of calculating the attractive potential field of an optimal trapping point to the water surface unmanned ship, calculating the repulsive potential field of an obstacle to the water surface unmanned ship, superposing the attractive potential field and the repulsive potential field to obtain a total potential field, and calculating the resultant force direction, wherein the resultant force direction is the navigation direction of the water surface unmanned ship.

Description

Navigation risk constraint-based water surface unmanned ship cluster collaborative capturing method Technical Field The invention relates to the technical field of cooperative control and decision-making of a marine unmanned system, in particular to a water surface unmanned ship cluster cooperative capturing method based on navigation risk constraint. Background With the development of ocean development and the development of offshore intelligent equipment technology, unmanned boats on the water surface are increasingly widely applied to tasks such as offshore patrol, target monitoring, cooperative capture, anti-diving operations and the like. In order to improve task execution efficiency and system reliability, a plurality of unmanned water surface vessels commonly work cooperatively in a cluster form, and complex offshore tasks are completed through information sharing and cooperative control. The cooperative trapping task is an important application scene of the unmanned surface vehicle cluster, and aims to restrict the movement space of the target ship under the cooperative action of multiple boats, so that the target is effectively controlled. In the prior art, a plurality of trapping points are preset around a target in cooperation with a trapping task of a water surface unmanned ship cluster, and each water surface unmanned ship reaches a corresponding trapping point to form a trapping structure. Although the method can realize the basic trapping function, the formed trapping formation is single, the positions of trapping points and the diversity of the trapping formation are not fully considered, and the problems of long navigation path, non-optimal trapping track, low cooperative efficiency and the like of the unmanned surface vehicle are easily caused, so that the trapping task completion time is prolonged, and the system energy consumption is increased. In addition, the prior method is difficult to effectively describe the constraint relation of the maneuvering capability of the target ship. Therefore, there is an urgent need for a collaborative capture method for a surface unmanned ship cluster that can describe target vessel maneuverability constraints, optimize capture point positions, and achieve adaptive formation adjustment. Disclosure of Invention In order to solve the problems that the capturing formation is single, the capturing points lack optimization and the target maneuvering constraint is difficult to describe in the prior art, the invention provides a water surface unmanned ship cluster collaborative capturing method based on navigation risk constraint, which specifically comprises the following steps: acquiring position and heading information of a target ship, and establishing a navigation risk model of the target ship; based on the navigation risk model, determining successful conditions of cooperative capturing of the unmanned surface vehicle clusters; Establishing a trapping point optimization model based on the cooperative trapping success condition, and determining the optimal trapping points corresponding to the unmanned vessels on the water surface by adopting an optimization algorithm; calculating the navigation direction of each water surface unmanned ship based on the optimal trapping points, and controlling the water surface unmanned ship clusters to move towards the corresponding optimal trapping points; in the process of capturing, based on the motion state of the target ship at the current moment, dynamically updating the navigation risk model, recalculating the corresponding optimal capturing point and navigation direction, and driving the unmanned water surface vessels which do not reach the optimal capturing point to continuously move until all the unmanned water surface vessels reach the corresponding optimal capturing point, so as to form a cooperative capturing formation for the target ship. Further, a voyage risk model describing a safe voyage area around the target ship and a risk distribution characteristic is established, and the voyage risk modelThe formula of (2) is: Wherein, the For the location of any point in the area around the target,As the location of the target vessel,Is the heading of the target ship. Furthermore, the successful condition of the cooperative capturing of the unmanned surface vehicle clustersThe formula of (2) is: Wherein, the For a set of locations of the area surrounding the target,Is a voyage risk threshold. Further, setting up a trapping point optimization model by taking the minimized trapping cost as an optimization target, wherein the trapping point optimization modelThe formula of (2) is: Wherein, the In order to capture the cost function in a round,Is a collection of unmanned boats on the water surface,A set of trapping points to satisfy a synergistic trapping success condition. Further, an optimization algorithm is adopted to optimize the trapping points, the optimal trapping points corresponding to the unmanned vessel