Multi-unmanned ship cooperative path tracking method and system

Abstract

The invention discloses a multi-unmanned ship cooperative path tracking method and system. The method comprises the following steps: S1, establishing a kinematic model of an unmanned ship based on the position and course of the unmanned ship; s2, calculating a path tangent angle and a tracking error according to the kinematic model; s3, receiving the path parameters of the adjacent unmanned surface vehicle, and calculating the difference value between the actual course and the guidance course of the unmanned surface vehicle and the change rate of the path parameters in combination with the path tangent angle of the unmanned surface vehicle; updating a current path parameter according to the change rate to obtain a real-time path parameter; and S4, based on the tracking error, the unmanned ship kinematic model and the real-time path parameters, defining an LOS guidance law so as to obtain an expected navigation speed and an expected yawing angular speed for controlling the unmanned ship. According to the method, the problem of collaborative consistency in formation path tracking is solved through inter-boat collaborative parameter interaction and a dynamic path updating mechanism, and the tracking precision and robustness of the multi-unmanned-boat system under the complex sea condition are remarkably improved through actual boat verification.

Description

Technical Field

[0001] The present invention relates to the field of autonomous navigation and collaborative control of unmanned boats, and in particular to a collaborative path tracking method and system for multiple unmanned boats. Background Art

[0002] With the rapid development of fields such as marine resource development, environmental monitoring, and military reconnaissance, collaborative operation systems for multiple unmanned vehicles (USVs) have become a research hotspot due to their flexibility, robustness, and efficiency. In such systems, accurate collaborative path tracking is the core foundation for achieving tasks such as formation control, area coverage, and target capture. However, ensuring the synchronization of individual USVs and overall mission reliability during multi-vessel collaborative operations remains an important research topic for existing USV path tracking technologies.

[0003] When performing complex tasks such as large-scale monitoring and multi-target tracking, individual unmanned aerial vehicles (UAVs) face limitations such as limited sensing range and insufficient computing power. Therefore, to address the limitations of single-vessel tracking, multi-vessel collaborative path tracking has become a research hotspot to meet the demands of collaborative operations. The current challenge lies in designing effective collaborative algorithms and validating them on real-world platforms. Summary of the Invention

[0004] The present invention provides a method and system for collaborative path tracking of multiple unmanned boats to overcome the limitations of the above-mentioned single unmanned boat tracking.

[0005] In order to achieve the above object, the technical solution of the present invention is:

[0006] 1. A method for collaborative path tracking of multiple unmanned boats, comprising:

[0007] S11. Construct a kinematic model of the unmanned boat based on its position and heading;

[0008] S12. defining a path tangent angle and a tracking error of the unmanned boat according to the kinematic model of the unmanned boat;

[0009] S13, calculating a steering angle based on the path tangent angle and the tracking error; calculating a difference between the actual heading of the unmanned boat and the steering angle; receiving path information of adjacent unmanned boats and designing path parameter synchronization variables to be designed in combination with the path parameters of the unmanned boat; calculating a change rate of the unmanned boat path parameters based on a reference speed of the unmanned boat and the path parameter synchronization variables to be designed; and updating the current path parameters according to the change rate to obtain real-time path parameters;

[0010] S14. Based on the difference between the actual heading of the unmanned boat and the guidance heading angle, the tracking error, the kinematic model of the unmanned boat, and the real-time path parameters, define the LOS guidance law to obtain the desired navigation speed and desired bow angular velocity of the unmanned boat, which are used to control the unmanned boat to navigate along the guidance trajectory.

[0011] Furthermore, the expression for constructing the kinematic model of the unmanned boat is:

[0012]

[0013] Where, represents the actual navigation speed of the unmanned boat i, ψ is =ψ i +β i Indicates the actual navigation direction of the unmanned boat, β i =arctan2(v i ,u i ) represents the sideslip angle of the unmanned boat, r i Indicates the bow angular velocity of the unmanned boat.

[0014] Furthermore, the expression for defining the path tangent angle is:

[0015]

[0016] Where, α i represents the path parameter of unmanned boat i;

[0017] The expression defining the tracking error is:

[0018]

[0019] Where, e ix represents the longitudinal tracking error; e iy represents the horizontal line tracking error; T represents transpose.

[0020] Furthermore, the step S13 specifically includes:

[0021] S131. Calculate the steering angle based on the path tangent angle and the tracking error. The calculation expression is:

[0022]

[0023] Where, Δ i Indicates the forward sight distance;

[0024] S132: Calculate the difference between the actual heading of the unmanned boat and the guidance heading angle, and the calculation expression is:

[0025] e iψ =ψ is-ψ iL os (5)

[0026] S133, receiving the path information of the adjacent unmanned boat and combining it with the path parameters of the unmanned boat, designing the path parameter synchronization variables to be designed, the expression of which is:

[0027]

[0028] Where, is a constant; α j is the path parameter of the adjacent unmanned boat j; a ij It is an element of the adjacency matrix of the UAV communication topology diagram;

[0029] Among them, the element a of the adjacent matrix of the unmanned boat communication topology diagram is ij The definition process is: use an undirected graph G = {V, E} to describe the internal communication between unmanned boats, where V = {v1, v2, ..., v N} is the vertex set of graph G, is the edge set of graph G; the adjacency matrix of graph G is defined as A={a ij} N×N ;

[0030] S134. Calculate the rate of change of the unmanned boat path parameter according to the unmanned boat reference speed and the path parameter synchronization variable to be designed. The calculation expression is:

[0031]

[0032] Where, represents the rate of change of the path parameters of the unmanned boat i; v c Indicates the reference speed of the unmanned boat, which is set manually according to mission requirements or design goals;

[0033] S135. Update the current path parameter according to the change rate, which is expressed as:

[0034]

[0035] Where a i (t) represents the real-time path parameter of the unmanned boat i; t represents time; dt represents the time increment.

[0036] Furthermore, the expression for defining the LOS guidance law is:

[0037]

[0038] Where U iLos represents the expected sailing speed; r iLos represents the desired yaw angular velocity; is a constant; where

[0039] The present invention also provides a multi-unmanned boat collaborative path tracking system, comprising:

[0040] An unmanned boat self-organizing network consisting of multiple unmanned boat platforms and wireless bridges; the multiple unmanned boat platforms are composed of multiple unmanned boats, each of which includes: a main control unit, a flight control module, a wireless bridge and wireless data transmission module, a sensor module, and a power and energy module;

[0041] The sensor module is connected to the flight control module and is used to collect status information of the unmanned boat and transmit it to the flight control module;

[0042] The flight control module is also connected to the main control unit and the power and energy module, and is used to transmit the status information of the unmanned boat to the main control unit, and is also used to receive the control instructions of the main control unit and convert the control instructions into PWM signals and transmit them to the power and energy module;

[0043] The main control unit is connected to the wireless bridge and the wireless data transmission module, and the main control unit generates a control instruction based on the multi-unmanned boat collaborative path tracking method;

[0044] The wireless bridge and the wireless data transmission module are also connected to other unmanned boats through a wireless network, and are used to transmit the status information of other unmanned boats to the main control unit of the unmanned boat; at the same time, the status information of the unmanned boat is transmitted to other unmanned boats;

[0045] The power and energy module receives the PWM signal, and is used to execute the PWM signal and drive the unmanned boat to move forward along the guidance trajectory.

[0046] Beneficial effects:

[0047] This method uses a parameter synchronization mechanism based on the path information of neighboring unmanned vehicles to update the unmanned vehicle path parameters in real time. Combined with LOS guidance, it generates precise desired navigation speed and desired bow angular velocity, enabling the unmanned vehicles to follow the guided trajectory. This significantly reduces path tracking errors during the coordinated operation of multiple unmanned vehicles and ensures the consistency of the formation's trajectory. Simultaneous testing in both simulated and real-world environments objectively quantifies the method's actual performance in complex scenarios, verifying its practicality and effectiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0049] Figure 1 This is a flow chart of the multi-unmanned collaborative path tracking method of the present invention;

[0050] Figure 2 This is a schematic diagram of the collaborative path tracking of multiple unmanned boats in the present invention;

[0051] Figure 3 This is a framework diagram of the collaborative path tracking of multiple unmanned boats in the present invention;

[0052] Figure 4 This is a hardware architecture diagram of the unmanned boat of the present invention;

[0053] Figure 5 The communication topology diagram of the unmanned boat of the present invention;

[0054] Figure 6 It is the unmanned boat cluster monitoring platform of the present invention;

[0055] Figure 7 It is the virtual machine simulation platform of the present invention;

[0056] FIG8 is the result of simulation test case 1 of the present invention;

[0057] Figure 8a This is the tracking path of the unmanned boat in simulation test case 1 of the present invention;

[0058] Figure 8b The collaborative path parameters of the unmanned boat in the simulation test case 1 of the present invention;

[0059] Figure 8c The speed of the unmanned boat in simulation test case 1 of the present invention;

[0060] Figure 8d This is the lateral tracking error of the unmanned boat in the simulation test case 1 of the present invention;

[0061] Figure 8e This is the longitudinal tracking error of the unmanned boat in the simulation test case 1 of the present invention;

[0062] Figure 8f This is the heading tracking error of the unmanned boat in the simulation test case 1 of the present invention;

[0063] FIG9 is the result of simulation test case 2 of the present invention;

[0064] Figure 9a This is the tracking path of the unmanned boat in simulation test case 2 of the present invention;

[0065] Figure 9b The collaborative path parameters of the unmanned boat in simulation test case 2 of the present invention;

[0066] Figure 9c The speed of the unmanned boat in simulation test case 2 of the present invention;

[0067] Figure 9d This is the lateral tracking error of the unmanned boat in the simulation test case 2 of the present invention;

[0068] Figure 9e This is the longitudinal tracking error of the unmanned boat in simulation test case 2 of the present invention;

[0069] Figure 9f This is the heading tracking error of the unmanned boat in simulation test case 2 of the present invention;

[0070] FIG10 is a test result of a multi-unmanned boat collaborative path tracking on a real ship according to the present invention;

[0071] Figure 10a The tracking path of the unmanned boat based on the actual ship test results of the present invention;

[0072] Figure 10b The collaborative path parameters of the unmanned boat based on the actual ship test results of the present invention;

[0073] Figure 10c The speed of the unmanned boat is the result of the actual ship test of the present invention;

[0074] Figure 10d The lateral tracking error of the unmanned boat is the result of the actual ship test of the present invention;

[0075] Figure 10e The longitudinal tracking error of the unmanned boat is the result of the actual ship test of the present invention;

[0076] Figure 10f The heading tracking error of the unmanned boat is the result of the actual ship test of the present invention. DETAILED DESCRIPTION

[0077] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of 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. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0078] This embodiment provides a method for collaborative path tracking of multiple unmanned boats. Figure 1 As shown, including:

[0079] S11. Construct a kinematic model of the unmanned boat based on its position and heading;

[0080] S12. defining a path tangent angle and a tracking error of the unmanned boat according to the kinematic model of the unmanned boat;

[0081] S13, calculating a steering angle based on the path tangent angle and the tracking error; calculating a difference between the actual heading of the unmanned boat and the steering angle; receiving path information of adjacent unmanned boats and designing path parameter synchronization variables to be designed in combination with the path parameters of the unmanned boat; calculating a change rate of the unmanned boat path parameters based on a reference speed of the unmanned boat and the path parameter synchronization variables to be designed; and updating the current path parameters according to the change rate to obtain real-time path parameters;

[0082] S14. Based on the difference between the actual heading of the unmanned boat and the guidance heading angle, the tracking error, the kinematic model of the unmanned boat, and the real-time path parameters, define the LOS guidance law to obtain the desired navigation speed and desired bow angular velocity of the unmanned boat, which are used to control the unmanned boat to navigate along the guidance trajectory.

[0083] Specifically, first, a kinematic model of the unmanned boat is constructed based on the position and heading of the unmanned boat; according to the kinematic model, the path tangent angle and tracking error are established to quantify the position deviation of the boat body relative to the reference path; secondly, the guidance heading angle is calculated based on the path tangent angle and the tracking error, and the difference is calculated in combination with the actual heading; at the same time, the path parameters are designed to synchronize the variables to be designed, and the path information of neighboring unmanned boats is integrated. The path parameter change rate is generated through distributed computing to drive the dynamic update of the real-time path parameters; thirdly, based on the difference, tracking error, kinematic model and real-time path parameters, a distributed LOS guidance law is constructed to solve the expected navigation speed and bow angular velocity instructions in real time to realize collaborative path tracking of multiple boats under dynamic parameters.

[0084] Specifically, the expression for constructing the unmanned boat kinematic model is:

[0085]

[0086] Where, represents the actual navigation speed of the unmanned boat i, ψ is =ψ i +β i Indicates the actual navigation direction of the unmanned boat, β i =arctan2(v i ,u i ) represents the sideslip angle of the unmanned boat, r i Indicates the bow angular velocity of the unmanned boat.

[0087] Specifically, such as Figure 2 As shown, the expression for defining the path tangent angle is:

[0088]

[0089] Where, α irepresents the path parameters of the unmanned boat i, where the path parameters include: speed and heading;

[0090] The expression defining the tracking error is:

[0091]

[0092] Where, e ix represents the longitudinal tracking error; e iy represents the horizontal line tracking error; T represents transpose.

[0093] Specifically, to achieve collaborative path tracking for multiple UAVs and ensure operational synchronization, a path parameter update law was designed. The core function of this path parameter update law is to dynamically calculate the rate of change of each UAV's path parameter based on the state of each UAV and its collaborative information with neighboring UAVs. The path parameter is then updated based on the rate of change. The steps involved include:

[0094] S131. Calculate the steering angle based on the path tangent angle and the tracking error. The calculation expression is:

[0095]

[0096] Where, Δ i Indicates the forward sight distance;

[0097] S132: Calculate the difference between the actual heading of the unmanned boat and the guidance heading angle, and the calculation expression is:

[0098] e iψ =ψ is -ψ iL os (5)

[0099] S133, receiving the path information of the adjacent unmanned boat and combining it with the path parameters of the unmanned boat, designing the path parameter synchronization variables to be designed, the expression of which is:

[0100]

[0101] Where, is a constant; α j is the path parameter of the adjacent unmanned boat j; a ij It is an element of the adjacency matrix of the UAV communication topology diagram;

[0102] Among them, the communication topology of the unmanned boat is as follows: Figure 5 As shown in the figure, 1 is the local unmanned boat, 2 and 3 are neighboring unmanned boats; the element a of the adjacent matrix of the unmanned boat communication topology diagram is ij The definition process is: use an undirected graph G = {V, E} to describe the internal communication between unmanned boats, where V = {v1, v2, ..., vN} is the vertex set of graph G, is the edge set of graph G; the adjacency matrix of graph G is defined as A={a ij} N×N ;

[0103] S134. Calculate the rate of change of the unmanned boat path parameter according to the unmanned boat reference speed and the path parameter synchronization variable to be designed. The calculation expression is:

[0104]

[0105] Where, represents the rate of change of the path parameters of the unmanned boat i; v c Indicates the reference speed of the unmanned boat, which is set manually according to mission requirements or design goals;

[0106] S135. Update the current path parameter according to the change rate, which is expressed as:

[0107]

[0108] Where a i (t) represents the real-time path parameter of the unmanned boat i; t represents time; dt represents the time increment.

[0109] Specifically, the unmanned boat adopts the following guidance law to obtain the desired navigation speed and bow angular velocity, and the expression of the LOS guidance law is defined as:

[0110]

[0111] Where U iLos represents the expected sailing speed; r iLos represents the desired yaw angular velocity; is a constant; where This formula supports the convergence and stability analysis of the adopted LOS guidance law, ensuring that the USV can stably converge and track the predetermined path when its heading is precisely controlled.

[0112] like Figure 3 、 4 As shown, this embodiment also provides a multi-unmanned boat collaborative path tracking system, including:

[0113] An unmanned boat self-organizing network consisting of multiple unmanned boat platforms and wireless bridges; the multiple unmanned boat platforms are composed of multiple unmanned boats, each of which includes: a main control unit, a flight control module, a wireless bridge and wireless data transmission module, a sensor module, and a power and energy module;

[0114] The sensor module is connected to the flight control module and is used to collect status information of the unmanned boat and transmit it to the flight control module;

[0115] The flight control module is also connected to the main control unit and the power and energy module, and is used to transmit the status information of the unmanned boat to the main control unit, and is also used to receive the control instructions of the main control unit and convert the control instructions into PWM signals and transmit them to the power and energy module;

[0116] The main control unit is connected to the wireless bridge and the wireless data transmission module, and the main control unit generates a control instruction based on the multi-unmanned boat collaborative path tracking method;

[0117] The wireless bridge and the wireless data transmission module are also connected to other unmanned boats through a wireless network, and are used to transmit the status information of other unmanned boats to the main control unit of the unmanned boat; at the same time, the status information of the unmanned boat is transmitted to other unmanned boats;

[0118] The power and energy module receives the PWM signal, and is used to execute the PWM signal and drive the unmanned boat to move forward along the guidance trajectory.

[0119] In this embodiment, the main control unit is a Raspberry Pi 4B; the flight control module is Pixhawk 2.4.8; the sensor module includes GPS and IMU; the sensor module and the power and energy module include: brushless ESC, brushless motor, 6S lithium battery and voltage converter.

[0120] Specifically, the operation process of the main control unit is as follows:

[0121] Communicate with the flight control module via the MAVLink protocol to obtain the status information of the unmanned boat;

[0122] Exchange path parameter information with other unmanned boats through wireless bridges to calculate path parameters;

[0123] Based on the operation of Python 3.8, the calculation of the collaborative path tracking method of multiple unmanned boats is realized to obtain the expected sailing speed and expected bow angular velocity;

[0124] Serial communication is performed with the flight control module via the MAVLink protocol, and the desired navigation speed and the desired yaw angular velocity are output to the flight control module.

[0125] Specifically, the operation process of the flight control module is as follows:

[0126] Receive data from sensor modules and fuse them, and estimate the attitude and position of the fused data;

[0127] Receive instructions from the main control unit through the MAVLink protocol;

[0128] The Rover firmware running ArduPilot converts the instructions into PWM signals through the underlying control algorithm to drive the motors and servos, thus achieving dynamic control of the unmanned boat.

[0129] In this embodiment, the multi-unmanned boat collaborative path tracking method is verified through a virtual environment and a real environment.

[0130] Specifically, in a virtual environment, three virtual unmanned boats were set up and verified using the SITL simulation environment of ArduPilot; the behavior of the unmanned boats was simulated on an Ubuntu virtual machine, the Rover firmware simulated the Pixhawk flight control, and Python was run in the virtual machine to simulate the Raspberry Pi function to implement the execution of the multi-unmanned boat collaborative path tracking method; the unmanned boat cluster monitoring platform used for monitoring was as follows: Figure 6 As shown, the virtual machine simulation platform is as follows Figure 7 shown.

[0131] In simulation test case 1, the parameter is set to v c =0.5, Δ ix =1,Δ iψ =0.1, Δ i =2.5, b ix =1, b iψ =1 and k i =1. The simulation test results are shown in Figure 8. Figure 8a It shows that the unmanned boat can track the path well, with the maximum error not exceeding 0.13 meters; Figure 8b It shows that the path parameters change with time with high consistency, achieving synchronization; Figure 8c It shows that the speed of the unmanned boat is stable at around 0.5 m / s; Figures 8d to 8f It shows that the lateral, longitudinal and heading tracking errors of the unmanned boat eventually oscillate around 0.

[0132] In simulation test case 2, the parameter is set to v c =1,Δ ix =1,Δ iψ =0.35,Δ i =3,b ix =1,b iψ =1 and k i =1. The simulation test results are shown in Figure 9. Figure 9a It shows that the tracking path of the unmanned boat basically coincides with the planned path; Figure 9b Quantification of path parameter synchrony is shown; Figure 9c It shows that the speed of the unmanned boat is stable at around 1 meter per second; Figures 9d to 9f It shows that the lateral, longitudinal and heading tracking errors of the unmanned boat oscillate within an acceptable range and eventually converge.

[0133] Specifically, three unmanned boat physical platforms were built in a real environment, and the experimental site was located at Lingshui Port of Dalian Maritime University.

[0134] In the actual ship test, the parameters set are the same as those in the simulation test case 1; the actual ship test results are shown in Figure 10. Figure 10a It shows that the unmanned boat can effectively track the planned path; Figure 10b It shows that the path parameters of the unmanned boats are basically consistent and have good synchronization; Figure 10c It shows that the speed of the unmanned boat oscillates between 0.1 and 1.1 m / s; Figure 10d 、 10e It shows that the horizontal and vertical tracking errors oscillate around 0 after a large fluctuation in the initial stage; Figure 10f It shows that the heading tracking error oscillates between -50° and 50°.

[0135] The oscillations that occurred during the above tests were caused by the Pixhawk parameter tuning steps, environmental interference, data transmission delays, and sensor noise.

[0136] The present invention has the following beneficial effects:

[0137] This method uses a parameter synchronization mechanism based on the path information of neighboring unmanned vehicles to update the unmanned vehicle path parameters in real time. Combined with LOS guidance, it generates precise desired navigation speed and desired bow angular velocity, enabling the unmanned vehicles to follow the guided trajectory. This significantly reduces path tracking errors during the coordinated operation of multiple unmanned vehicles and ensures the consistency of the formation's trajectory. Simultaneous testing in both simulated and real-world environments objectively quantifies the method's actual performance in complex scenarios, verifying its practicality and effectiveness.

[0138] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements 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 path tracking of multiple unmanned boats, characterized in that: include: S11. Construct a kinematic model of the unmanned boat based on its position and heading; S12. defining a path tangent angle and a tracking error of the unmanned boat according to the kinematic model of the unmanned boat; S13, calculating a navigation heading angle based on the path tangent angle and the tracking error; Calculating the difference between the actual heading of the unmanned boat and the guidance heading angle; Receive path information of adjacent unmanned boats and design the path parameter synchronization variables to be designed in combination with the path parameters of the unmanned boats; calculate the rate of change of the path parameters of the unmanned boats according to the reference speed of the unmanned boats and the path parameter synchronization variables to be designed; updating the current path parameters according to the change rate to obtain real-time path parameters; S14. Based on the difference between the actual heading of the unmanned boat and the guidance heading angle, the tracking error, the kinematic model of the unmanned boat, and the real-time path parameters, define the LOS guidance law to obtain the desired navigation speed and desired bow angular velocity of the unmanned boat, which are used to control the unmanned boat to navigate along the guidance trajectory.

2. The method for collaborative path tracking of multiple unmanned boats according to claim 1, characterized in that: The expression for constructing the kinematic model of the unmanned boat is: Where, represents the actual navigation speed of the unmanned boat i, ψ is =ψ i +β i Indicates the actual navigation direction of the unmanned boat, β i =arctan2(v i ,u i ) represents the sideslip angle of the unmanned boat, r i Indicates the bow angular velocity of the unmanned boat.

3. The method for collaborative path tracking of multiple unmanned boats according to claim 1, characterized in that ； The expression defining the path tangent angle is: Where, α i represents the path parameter of unmanned boat i; The expression defining the tracking error is: Where, e ix represents the longitudinal tracking error; e iy represents the horizontal line tracking error; T represents transpose.

4. The method for collaborative path tracking of multiple unmanned boats according to claim 1, characterized in that: The step S13 specifically includes: S131. Calculate the steering angle based on the path tangent angle and the tracking error. The calculation expression is: Where, Δ i Indicates the forward sight distance; S132: Calculate the difference between the actual heading of the unmanned boat and the guidance heading angle, and the calculation expression is: e iψ =ψ is -ψ iLos (5) S133, receiving the path information of the adjacent unmanned boat and combining it with the path parameters of the unmanned boat, designing the path parameter synchronization variables to be designed, the expression of which is: Where, is a constant; α j is the path parameter of the adjacent unmanned boat j; a ij It is an element of the adjacency matrix of the UAV communication topology diagram; Among them, the element a of the adjacent matrix of the unmanned boat communication topology diagram is ij The definition process is: use an undirected graph G = {V, E} to describe the internal communication between unmanned boats, where V = {v1, v2, ..., v N } is the vertex set of graph G, is the edge set of graph G; the adjacency matrix of graph G is defined as A={a ij } N×N ; S134. Calculate the rate of change of the unmanned boat path parameter according to the unmanned boat reference speed and the path parameter synchronization variable to be designed. The calculation expression is: Where, represents the rate of change of the path parameters of the unmanned boat i; v c Indicates the reference speed of the unmanned boat, which is set manually according to mission requirements or design goals; S135. Update the current path parameter according to the change rate, which is expressed as: Where a i (t) represents the real-time path parameter of the unmanned boat i; t represents time; dt represents the time increment.

5. The method for collaborative path tracking and actual ship verification of multiple unmanned boats according to claim 1, characterized in that: The expression defining the LOS guidance law is: Where U iLos represents the expected sailing speed; r iLos represents the desired yaw angular velocity; is a constant; where 6. A multi-unmanned boat collaborative path tracking system, characterized in that: include: An unmanned boat self-organizing network consisting of multiple unmanned boat platforms and wireless bridges; The multi-unmanned boat platform is composed of multiple unmanned boats, each of which includes: a main control unit, a flight control module, a wireless bridge and wireless data transmission module, a sensor module, and a power and energy module; The sensor module is connected to the flight control module and is used to collect status information of the unmanned boat and transmit it to the flight control module; The flight control module is also connected to the main control unit and the power and energy module, and is used to transmit the status information of the unmanned boat to the main control unit, and is also used to receive the control instructions of the main control unit and convert the control instructions into PWM signals and transmit them to the power and energy module; The main control unit is connected to the wireless bridge and the wireless data transmission module, and the main control unit generates a control instruction based on the method according to any one of claims 1 to 5; The wireless bridge and the wireless data transmission module are also connected to other unmanned boats through a wireless network, and are used to transmit the status information of other unmanned boats to the main control unit of the unmanned boat; at the same time, the status information of the unmanned boat is transmitted to other unmanned boats; The power and energy module receives the PWM signal, and is used to execute the PWM signal and drive the unmanned boat to move forward along the guidance trajectory.

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