A collaborative control method for unmanned boat swarm based on virtual-real integration

Abstract

The present invention discloses a method for collaborative control of an unmanned boat cluster based on a combination of virtual and real, establishing an unmanned boat cluster formation in a virtual ocean environment, and obtaining the actual speed and actual heading angle of the physical ship and the digitally simulated unmanned boat at the next moment through the mapping position, mapping speed, and mapping heading angle of the real boat in the virtual ocean environment, as well as the virtual position, virtual speed, and virtual heading angle of the digitally simulated virtual unmanned boat in the virtual ocean environment, based on a cluster collaborative control algorithm. By combining the actual unmanned boat with the virtual digitally simulated unmanned boat, the present invention can provide highly reliable physical feedback and immersive interactive experience in complex and changing scenarios. The error between the simulation results and the actual operating conditions is small, which greatly improves the accuracy and efficiency of the algorithm verification, thereby providing important support for the development of unmanned boat cluster collaborative technology and meeting its diverse application needs in complex environments.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned boat cluster collaboration, and in particular to an unmanned boat cluster collaboration control method based on virtual-real integration. Background Art

[0002] In the field of unmanned watercraft technology research, the verification of unmanned autonomous algorithms is a key link in promoting its technological development. Current verification methods mainly include two forms: real-world boat testing at sea and simulation scenario verification. However, both methods face significant challenges in practical application. Although offshore unmanned watercraft swarm testing can provide real-world environmental feedback, its implementation cost is high and consumes a lot of time, manpower, and material resources. At the same time, due to the limitations of scenario conditions, it is difficult to build a diverse and complex test environment, which greatly restricts the development and verification of autonomous algorithms. Although simulation scenario verification has attracted much attention due to its low cost and high flexibility, existing simulation tools cannot meet the needs of performance evaluation in complex environments, and the problems of insufficient realism and credibility are particularly prominent. At the same time, traditional simulation environments often cannot provide real physical feedback and lack an intuitive user interaction experience, resulting in large errors between simulation results and actual operation. Summary of the Invention

[0003] The present invention discloses a collaborative control method for an unmanned boat cluster based on a combination of virtual and real, in order to overcome the above technical problems.

[0004] In order to achieve the above object, the technical solution of the present invention is:

[0005] A collaborative control method for an unmanned boat swarm based on virtual-real integration includes the following steps:

[0006] S1: Establish a three-dimensional visual simulation virtual space model and obtain an initialized virtual ocean environment;

[0007] S2: establishing an unmanned boat swarm formation in the initialized virtual ocean environment, where the unmanned boats in the unmanned boat swarm formation include mapping boats of real boats or digital simulation unmanned boats;

[0008] S3: establishing a numerical simulation motion model of the unmanned boat; and obtaining the mapped position, mapped speed, and mapped heading angle of the real boat in the virtual ocean environment at the current moment according to the actual position, actual speed, and actual heading angle of the physical ship sailing at sea at the current moment;

[0009] S4: Based on the mapped position, mapped speed, and mapped heading angle of the real boat in the virtual ocean environment at the current moment, and the virtual position, virtual speed, and virtual heading angle of the digital simulated virtual unmanned boat in the virtual ocean environment at the current moment, obtaining, based on a cluster collaborative control algorithm, an expected mapped speed and expected mapped heading angle of the real boat in the virtual ocean environment at the next moment, and an expected virtual speed and expected virtual heading angle of the digital simulated unmanned boat at the next moment;

[0010] S5: obtaining the actual speed and actual heading angle of the physical ship at the next moment according to the expected mapping speed and expected mapping heading angle of the mapping boat of the real ship in the virtual ocean environment at the next moment;

[0011] According to the expected virtual speed and expected virtual heading angle of the digital simulation unmanned boat at the next moment, the actual virtual speed and actual virtual heading angle of the digital simulation unmanned boat at the next moment are obtained;

[0012] S6: According to the actual speed, actual heading angle and actual position of the physical ship at the next moment, obtain the mapping speed, mapping heading angle and mapping position of the mapping boat of the real boat in the virtual ocean environment at the next moment; repeat S4-S5 according to the actual virtual speed, actual virtual heading angle and actual virtual position of the digital simulated unmanned boat at the next moment; so as to realize the coordinated control of the unmanned boat cluster based on the combination of virtual and real, and then realize the control of the physical ship sailing at sea.

[0013] Furthermore, the steps of the cluster collaborative control algorithm are as follows:

[0014] S41: Based on the position of the set reference virtual center point in the virtual ocean environment, the position of the target virtual point of the unmanned boat in the unmanned boat cluster formation is obtained;

[0015] S42: obtaining the expected speed and expected heading angle of the unmanned boats in the unmanned boat cluster formation at the next moment in the virtual ocean environment according to the positions of the target virtual points of the unmanned boats;

[0016] S43. According to the expected speed and expected heading angle of the unmanned boats in the unmanned boat cluster formation in the virtual ocean environment at the next moment, obtain the expected mapping speed and expected mapping heading angle of the mapping boat of the real boat in the virtual ocean environment at the next moment, as well as the expected speed and expected heading angle of the digital simulation unmanned boat model at the next moment.

[0017] Furthermore, the formula used to obtain the position of the target virtual point of the unmanned boat in the unmanned boat cluster formation is as follows:

[0018]

[0019] Where: represents the position of the target virtual point of the i-th unmanned boat; P l Indicates the position of the reference virtual center point, R(ψ l ) represents the transformation matrix from the local coordinate system to the earth coordinate system; ψ l Indicates the heading angle of the reference virtual center point; d i represents the relative distance between the i-th virtual center point and the reference virtual point; θ i Indicates the relative angle between the virtual center point and the reference virtual point; x i l ,y i l They represent the X-axis coordinate and Y-axis coordinate of the target virtual point of the i-th unmanned boat in the geodetic coordinate system respectively.

[0020] Furthermore, the formula used to obtain the expected speed and expected heading angle of the unmanned boats in the unmanned boat cluster formation at the next moment in the virtual ocean environment is as follows:

[0021]

[0022] Where: is the expected speed of the i-th unmanned boat in the virtual ocean environment at the next moment; k p Indicates the position difference compensation parameter; Indicates the distance between the unmanned boat and the target virtual point; is the speed of the target virtual point of the i-th unmanned boat; k d represents the rate balance parameter; u i represents the actual speed of the i-th unmanned boat; Δψ represents the angle deviation; represents the azimuth between the unmanned boat and the target virtual point; x i l ,y i l They represent the horizontal and vertical coordinates of the target virtual point of the i-th unmanned boat in the virtual ocean environment; i ,y i They represent the horizontal and vertical coordinates of the position of the i-th unmanned boat in the virtual ocean environment; ψ i represents the actual heading angle of the i-th unmanned boat at the current moment; represents the expected heading angle of the i-th unmanned vehicle in the virtual ocean environment at the next moment; sign(·) represents the sign function; r max represents the maximum turning angle of the unmanned boat; |·| represents absolute value operation.

[0023] Furthermore, the motion model of the digital simulation unmanned boat model is expressed as follows:

[0024]

[0025] Where: η represents the position and attitude vector of the digital simulation unmanned boat, where η=[α,β,γ,φ,θ,ψ] T , α represents the longitudinal position of the digital simulation unmanned boat, β represents the lateral position of the digital simulation unmanned boat, γ represents the vertical position of the digital simulation unmanned boat, φ represents the roll angle of the digital simulation unmanned boat, θ represents the longitudinal tilt angle of the digital simulation unmanned boat, ψ represents the bow phase angle of the digital simulation unmanned boat, represents the first-order differential; R(η) represents the rotation matrix; ξ represents the velocity vector of the digital simulation unmanned boat, where ξ=[u,v,w,p,q,r] T , u represents the longitudinal velocity of the digital simulation unmanned boat, v represents the lateral velocity of the digital simulation unmanned boat, w represents the vertical velocity of the digital simulation unmanned boat, p represents the longitudinal angular velocity of the digital simulation unmanned boat, q represents the lateral angular velocity of the digital simulation unmanned boat, and r represents the vertical angular velocity of the digital simulation unmanned boat; M represents the inertia matrix; C(ξ) represents the Coriolis centripetal force matrix; D(ξ) represents the fluid damping matrix; g(η) represents the restoring force matrix of the digital simulation unmanned boat model itself; τ represents the control input matrix of the digital simulation unmanned boat, where τ=[τ u , τ v , τ w , τ p , τ q , τ q ] T , τ u represents the longitudinal force acting on the digital simulation unmanned boat; τ v represents the lateral force acting on the digital simulation unmanned boat; τ w represents the vertical force acting on the digital simulation unmanned boat; τ p represents the moment acting on the rolling of the digital simulation unmanned boat; τ q represents the moment acting on the pitching of the digital simulation unmanned boat; τ q Indicates the moment acting on the bow of the digital simulation unmanned boat;

[0026] The motion model of the digital simulation unmanned boat model is simplified and expressed as follows:

[0027]

[0028] Where: m 11 Indicates the longitudinal inertia coefficient of the digital simulation unmanned boat; m 22 Indicates the lateral inertia coefficient of the digital simulation unmanned boat; m 33 Indicates the vertical inertia coefficient of the digital simulation unmanned boat; d 11 Represents the linear damping coefficient of the longitudinal motion of the digital simulation unmanned boat; d 22Represents the linear damping coefficient of the lateral motion of the digital simulation unmanned boat; d 33 Represents the rotational damping coefficient of the vertical rotation of the digital simulation unmanned boat.

[0029] Furthermore, the unmanned boat cluster formation adopts a triangular cluster formation.

[0030] Furthermore, the method for obtaining the outline of the unmanned boats in the unmanned boat cluster formation is:

[0031] According to the outline of the physical ship, 3D Max software is used to proportionally reduce the size of the physical ship and then perform three-dimensional modeling.

[0032] Beneficial effect: The present invention provides a collaborative control method for unmanned boat clusters based on the combination of virtual and real. By establishing an unmanned boat cluster formation including a mapping boat of a real boat and a digitally simulated unmanned boat in a virtual ocean environment, the mapping position, mapping speed and mapping heading angle of the mapping boat of the real boat at the current moment in the virtual ocean environment are obtained according to the actual position, actual speed and actual heading angle of the physical ship sailing on the sea at the current moment; and then, based on the virtual position, virtual speed and virtual heading angle of the digitally simulated virtual unmanned boat at the current moment in the virtual ocean environment, the expected mapping speed and expected mapping heading angle of the mapping boat of the real boat at the next moment and the expected virtual speed and expected virtual heading angle of the digitally simulated unmanned boat at the next moment are obtained based on the cluster collaborative control algorithm; and then the actual speed and actual heading angle of the physical ship and the digitally simulated unmanned boat at the next moment can be obtained; based on the cluster collaborative control algorithm, the control of the physical ship is continuously achieved by controlling the unmanned boat cluster. By combining actual unmanned boats with virtual digital simulation unmanned boats, the present invention can provide highly reliable physical feedback and immersive interactive experience in complex and changing scenarios. The simulation results have little error compared with the actual operating conditions, which not only verifies the computational effect of the cluster collaborative control algorithm of the present invention, but also provides important support for the development of unmanned boat cluster collaborative technology and meets its diverse application needs in complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] 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.

[0034] Figure 1 This is a flow chart of the collaborative control method of unmanned boat swarm based on virtual-real combination of the present invention;

[0035] Figure 2 This is a schematic diagram of the results of a virtual-reality combination experiment at sea according to an embodiment of the present invention. The left side is the virtual environment display interface, and the right side is the drone aerial photography interface.

[0036] Figure 3 This is a schematic diagram of the structure of a physical unmanned boat built autonomously in an embodiment of the present invention;

[0037] Figure 4a This is a left view of a digitally simulated unmanned boat in the Unity3D visual simulation environment in an embodiment of the present invention;

[0038] Figure 4b A top view of a digitally simulated unmanned boat in a Unity3D visual simulation environment in an embodiment of the present invention;

[0039] Figure 5 Schematic diagram of the calculation process of the digital simulation unmanned boat motion model in an embodiment of the present invention;

[0040] Figure 6 Schematic diagram of a simulated water body in a Unity3D visual simulation environment in an embodiment of the present invention;

[0041] Figure 7 Schematic diagram of the trajectory of the results of the virtual-real combined experiment at sea in an embodiment of the present invention;

[0042] Figure 8a Schematic diagram of the speed of three physical unmanned boats according to the results of the virtual-real combined experiment at sea in an embodiment of the present invention;

[0043] Figure 8b Schematic diagram of the speed of three digitally simulated unmanned boats according to the results of the virtual-real combined experiment at sea in an embodiment of the present invention;

[0044] Figure 9a Schematic diagram of three physical unmanned boat heading angles according to the results of a virtual-real combined experiment at sea in an embodiment of the present invention;

[0045] Figure 9b Schematic diagram of three digitally simulated unmanned boat heading angles according to the results of a virtual-real combined experiment at sea in an embodiment of the present invention;

[0046] Figure 10 The figure is a flow chart of a collaborative control method for a swarm of unmanned boats based on the combination of virtual and real in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] 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.

[0048] This embodiment introduces a method for cooperative control of a swarm of unmanned boats based on virtual and real integration, including the following steps: Figure 1 and Figure 10 As shown:

[0049] S1: Establish a three-dimensional visual simulation virtual space model and obtain an initialized virtual ocean environment;

[0050] S2: establishing an unmanned boat swarm formation in the initialized virtual ocean environment, where the unmanned boats in the unmanned boat swarm formation are mapped boats of real boats or digitally simulated unmanned boats;

[0051] Specifically, the unmanned boat swarm formation of this embodiment includes a plurality of mapping boat models of real boats and a plurality of digital simulation unmanned boat models, so as to establish an unmanned boat swarm formation in the virtual ocean environment;

[0052] Preferably, the unmanned boat cluster formation adopts a triangular cluster formation.

[0053] Preferably, the method for obtaining the outline of the unmanned boats in the unmanned boat cluster formation is:

[0054] According to the outline of the physical ship, 3D Max software is used to proportionally reduce the size of the physical ship and then perform three-dimensional modeling.

[0055] Specifically, let the geometric parameters of a physical ship sailing on the sea be length L r 、Width W r , high H r , the length of the unmanned boat in the unmanned boat cluster formation is L v , width is W v 、High is H v , the scaling factor is λ∈(0,1), then its three-dimensional vertex coordinate transformation can be expressed as:

[0056]

[0057] S3: Establishing a numerical simulation motion model of the unmanned boat; and obtaining the mapped position, mapped speed, and mapped heading angle of the real boat in the virtual ocean environment at the current moment according to the actual position, actual speed, and actual heading angle of the physical ship sailing at sea at the current moment;

[0058] Preferably, the motion model of the digital simulation unmanned boat model is expressed as follows:

[0059]

[0060] Where: η represents the position and attitude vector of the digital simulation unmanned boat, where η = [α, β, γ, φ, θ, ψ] T , α represents the longitudinal position of the digital simulation unmanned boat, β represents the lateral position of the digital simulation unmanned boat, γ represents the vertical position of the digital simulation unmanned boat, φ represents the roll angle of the digital simulation unmanned boat, θ represents the longitudinal tilt angle of the digital simulation unmanned boat, ψ represents the bow phase angle of the digital simulation unmanned boat, represents the first-order differential; R(η) represents the rotation matrix; ξ represents the velocity vector of the digital simulation unmanned boat, where ξ=[u,v,w,p,q,r] T , u represents the longitudinal velocity of the digital simulation unmanned boat, v represents the lateral velocity of the digital simulation unmanned boat, w represents the vertical velocity of the digital simulation unmanned boat, p represents the longitudinal angular velocity of the digital simulation unmanned boat, q represents the lateral angular velocity of the digital simulation unmanned boat, and r represents the vertical angular velocity of the digital simulation unmanned boat; M represents the inertia matrix; C(ξ) represents the Coriolis centripetal force matrix; D(ξ) represents the fluid damping matrix; g(η) represents the restoring force matrix of the digital simulation unmanned boat model itself; τ represents the control input matrix of the digital simulation unmanned boat, where τ=[τ u , τ v , τ w , τ p , τ q , τ q ] T , τ u represents the longitudinal force acting on the digital simulation unmanned boat; τ v represents the lateral force acting on the digital simulation unmanned boat; τ w represents the vertical force acting on the digital simulation unmanned boat; τ p represents the moment acting on the rolling of the digital simulation unmanned boat; τ q represents the moment acting on the pitching of the digital simulation unmanned boat; τ q Indicates the moment acting on the bow of the digital simulation unmanned boat;

[0061] Specifically, since the experimental platform structure of this embodiment is symmetrical and only the motion of the digital simulated unmanned vehicle on the horizontal plane is considered, by ignoring the non-diagonal elements in the inertia matrix and the damping matrix, and ignoring the effect of viscous fluid on the motion of the digital simulated unmanned vehicle, the motion model of the digital simulated unmanned vehicle model can be simplified to the following equation:

[0062]

[0063] Where: m 11 Indicates the longitudinal inertia coefficient of the digital simulation unmanned boat; m 22 Indicates the lateral inertia coefficient of the digital simulation unmanned boat; m 33 Indicates the vertical inertia coefficient of the digital simulation unmanned boat; d 11 Represents the linear damping coefficient of the longitudinal motion of the digital simulation unmanned boat; d 22 Represents the linear damping coefficient of the lateral motion of the digital simulation unmanned boat; d 33 Indicates the rotation damping coefficient of the vertical rotation of the digital simulation unmanned boat;

[0064] Specifically, the physical ship (physical unmanned boat) in this embodiment, that is, the actual ship sailing on the sea, establishes a serial communication network with the unmanned boat ground station, and sends the status data of the physical unmanned boat back to the unmanned boat ground station in real time. According to the status data of the physical unmanned boat, a corresponding twin unmanned boat is generated in the three-dimensional visual simulation virtual space model, that is, a mapping boat model of the real boat.

[0065] The twin unmanned boat, that is, the mapping boat model of the real boat has the same appearance, spatial position and posture information (speed and heading angle) as the physical unmanned boat; wherein, the appearance model of the twin unmanned boat is obtained by proportional modeling of the physical unmanned boat; wherein, the spatial position of the twin unmanned boat is achieved by establishing a spatial coordinate system in a three-dimensional visual simulation virtual space, selecting a reference point in the virtual space, and setting the longitude and latitude of the reference point to be consistent with the longitude and latitude of the corresponding point in the actual maritime scene. The status data of the physical unmanned boat is transmitted back to the unmanned boat ground station through the serial communication network, and the relative position of the physical unmanned boat and the actual maritime scene reference point is calculated and converted into the relative position with the midpoint of the virtual space, thereby determining the position of the twin unmanned boat in the virtual space; the posture information transmitted back by the physical unmanned boat is assigned to the twin unmanned boat. Thereby, the twin unmanned boat is mapped in the virtual space to the movement of the physical unmanned boat in the actual maritime scene. Specifically, the design of the digital simulation unmanned boat model in this embodiment includes the design of the outline of the digital simulation unmanned boat model and the design of the motion model of the digital simulation unmanned boat. The outline of the digitally simulated unmanned boat model is obtained by scaling down the actual physical unmanned boat using 3D Max software. The virtual position of the digitally simulated unmanned boat model in the virtual ocean environment is its actual position in the virtual ocean environment. In this embodiment, the initial virtual speed and initial virtual heading angle of the digitally simulated unmanned boat model in the virtual ocean environment are set to 0.

[0066] The digital simulation unmanned boat motion model takes the expected speed and expected heading angle as input, and the actual position and actual attitude information (including speed and heading angle) of the digital simulation unmanned boat model as output. The controller generates the underlying control signal, and controls the speed of the propeller and the rudder angle of the servo of the digital simulation unmanned boat model through the obtained navigation speed and heading angle. The propeller generates thrust and the servo generates torque. The speed and heading angle are calculated according to the three-degree-of-freedom dynamic model of the unmanned boat, and the position information is calculated according to the three-degree-of-freedom kinematic model of the unmanned boat.

[0067] S4: Based on the mapped position, mapped speed, and mapped heading angle of the real boat in the virtual ocean environment at the current moment, and the virtual position, virtual speed, and virtual heading angle of the digital simulated virtual unmanned boat in the virtual ocean environment at the current moment, obtaining, based on a cluster collaborative control algorithm, an expected mapped speed and expected mapped heading angle of the real boat in the virtual ocean environment at the next moment, and an expected virtual speed and expected virtual heading angle of the digital simulated unmanned boat at the next moment;

[0068] Preferably, the steps of the cluster collaborative control algorithm are as follows:

[0069] S41: Based on the position of the set reference virtual center point in the virtual ocean environment, the positions of other virtual points in the virtual ocean environment are obtained to obtain the positions of target virtual points of the unmanned boats in the unmanned boat cluster formation; this includes the positions of the target virtual points of the mapped real boats and the positions of the target virtual points of the digitally simulated virtual unmanned boats;

[0070] Preferably, the formula used to obtain the position of the target virtual point of the unmanned boat in the unmanned boat cluster formation is as follows:

[0071]

[0072] Where: represents the position of the target virtual point of the i-th unmanned boat; P l Indicates the position of the reference virtual center point, R(ψ l ) represents the transformation matrix from the local coordinate system to the earth coordinate system; ψ l Indicates the heading angle of the reference virtual center point; d i represents the relative distance between the i-th virtual center point and the reference virtual point; θ i Indicates the relative angle between the virtual center point and the reference virtual point; x i l ,y i l They represent the X-axis coordinate and Y-axis coordinate of the target virtual point of the i-th unmanned boat in the geodetic coordinate system respectively.

[0073] S42: obtaining the expected speed and expected heading angle of the unmanned boats in the unmanned boat cluster formation at the next moment in the virtual ocean environment according to the positions of the target virtual points of the unmanned boats;

[0074]

[0075] Where: is the expected speed of the i-th unmanned boat in the virtual ocean environment at the next moment; k p Indicates the position difference compensation parameter; Indicates the distance between the unmanned boat and the target virtual point; is the speed of the target virtual point of the i-th unmanned boat; k d represents the rate balance parameter; u i represents the actual speed of the i-th unmanned boat; Δψ represents the angle deviation; represents the azimuth between the unmanned boat and the target virtual point; x i l ,y i l They represent the horizontal and vertical coordinates of the target virtual point of the i-th unmanned boat in the virtual ocean environment; i ,yi They represent the horizontal and vertical coordinates of the position of the i-th unmanned boat in the virtual ocean environment; ψ i represents the actual heading angle of the i-th unmanned boat at the current moment; represents the expected heading angle of the i-th unmanned vehicle in the virtual ocean environment at the next moment; sign(·) represents the sign function; r max represents the maximum turning angle of the unmanned boat; |·| represents absolute value operation;

[0076] S43. Obtaining the expected mapping speed and expected mapping heading of the real vessel in the virtual ocean environment at the next moment, and the expected speed and expected heading of the digital simulation unmanned vessel model at the next moment, based on the expected speed and expected heading of the unmanned vessel in the unmanned vessel cluster formation at the next moment in the virtual ocean environment; thereby obtaining the actual expected speed and actual expected heading of the physical vessel sailing at the sea at the next moment;

[0077] Specifically, in the swarm collaborative control algorithm, a virtual formation is formed by setting a reference virtual point as the virtual center point, and determining the positions of the remaining virtual points based on the virtual center point. Since the physical unmanned boats and the digitally simulated unmanned boats have the same input and output forms, the physical unmanned boats and the digitally simulated unmanned boats are treated as the same objects for calculation in the swarm collaborative control algorithm. Once the expected speed and expected heading angle of the unmanned boats in the swarm formation at the next moment are obtained, the expected speed and expected heading angle of the physical unmanned boats and the digitally simulated unmanned boats in the swarm formation can be determined.

[0078] S5: obtaining the actual position, actual speed, and actual heading angle of the physical ship at the next moment according to the expected mapping speed and expected mapping heading angle of the mapping ship of the real ship in the virtual ocean environment at the next moment;

[0079] According to the expected virtual speed and expected virtual heading angle of the digital simulated unmanned boat at the next moment, the actual virtual position, actual virtual speed, and actual virtual heading angle of the digital simulated unmanned boat at the next moment are obtained;

[0080] Specifically, according to the expected virtual speed and expected virtual heading angle of the digital simulation unmanned boat at the next moment; the actual virtual position, actual virtual speed and actual expected heading angle of the digital simulation unmanned boat at the next moment can be obtained through the digital simulation unmanned boat motion model;

[0081] Specifically, in this embodiment, the expected mapping speed and expected mapping heading angle of the mapping boat of the real boat in the virtual ocean environment at the next moment are the expected speed and expected heading angle of the physical ship sailing on the sea at the next moment. The physical ship sails according to the expected speed and expected heading angle. Due to the existence of various interference information, when the physical ship sails according to the expected speed and expected heading angle, the speed and heading angle actually reached at the next moment will have a certain deviation. Therefore, in this embodiment, the autopilot in the actual ship calculates and generates a bottom-level control signal based on the expected speed and expected heading angle of the physical ship at the next moment, and sends it to the electric regulator and the steering gear to execute the control command; at the same time, the positioning module and each sensor module obtain the actual position, actual speed and actual heading angle of the physical ship sailing on the sea.

[0082] S6: According to the actual speed, actual heading angle and actual position of the physical ship at the next moment, obtain the mapping speed, mapping heading angle and mapping position of the mapping boat of the real boat in the virtual ocean environment at the next moment; repeat S4-S5 according to the actual virtual speed, actual virtual heading angle and actual virtual position of the digital simulation unmanned boat at the next moment; to achieve collaborative control of the unmanned boat cluster based on the combination of virtual and real, and then achieve control of the physical ships sailing on the sea. Specifically, this embodiment adopts a cluster collaborative control algorithm to select a virtual center point, determine the formation based on the virtual center point, and assign a formation position to the unmanned boat; obtain the expected speed and expected angle of each unmanned boat through the unmanned boat motion controller, and send it to the physical ship and the digital simulation unmanned boat model to control it to move to the formation position, and then achieve collaborative control of the unmanned boat formation through formation control of the real boat and the digital simulation unmanned boat model. A specific implementation method of this embodiment is as follows:

[0083] Based on the three-dimensional visual simulation virtual space model, a collaborative movement scene of a cluster of six unmanned boats is established, including a mapping boat of a real boat and a digital simulation unmanned boat model.

[0084] The total number of virtual and real unmanned boat nodes in this embodiment is determined to be 6, of which 3 nodes are digital simulation unmanned boats and 3 nodes are mapping boats of real boats sailing at sea. Figure 2 As shown, the Unity3D simulation platform displays the fleet formation from multiple angles and perspectives, displaying the unmanned boat identification and trajectory to distinguish between the real-world mapped boat (red) and the digitally simulated unmanned boat (yellow). A drone is then used to follow the actual ships at sea for aerial photography and comparison of virtual and real scenes. Finally, the system's operational data is recorded at every moment, and post-processed to generate trajectory diagrams, speed change diagrams, and angle change diagrams, resulting in combined virtual and real simulation comparison data.

[0085] The virtual-real combined unmanned autonomous algorithm verification system of this embodiment includes three parts: a physical unmanned boat, a digital simulation unmanned boat module, and a three-dimensional vision module.

[0086] The physical unmanned boat is an independently built under-actuated unmanned boat experimental platform, which executes the cluster collaborative control algorithm of this embodiment in an actual marine scenario and transmits the physical unmanned boat status data back to the unmanned boat ground station in real time;

[0087] The digital simulation unmanned boat module includes the appearance outline of the unmanned boat and the digital simulation unmanned boat motion model. It executes the cluster collaborative control algorithm in a digital simulation manner to obtain control instructions (desired speed, desired heading angle) and feedback status data (actual speed, actual heading angle);

[0088] The three-dimensional vision module is used to create a virtual maritime scene, generate a twin unmanned boat based on the physical unmanned boat data, and display the cluster movement status through the twin unmanned boat and the digital simulation unmanned boat model.

[0089] See also Figure 3 , demonstrating the overall construction plan for a physical unmanned boat. A self-built underactuated unmanned boat was selected as the experimental platform. Its hull is made of fiberglass, which features light weight, high strength, good insulation, and corrosion resistance. The boat measures 121cm x 39cm and weighs 10.15kg. Its propeller has a diameter of 5.075cm, a rudder length of 10.4cm, and a width of 5.4cm. It uses a single-propeller, single-rudder propulsion system. The auxiliary computer in the physical unmanned boat receives control commands (desired speed, desired heading angle) from the unmanned boat's ground station and sends them to the autopilot to calculate and generate low-level control signals. These signals are then sent to the electronic speed controller and steering gear to execute the control commands. Simultaneously, the positioning module and various sensor modules transmit various status information of the unmanned boat to the onboard auxiliary computer for data processing. The auxiliary computer then transmits this status information back to the unmanned boat's ground station via the wireless communication module.

[0090] See Figure 4 and Figure 5 The flow charts for the digital simulation unmanned vehicle model and the digital simulation unmanned vehicle motion module in Unity3D are presented. Using 3D Max software, a three-dimensional model of the physical unmanned vehicle is scaled down to obtain the digital simulation unmanned vehicle's outline. The processed model is then imported into Unity3D. The digital simulation unmanned vehicle motion module takes control commands (desired speed and angle) as input and the actual position and pose information (speed and heading) of the digital simulation unmanned vehicle as output. It supports parsing control commands through a controller to generate underlying control signals to control the propeller speed and steering angle of the servo. After the propeller generates thrust and the servo generates torque, the actual speed and heading angle are calculated based on the digital simulation unmanned vehicle dynamics model, and the position information is calculated based on the digital simulation unmanned vehicle kinematics model.

[0091] Figure 6 and Figure 2 Both virtual marine scenes and virtual-real collaborative motion scenes are displayed. The ocean environment is established using the Crest Ocean System plug-in. A new ocean object is created in the scene, and the Ocean Renderer component is attached to generate an initialized ocean environment. The sea level is adjusted to an appropriate level. Details such as the water material and color are set based on the characteristics of the actual water body. The Shape FTT component is used to configure detailed wave effects. Data such as the position and posture of the physical unmanned boat is received, and by constructing a virtual space coordinate system for the unmanned boat, the latitude and longitude positions of the unmanned boat are converted to virtual space positions. The navigation status of the unmanned boat is displayed in three dimensions, meeting the 3D display and scene requirements of large-scale unmanned boat swarm simulations.

[0092] See also Figure 7 , showing the trajectory diagram of the combined virtual-real sea experiment results of this embodiment. The red image shows the physical unmanned boat, and the blue image shows the digitally simulated unmanned boat. The mapped boat and the digitally simulated unmanned boat jointly achieved the desired formation shape and maintained the formation heading, demonstrating the effectiveness and stability of this embodiment. The displacement curve of the physical unmanned boat exhibits slight fluctuations due to wind and wave interference at sea; however, the displacement trajectory of the digitally simulated unmanned boat is closer to the ideal path, demonstrating that the digital simulation model can effectively simulate the ideal navigation state of the unmanned boat.

[0093] See also Figure 8a , showing the speed diagrams of three physical unmanned boats of the virtual-reality combined experiment results at sea of ​​this embodiment; the speeds of the three physical unmanned boats were stable throughout the entire experiment and were able to maintain the set speed, reflecting the reliability of the speed control of the physical unmanned boats in this embodiment.

[0094] Figure 8b These are three speed diagrams of digitally simulated unmanned boats according to the results of the virtual-reality combined experiment at sea described in the embodiment; the speeds of the three digitally simulated unmanned boats are relatively stable and can maintain a constant speed, which verifies the accuracy and consistency of the speed control of the digitally simulated unmanned boats in this embodiment.

[0095] Figure 9a The following are the heading angle diagrams of three physical unmanned boats according to the results of the virtual-reality combined experiment at sea described in the embodiment; the heading angle of the physical unmanned boat fluctuated, and the fluctuation was synchronized with the speed fluctuation period, which shows that the wind and wave interference affected the speed and heading control of the physical unmanned boat at the same time, but the unmanned boat was still able to maintain the predetermined heading to a certain extent, reflecting the robustness of this embodiment.

[0096] Figure 9bThese are three heading angle diagrams of digitally simulated unmanned boats based on the results of the virtual-reality combined experiment at sea described in the examples. Since wind and wave resistance is not considered, the heading angle curve is smooth, which reflects the precise control capability of the digitally simulated unmanned boats in ideal environments and also provides a reference for optimizing control strategies in practical applications.

[0097] 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.

[0098] 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 collaborative control method for unmanned boat swarm based on virtual-real integration, characterized in that: The steps include: S1: Establish a three-dimensional visual simulation virtual space model and obtain an initialized virtual ocean environment; S2: establishing an unmanned boat swarm formation in the initialized virtual ocean environment, where the unmanned boats in the unmanned boat swarm formation include mapping boats of real boats or digital simulation unmanned boats; S3: Establishing a motion model of a digital simulation unmanned boat; and obtaining the mapped position, mapped speed, and mapped heading angle of the real boat in the virtual ocean environment at the current moment based on the actual position, actual speed, and actual heading angle of the physical ship sailing at sea at the current moment; S4: Based on the mapped position, mapped speed, and mapped heading angle of the real boat in the virtual ocean environment at the current moment, and the virtual position, virtual speed, and virtual heading angle of the digital simulated unmanned boat in the virtual ocean environment at the current moment, obtaining, based on a cluster collaborative control algorithm, an expected mapped speed and expected mapped heading angle of the real boat in the virtual ocean environment at the next moment, and an expected virtual speed and expected virtual heading angle of the digital simulated unmanned boat at the next moment; S5: obtaining the actual speed and actual heading angle of the physical ship at the next moment according to the expected mapping speed and expected mapping heading angle of the mapping boat of the real ship in the virtual ocean environment at the next moment; According to the expected virtual speed and expected virtual heading angle of the digital simulation unmanned boat at the next moment, the actual virtual speed and actual virtual heading angle of the digital simulation unmanned boat at the next moment are obtained; S6: obtaining the mapped speed, mapped heading angle, and mapped position of the mapped boat of the real boat in the virtual ocean environment at the next moment according to the actual speed, actual heading angle, and actual position of the physical boat at the next moment; S4-S5 are repeatedly executed according to the actual virtual speed, actual virtual heading angle, and actual virtual position of the digitally simulated unmanned boat at the next moment; thereby realizing the coordinated control of the unmanned boat cluster based on the combination of virtual and real, and further realizing the control of the physical ship sailing at sea; The steps of the cluster collaborative control algorithm are as follows: S41: Based on the position of the set reference virtual center point in the virtual ocean environment, the position of the target virtual point of the unmanned boat in the unmanned boat cluster formation is obtained; S42: obtaining the expected speed and expected heading angle of the unmanned boats in the unmanned boat cluster formation at the next moment in the virtual ocean environment according to the positions of the target virtual points of the unmanned boats; S43, obtaining the expected mapping speed and expected mapping heading of the real boat in the virtual ocean environment at the next moment, as well as the expected speed and expected heading of the digital simulation unmanned boat model at the next moment, based on the expected speed and expected heading of the unmanned boats in the unmanned boat cluster formation in the virtual ocean environment at the next moment; The formula used to obtain the position of the target virtual point of the unmanned boat in the unmanned boat cluster formation is as follows: Where: represents the position of the target virtual point of the i-th unmanned boat; P l Indicates the position of the reference virtual center point, R(ψ l ) represents the transformation matrix from the local coordinate system to the earth coordinate system; ψ l Indicates the heading angle of the reference virtual center point; d i represents the relative distance between the i-th virtual center point and the reference virtual point; θ i Indicates the relative angle between the virtual center point and the reference virtual point; x i l ,y i l They represent the X-axis coordinate and Y-axis coordinate of the target virtual point of the i-th unmanned boat in the geodetic coordinate system respectively.

2. The method for collaborative control of a swarm of unmanned boats based on virtual-real integration according to claim 1 is characterized in that: The formula used to obtain the expected speed and expected heading angle of the unmanned boats in the unmanned boat cluster formation at the next moment in the virtual ocean environment is as follows: Where: is the expected speed of the i-th unmanned boat in the virtual ocean environment at the next moment; k p Indicates the position difference compensation parameter; |P i l -P l | represents the distance between the unmanned boat and the target virtual point; is the speed of the target virtual point of the i-th unmanned boat; k d represents the rate balance parameter; u i represents the actual speed of the i-th unmanned boat; Δψ represents the angular deviation; represents the azimuth between the unmanned boat and the target virtual point; x i l ,y i l They represent the horizontal and vertical coordinates of the target virtual point of the i-th unmanned boat in the virtual ocean environment; i ,y i They represent the horizontal and vertical coordinates of the position of the i-th unmanned boat in the virtual ocean environment; ψ i represents the actual heading angle of the i-th unmanned boat at the current moment; represents the expected heading angle of the i-th unmanned vehicle in the virtual ocean environment at the next moment; sign(·) represents the sign function; r max represents the maximum turning angle of the unmanned boat; |·| represents absolute value operation.

3. The method for cooperative control of a swarm of unmanned boats based on virtual-real integration according to claim 1 is characterized in that: The motion model of the digital simulation unmanned boat model is expressed as follows: Where: η represents the position and attitude vector of the digital simulation unmanned boat, where η=[α,β,γ,φ,θ,ψ] T , α represents the longitudinal position of the digital simulation unmanned boat, β represents the lateral position of the digital simulation unmanned boat, γ represents the vertical position of the digital simulation unmanned boat, φ represents the roll angle of the digital simulation unmanned boat, θ represents the longitudinal tilt angle of the digital simulation unmanned boat, ψ represents the bow phase angle of the digital simulation unmanned boat, represents the first-order differential; R(η) represents the rotation matrix; ξ represents the velocity vector of the digital simulation unmanned boat, where ξ=[u,v,w,p,q,r] T , u represents the longitudinal velocity of the digital simulation unmanned boat, v represents the lateral velocity of the digital simulation unmanned boat, w represents the vertical velocity of the digital simulation unmanned boat, p represents the longitudinal angular velocity of the digital simulation unmanned boat, q represents the lateral angular velocity of the digital simulation unmanned boat, and r represents the vertical angular velocity of the digital simulation unmanned boat; M represents the inertia matrix; C(ξ) represents the Coriolis centripetal force matrix; D(ξ) represents the fluid damping matrix; g(η) represents the restoring force matrix of the digital simulation unmanned boat model itself; τ represents the control input matrix of the digital simulation unmanned boat, where τ=[τ u ,τ v ,τ w ,τ p ,τ q ,τ r ] T , τ u represents the longitudinal force acting on the digital simulation unmanned boat; τ v represents the lateral force acting on the digital simulation unmanned boat; τ w represents the vertical force acting on the digital simulation unmanned boat; τ p represents the moment acting on the rolling of the digital simulation unmanned boat; τ q represents the moment acting on the pitching of the digital simulation unmanned boat; τ r Indicates the moment acting on the bow of the digital simulation unmanned boat; The motion model of the digital simulation unmanned boat model is simplified and expressed as follows: Where: m 11 Indicates the longitudinal inertia coefficient of the digital simulation unmanned boat; m 22 Indicates the lateral inertia coefficient of the digital simulation unmanned boat; m 33 Indicates the vertical inertia coefficient of the digital simulation unmanned boat; d 11 Represents the linear damping coefficient of the longitudinal motion of the digital simulation unmanned boat; d 22 Represents the linear damping coefficient of the lateral motion of the digital simulation unmanned boat; d 33 Represents the rotational damping coefficient of the vertical rotation of the digital simulation unmanned boat.

4. The method for cooperative control of a swarm of unmanned boats based on virtual-real integration according to claim 1 is characterized in that: The unmanned boat cluster formation adopts a triangular cluster formation.

5. The method for cooperative control of a swarm of unmanned boats based on virtual-real integration according to claim 1 is characterized in that: The method for obtaining the outline of the unmanned boats in the unmanned boat cluster formation is: According to the outline of the physical ship, 3D Max software is used to proportionally reduce the size of the physical ship and then perform three-dimensional modeling.

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