Method and system for unmanned ship and unmanned aerial vehicle cooperative operation

Abstract

This invention relates to a method and system for collaborative operation between an unmanned surface vessel (USV) and an unmanned aerial vehicle (UAV), belonging to the field of unmanned system control technology. The method includes: the USV autonomously cruises in a fan-shaped or parallel search mode, detecting targets and calculating their coordinates using side-scan sonar and radar; the USV generates a mission data packet and sends it to the UAV, adjusting its attitude for UAV takeoff and landing; the UAV flies to the target's airspace, confirms the target's attributes and status using an infrared pod or zoom camera, and autonomously drops a lifebuoy and provides acoustic and optical guidance; the USV dynamically optimizes its trajectory based on the transmitted real-time target coordinates and approaches the target, dropping rescue equipment via an electrically operated drop device upon arrival. This invention constructs a closed-loop collaborative process of "detection-confirmation-initial rescue-final disposal," effectively solving the problems of poor adaptability to harsh sea conditions, insufficient collaborative depth, and low reliability of long-range communication in existing technologies.

Description

Technical Field

[0001] This invention belongs to the field of unmanned system control technology, specifically relating to a method and system for collaborative operation of unmanned surface vessels and unmanned aerial vehicles. Background Technology

[0002] With the rapid development of the marine economy, maritime shipping, tourism, and fishing activities are becoming increasingly frequent, leading to a gradual increase in the probability of various maritime emergencies. This places higher demands on the reliability and efficiency of maritime patrol and search and rescue equipment. Currently, although there are technological explorations combining unmanned surface vessels (USVs) and unmanned aerial vehicles (UAVs) for maritime operations, there are still general shortcomings.

[0003] Existing technology CN111830981A discloses an unmanned three-dimensional collaborative search and rescue platform for maritime rescue, which consists of intelligent ships, drones, and underwater vehicles, and achieves information exchange through data transmission radios and low-frequency communication. However, this solution focuses on the communication connection between the platforms and the loose coordination method, and does not form a closed-loop operation process with clear stage divisions and triggering conditions. During the rescue process, the handover of tasks from target discovery to disposal relies on manual scheduling, and there is a delay in the task connection between the platforms, which cannot achieve the efficient response of "discovery and disposal". Existing technology CN117519170A discloses a collaborative search and rescue method and system for ship and vehicle swarms based on resource pre-allocation. It optimizes resource deployment through accident black spot analysis and LSTM prediction, and uses ant colony algorithm for multi-drone task allocation. This solution mainly solves the problem at the resource scheduling level, but does not improve the unmanned vehicle platform's ability to withstand harsh sea conditions. When encountering typhoons or severe convective weather, the unmanned surface vessel (USV) used in this system experiences severe hull rolling and large waves on the deck, making it impossible to provide a stable working environment for the onboard equipment and UAVs, thus limiting the system's applicability in high sea states. Existing technology CN118760170A discloses a sea-air cross-domain collaborative intelligent unmanned surface search and rescue system, consisting of a multi-functional UAV, an autonomous obstacle-avoiding USV, a rescue robot, and a ground station. Its USV adopts a conventional catamaran or monohull design and lacks a deep wave-resistant structure and active attitude control device. In sea states exceeding level 5, the hull roll angle increases significantly, leading to higher safety risks for UAV takeoff and landing and a higher failure rate for search and rescue equipment, making it difficult to meet all-weather operational requirements. Existing technology CN120817219A discloses a USV-UAV three-dimensional search and rescue device and method, which achieves rapid deployment through a detachable design of the UAV support and USV connection port, and uses YOLOv7 and ORB-SLAM3 algorithms for target recognition and visual navigation. This solution focuses on structural connectivity and single-unit vision technology, neglecting the survivability of unmanned surface vessels (USVs) in harsh sea conditions and failing to construct a redundant communication network adapted to the absence of public networks in the open ocean. When the operational area exceeds public network coverage, the single communication link limits both the reliability and coverage of data transmission.

[0004] Therefore, there is an urgent need for a method and system for collaborative operation of unmanned surface vessels and unmanned aerial vehicles (UAVs) with strong wave resistance, high dynamic reliability, standardized closed-loop collaborative logic, and wide-area redundant communication capabilities. Summary of the Invention

[0005] To address the aforementioned problems in the existing technology, this invention provides a method and system for collaborative operation of unmanned surface vessels and unmanned aerial vehicles.

[0006] The objective of this invention can be achieved through the following technical solutions: A method for collaborative operation of unmanned surface vessels and unmanned aerial vehicles includes the following steps: S1. Autonomous cruise and wide-area target detection of unmanned surface vessels: The unmanned surface vessel receives mission instructions from the shore-based system and navigates autonomously in the target sea area in a fan-shaped search mode or a parallel search mode. It collects environmental data and identifies targets through the onboard side-scan sonar and navigation radar. After discovering a suspicious target, it calculates its absolute coordinates. S2. The collaborative mission is initiated and the unmanned surface vessel (USV) and unmanned aerial vehicle (UAV) missions are handed over. The USV sends a mission data package containing the coordinates of the suspected target and the initial screening type information to the shore-based platform and the UAV mounted on the USV via satellite link and air-sea data link, respectively. If the USV is in deep semi-submersible mode, it will automatically surface and open the UAV hangar door and suppress the hull roll angle to takeoff conditions through the attitude control system based on inertial measurement unit feedback carried by the USV. S3. Precise UAV Authentication and Autonomous Initial Rescue Execution: After receiving the mission data packet, the UAV takes off autonomously and flies to the target area. It collects target images through the onboard visual payload and uses the target detection model to confirm the target category. When the target is confirmed to be a person to be rescued, the UAV autonomously executes the initial rescue subroutine, including deploying life-saving equipment with positioning function and providing audio-visual guidance. S4. Dynamic trajectory optimization and adaptation final processing of unmanned surface vessels: The unmanned surface vessel receives the real-time coordinates and status assessment information of the target transmitted back by the drone, switches the trajectory planning to the search and rescue target priority mode and sails towards the target area; upon arrival, it makes decisions based on the target status assessment information and deploys the appropriate type of rescue equipment. S5. Mission closed-loop confirmation and coordinated evacuation guidance: After the unmanned surface vessel confirms the successful rescue, it generates a rescue report and automatically reports it; if personnel transfer is required, the unmanned surface vessel broadcasts its own position, and the drone uses laser pointers to visually guide the target position.

[0007] As a preferred embodiment of this application, in step S1, the sector search mode is: taking the known target point coordinates as the center, generating a set of sector scanning lines covering a preset central angle, and the sonar detection range between adjacent scanning lines has a preset connection overlap rate; the parallel search mode is: determining the spacing between adjacent parallel lines based on the effective single-side scanning width of the side-scan sonar, and the line spacing is the product of the single-side scanning width and the preset overlap coefficient.

[0008] As a preferred embodiment of this application, in step S2, the semi-submersible mode is as follows: the ballast tanks of the unmanned surface vessel are filled with water to a preset capacity ratio, and the hull is located at a preset underwater depth range; the surfacing procedure is as follows: the ballast tank filling valve is closed, and the drainage pump is started to discharge the ballast water until the water level in each ballast tank drops below a preset empty threshold; the attitude control system uses the angular velocity and acceleration data output by the inertial measurement unit to calculate the anti-roll torque using a PID controller, and adjusts the nozzle direction and thrust of the tail water jet propulsion unit differentially and fine-tunes the angle of attack of the tail stabilizing fin to make the hull roll angle meet the takeoff conditions of the unmanned surface vessel.

[0009] As a preferred embodiment of this application, the specific execution process of the preliminary rescue subroutine in step S3 is as follows: the UAV measures the vertical distance to the sea surface using a laser rangefinder, the flight control computer reads wind speed and direction data, calls the ballistic calculation function to calculate the coordinate offset of the forward drop point, adjusts the horizontal position and hovers directly above the drop point; sends an opening command to the emergency drop cabin, releases the electromagnetic lock pin, and the rescue equipment falls freely; after the drop is completed, the high-volume broadcaster plays the pre-stored rescue guidance voice in a loop mode, and the green laser pointer emits a laser beam, with the light spot continuously illuminating the location where the rescue equipment falls into the water.

[0010] As a preferred embodiment of this application, in step S4, the search and rescue target priority mode is: in improved A In the cost function of the algorithm, the weight of the target point heuristic function term is increased, while the weight of the collision avoidance cost terms related to static and dynamic obstacles is reduced. The decision logic of the adaptive type of life-saving equipment is as follows: if the target state is a single person with normal physical strength, a life ring with a positioning beacon is deployed; if the target state is multiple people, or a single person with insufficient physical strength or signs of hypothermia, an automatically inflatable life raft is deployed.

[0011] As a preferred embodiment of this application, during the entire collaborative operation, the unmanned surface vessel and the unmanned aerial vehicle communicate through a multi-link communication network consisting of a 5G communication module, a satellite terminal, a VHF relay module, and an air-sea data link. After the unmanned aerial vehicle takes off, its onboard VHF relay transponder is automatically activated as an airborne auxiliary communication node. The communication controller monitors the quality indicators of each link, and when the quality of the first link is detected to be lower than the preset conditions, it automatically switches the data stream to the second link.

[0012] This application also provides a collaborative operation system for unmanned surface vessels and unmanned aerial vehicles (UAVs) to implement the method described above, including an unmanned surface vessel, at least one UAV, and a shore-based control platform; The unmanned surface vessel includes a central controller, an intelligent driving module, a multi-dimensional perception system, a semi-submersible control module, a disposal module, a communication module, and an onboard UAV library, used to perform maritime patrol, target detection, mission data packet generation and distribution, UAV release control, dynamic trajectory optimization, and final rescue disposal. The drone, mounted on the unmanned surface vessel, includes a flight control computer, a mission management computer, a visual perception payload, a preliminary rescue payload, and an airborne data terminal, used to receive mission data packets, fly to the target, perform visual confirmation, perform preliminary rescue, and transmit information back. The shore-based control platform is communicatively connected to the unmanned surface vessel and is used for mission issuance, remote monitoring and emergency takeover. The unmanned surface vessel and the unmanned aerial vehicle communicate with each other via an air-sea data link, forming a collaborative operation network.

[0013] As a preferred embodiment of this application, the hull of the unmanned surface vessel is a manta ray-inspired deep-V monohull structure made of carbon fiber composite material, with a stabilizing fin at the tail; its power system includes two main water jet propulsion units and one emergency pod propulsion unit; the energy system is a lithium iron phosphate battery pack, and is equipped with a search and rescue mode energy consumption management strategy; the semi-submersible control module includes a meteorological satellite data receiving terminal, a three-dimensional wave sensor, a model predictive control-based anti-sea state control algorithm, and a ballast water system.

[0014] This application also provides an electronic device, including a processor, a memory, and a computer program stored in the memory, wherein the processor executes the computer program to implement the method described above.

[0015] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described above.

[0016] The beneficial effects of this invention are as follows: 1) Significantly Improved Collaborative Operation Efficiency: This invention establishes a standardized closed-loop collaborative logic of "Unmanned Surface Vessel (USV) Detection - Unmanned Aerial Vehicle (UAV) Confirmation - UAV Initial Rescue - USV Final Disposal." After the USV detects a target, it automatically generates a mission data packet and sends it to the UAV. Upon target confirmation, the UAV autonomously performs drop operations and audio-visual guidance. Simultaneously, the USV receives real-time location information and dynamically plans its approach path. This process clearly defines the mission boundaries and triggering conditions of each platform, achieving seamless integration from detection to disposal, and significantly shortening the rescue response time.

[0017] 2) Strong adaptability to extreme sea states: The unmanned surface vessel (USV) adopts a manta ray-inspired monohull structure, combined with a bow wave-breaking bulwark, a stern double stabilizing fin, and a deep V-shaped hull. The semi-submersible control module integrates meteorological satellite data and three-dimensional wave sensor data. When the sea state exceeds a threshold, it automatically triggers a deep semi-submersible mode, controlling the hull to submerge to a depth of 8 to 12 meters through the ballast water system, ensuring that the roll angle does not exceed 8 degrees in sea state 8, providing a stable platform for the USV's take-off, landing, and collaborative operations in extreme weather conditions.

[0018] 3) High reliability of the power system: The unmanned surface vessel adopts a "2 main, 1 backup" power redundancy architecture. In the event of a main thruster failure, the emergency thruster can be deployed and output thrust within 5 seconds, ensuring a speed of no less than 15 knots. The battery pack has a built-in search and rescue mode energy management strategy. When the state of charge drops to 20%, it automatically cuts off low-priority loads to ensure that the core search and rescue equipment can operate for no less than 4 hours, avoiding mission interruption due to power or energy problems.

[0019] 4) Wide and reliable communication coverage in distant waters: This invention constructs a multi-link adaptive communication network integrating 5G, satellite terminals, and VHF relay modules. Unmanned surface vessels (USVs) act as gateways, while drones serve as aerial auxiliary relay nodes after takeoff. The communication controller monitors link quality in real time, automatically switching to the satellite link when the 5G link fails. End-to-end data transmission latency is controlled within 2 seconds, ensuring reliable communication for collaborative operations in areas without public networks in distant waters. Attached Figure Description

[0020] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0021] Figure 1 This is a flowchart illustrating the overall process of the collaborative operation method between unmanned surface vessels and unmanned aerial vehicles provided in an embodiment of the present invention. Figure 2 This is an architecture diagram of the unmanned surface vessel and unmanned aerial vehicle collaborative operation system provided in an embodiment of the present invention; Detailed Implementation To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0022] Example 1 This embodiment provides a method for collaborative operation between unmanned surface vessels (USVs) and unmanned aerial vehicles (UAVs). For example... Figure 1 As shown, the specific steps are as follows: S1, Autonomous Cruise and Wide-Area Target Detection of Unmanned Surface Vessels This step involves an unmanned surface vessel (USV) acting as an independent entity to conduct a comprehensive search of the target sea area and to initially detect and identify suspicious targets.

[0023] S101, Mission Reception and Track Planning The unmanned surface vessel (USV) receives mission command data packets from a shore-based control platform via its communication module. These packets contain at least: a unique mission identifier, a sequence of target sea area boundary coordinates, a search priority indicator, and specific mission parameters. The USV's central controller parses the mission command data packets and forwards the target sea area boundary coordinates and specific mission parameters to the intelligent driving module.

[0024] The intelligent driving module has a built-in improved A-based system. The algorithm's track generation function: When the special mission parameters include a known target point specified by the shore-based control platform, the intelligent driving module automatically selects the sector search mode. In sector search mode, the intelligent driving module generates a set of sector scan lines covering a central angle of 120 degrees, centered on the latitude and longitude coordinates of the known target point. The length of each scan line and the angular interval between adjacent scan lines are automatically calculated by the intelligent driving module based on the search radius and the effective single-side scan width of the shipborne side-scan sonar. The calculation process ensures that the overlap rate of the sonar detection range between two adjacent scan tracks is not less than 10%, thereby ensuring that the theoretical search coverage of the entire sector area is not less than 98%.

[0025] If the special mission parameters do not provide a known target point but only specify a rectangular or polygonal sea area, the intelligent driving module automatically selects the parallel search mode. In parallel search mode, the intelligent driving module determines the spacing between adjacent parallel lines based on the effective single-side scan width of the side-scan sonar. Taking the SSS-50 side-scan sonar as an example, its single-side scan width is 100 meters. To compensate for coverage gaps that may be caused by water flow and positioning errors, the line spacing is set to 180 meters to ensure at least 10% scan overlap.

[0026] During the generation of parallel routes, the intelligent driving module loads depth, shoals, reefs, and no-navigation zone layer information from the electronic nautical chart database. When a potential waypoint falls into or is too close to an obstacle layer, the improved A... The exclusionary term related to obstacles in the algorithm's cost function dramatically increases the cost of the path, thus driving the algorithm to automatically find alternative routes that bypass the area.

[0027] S102, Sensor Data Acquisition While the unmanned surface vessel is traveling along the planned route at an economical speed, its multi-dimensional perception system continuously collects data on the surrounding environment.

[0028] For underwater target detection, the side-scan sonar installed on the underwater side of the midship section of the hull begins operation. The side-scan sonar consists of a towed transducer array and a deck processing unit. The transducer array transmits fan-shaped acoustic pulses at a frequency of 455 kHz into the underwater space on both sides perpendicular to the course of the vessel, and continuously receives reflected echoes from the seabed, water bodies, and underwater targets. The deck processing unit arranges the echo intensity signals in a time sequence to form a sonar waterfall map reflecting the seabed topography and the distribution of underwater targets, and transmits the image data stream in real time at a frequency of 30 frames per second to the onboard search and rescue data processing terminal.

[0029] For surface target detection, the unmanned surface vessel simultaneously operates its X-band navigation radar. The radar antenna performs a circular scan at a speed of 24 revolutions per minute. The radar signal processing unit performs digital down-conversion, pulse compression, moving target detection, and constant false alarm rate processing on the raw echo to extract small-sized target points with stable tracks or stationary targets.

[0030] S103. Initial Target Screening and Coordinate Calculation The shipboard search and rescue data processing terminal has a built-in graphics processing unit with a specially trained deep convolutional neural network model deployed on it. During the inference phase, the deep convolutional neural network model scans the input sonar waterfall map in a sliding window manner and outputs a confidence probability value for the presence of a preset category target in each window. When the confidence value of a window exceeds the alarm threshold of 0.85, the shipboard search and rescue data processing terminal determines that a suspicious target has been detected.

[0031] The onboard search and rescue data processing terminal software calculates the slant range and azimuth of the target relative to the sonar transducer based on the position of the window in the sonar waterfall diagram. Then, combined with the real-time high-precision positioning data (obtained based on GPS differential positioning technology) and heading angle data provided by the unmanned surface vessel's central controller, it calculates the absolute geographical latitude and longitude coordinates of the suspicious target through a coordinate transformation algorithm and assigns it a unique temporary target number.

[0032] For radar targets, the shipboard search and rescue data processing terminal performs nearest neighbor comparisons between the radar target's location and the Automatic Identification System (AIS) broadcast data received via the network. If the Euclidean distance between the radar target and the AIS target location is less than 50 meters, the radar target is considered to be a cooperative vessel and is filtered out. Radar targets that cannot be associated are also identified as suspicious targets, their absolute coordinates are calculated, and a temporary target number is assigned.

[0033] S2. Collaborative mission initiation and unmanned surface vessel-unmanned aerial vehicle (USV) mission handover This step facilitates the handover of tasks from independent unmanned surface vessels (USVs) to collaborative operations with unmanned aerial vehicles (UAVs).

[0034] S201, Task Data Packet Generation and Distribution When the onboard search and rescue data processing terminal generates a new suspicious target, its mission management service reads all attribute information related to that target from the system memory, including the target number, initial target type screening result, calculated target latitude and longitude coordinates, target's current distance and bearing relative to the unmanned surface vessel, original echo feature description, and current timestamp. The mission management service packages this information according to a predefined data structure to generate a mission data packet using an efficient binary encoding format to reduce data size.

[0035] The mission data packet is distributed synchronously through two communication links. The first link transmits the packet to the shore-based control platform via the UAV's satellite communication terminal. A transmission control protocol is used to ensure complete data reception. The second link transmits the packet via a dedicated air-sea data link between the UAV and the UAV. This data link operates in the 5.8 GHz band and uses frequency-hopping spread spectrum technology to enhance anti-interference capabilities, with an effective communication range of no less than 15 kilometers under line-of-sight conditions. The UAV's onboard data terminal is always in a receiving standby state. Upon receiving the mission data packet, the onboard mission management computer parses the packet, extracts the target coordinates as the navigation endpoint, and switches its status from standby to mission ready.

[0036] S202, Unmanned Surface Vessel Attitude Adjustment and Unmanned Aircraft Release Preparation After sending out the mission data packet, the central controller of the unmanned surface vessel immediately queries the status register of the semi-submersible control module.

[0037] If the vessel is in a semi-submerged mode (ballast tanks are filled to 80% of their total capacity, and the vessel is at a depth of 8 to 12 meters), the semi-submersible navigation control module automatically initiates the surfacing procedure. The surfacing procedure closes the ballast tank filling valves and sequentially starts the drainage pumps (each with a rated flow rate of 50 L / min). The drainage pumps pump seawater out of the ballast tanks. Level sensors continuously monitor the water level changes in each ballast tank. When the water level in all ballast tanks drops to 5% of their capacity, the drainage pumps stop operating, and the semi-submersible navigation control module marks the vessel's status as surface navigation. If the vessel is already in surface navigation, this surfacing step is skipped.

[0038] The central controller sends a command to the control unit in the tail-mounted drone hangar, and the servo motor opens the top sliding door of the drone hangar. Simultaneously, the hull attitude control system actively engages to suppress roll. Using the three-axis angular velocity and acceleration data output from the inertial measurement unit, the hull attitude control system calculates the required anti-roll torque using a proportional-integral-derivative controller. It then differentially adjusts the nozzle direction and thrust of the two tail-mounted waterjet propellers, and fine-tunes the angle of attack of the tail-mounted dual stabilizing fins, generating a stabilizing torque opposite to wave disturbances, ensuring that the root mean square value of the hull's roll angle before drone takeoff does not exceed 5 degrees.

[0039] S3. Drone Precision Authentication and Autonomous Initial Rescue Execution This step uses drones as the primary execution unit to conduct close-range identification of suspicious targets and then carry out initial rescue operations after confirmation.

[0040] S301, Autonomous Flight and Target Localization of Unmanned Aerial Vehicles After receiving the mission data packet and confirming its mission readiness, the flight control computer initiates the autonomous takeoff procedure. The flight control computer reads the built-in global digital elevation model data, combines its current GPS location with the target coordinates in the mission data packet, and calls the fast extended random tree path planning algorithm to generate a flyable obstacle avoidance path in three-dimensional space consisting of hundreds of intermediate waypoints.

[0041] Driven by an electronic speed controller, the drone's rotor motors accelerate and rotate, taking off vertically to a preset safe altitude before entering the autonomous flight phase along a planned path. During flight, data from GPS, inertial measurement unit, barometric altimeter, and magnetometer are fused using a Kalman filter algorithm to obtain high-frequency, low-noise attitude estimation results.

[0042] S302. Multimodal visual verification and target attribute determination After the drone reaches the target coordinates, it enters position-keeping mode. The onboard mission management computer reads the ambient light sensor readings. If the reading is below 10 lux, the onboard high-definition infrared night vision pod is activated; if the ambient light sensor reading is above 10 lux, the high-definition zoom camera is activated first.

[0043] The acquired video stream is transmitted via an image transmission link to the unmanned surface vessel and a shore-based control platform for manual interpretation, and simultaneously input to an onboard edge computing module. The edge computing module contains a YOLOv7 object detection model that has undergone pruning, quantization, and operator optimization. The object detection model performs multi-scale feature extraction and bounding box regression prediction on the input video frames. When the confidence score of a bounding box predicted by the model exceeds 0.90, the edge computing module confirms the target attribute and sends the confirmation signal, target category label, and bounding box coordinates to the task management computer.

[0044] The edge computing module simultaneously performs a preliminary assessment of the target's state, evaluating the risk of hypothermia by analyzing the temperature distribution gradient and absolute temperature value of the target area in infrared thermal imaging; or by analyzing the amplitude and frequency of limb movements in visible light images to assess physical condition. The assessment results are appended to the confirmation signal in the form of enumerated values.

[0045] S303, Unmanned Aerial Vehicle (UAV) Autonomous Initial Rescue When the task management computer receives a target confirmation signal and the category label is a person who has fallen into the water or is in distress, it immediately triggers the preset autonomous preliminary rescue subroutine.

[0046] First, the drone uses its onboard laser rangefinder to measure its precise vertical distance from the sea surface. The flight control computer reads the current wind speed and direction data and calls a ballistic calculation function based on a mass kinematics and air resistance model. The function inputs include the drone's current altitude, wind speed, wind direction, the mass of the rescue equipment, and the estimated air resistance coefficient. The output is the coordinate offset relative to a forward deployment point directly below the drone. Based on this, the flight control computer adjusts the drone's horizontal position, hovering it directly above the calculated, precise deployment point.

[0047] Subsequently, the mission management computer sent an opening command to the attached emergency drop capsule. The electromagnetic lock was de-energized, and the capsule door opened under the action of a torsion spring. The lifebuoys carried inside the capsule fell freely under the action of gravity, and the distance between the landing point and the target personnel was controlled within ±1 meter.

[0048] After the lifebuoy is launched, the mission management computer sends a play command to the loudspeaker. The loudspeaker's built-in solid-state memory contains standardized life-saving instruction voice files, which are played in a loop. At the same time, the green laser pointer mounted on the side of the pan-tilt unit is activated, emitting a green laser beam with a wavelength of 532 nanometers. The light spot continuously illuminates the lifebuoy that has fallen into the water or the water nearby, forming a visual guidance marker.

[0049] S4, Unmanned Surface Vessel Dynamic Track Optimization and Adaptability Final Processing This step partially overlaps with S3 in terms of timing. While the drone is performing its mission, the unmanned surface vessel dynamically adjusts its trajectory based on the real-time information transmitted back by the drone and performs the final rescue operation.

[0050] S401, Dynamic Planning of Target Trajectory Based on Real-Time Information During the execution of S3 by the UAV, its onboard data terminal continuously transmits telemetry data streams back to the unmanned surface vessel (USV) at a frequency of 1Hz. These data streams include the target's precise latitude and longitude coordinates, target category label, and target status assessment value, all of which have been visually confirmed and corrected by the UAV. The USV's central controller receives and parses this data stream, then sends the dynamically updated target coordinates to the intelligent driving module in real time.

[0051] The intelligent driving module's path planning software unit switches its operating mode to a search and rescue target priority mode. In this mode, the improved A... The target point weight in the algorithm's heuristic function is significantly increased, while the collision avoidance cost weights associated with static and dynamic obstacles are correspondingly decreased. The algorithm tends to choose the straightest possible path towards the target, only maneuvering to avoid collisions when faced with a direct collision risk.

[0052] The two 200kW main water jet thrusters of the unmanned surface vessel (USV) received the command to operate at full power. The impellers of the water jet pumps of the thrusters rotated at the maximum rated speed, driving the USV to approach the target point at the highest safe speed.

[0053] S402, Adaptive Ultimate Rescue Response When the unmanned surface vessel detects that the distance to the target has been reduced to about 50 meters through its own electro-optical pod, the central controller automatically reduces the speed to the maneuvering speed.

[0054] The integrated electro-optical pod mounted on the bow of the submarine begins precise targeting of the target area. The pod integrates a high-definition visible light camera, a mid-wave infrared thermal imager, and a laser rangefinder. Once the operator or an automatic tracking algorithm locks onto the target, the pod's servo system automatically keeps the target centered in the frame. The laser rangefinder precisely measures the distance from the pod to the target at a frequency of 10Hz.

[0055] The control unit obtains the target status information evaluated and transmitted back by the UAV in S3 from the central controller. Based on the different target status information, it executes the preset decision logic: if the target status is a single person and the assessment is that the physical strength is normal, it decides to deploy a lifebuoy with a GPS positioning beacon; if the target status is multiple people or a single person and the assessment is that the physical strength is insufficient or there are signs of hypothermia, it decides to deploy an automatic inflatable life raft.

[0056] After the decision is made, the disposal control unit sends a control command to the electrically powered life-saving thrower installed at the bow. The base of the electrically powered life-saving thrower is an electromechanical servo gimbal that can rotate 360 ​​degrees horizontally and adjust its pitch angle from -10 degrees to 60 degrees, with a launch tube fixed on the gimbal. The disposal control unit first drives the gimbal motor to precisely align the launch tube with the target direction based on the target azimuth and pitch angle data provided by the electro-optical pod. Then, based on the target distance provided by the laser rangefinder and combined with the internally stored life-saving equipment ballistic firing tables, the disposal control unit automatically selects the required high-pressure gas cylinder release pressure.

[0057] The control unit issues a firing command, the solenoid valve opens instantly, and compressed gas from the high-pressure cylinder rushes into the rear of the launch tube, propelling the life-saving equipment placed inside at high speed. After the life-saving equipment hits the water, a water-sensitive sensor triggers an automatic inflation device, and the life raft inflates and unfolds within 3 seconds. The landing accuracy of the entire throwing process is controlled within ±2 meters.

[0058] S5. Mission Closed-Loop Confirmation and Coordinated Evacuation Guidance This step completes the finalization and status confirmation of the entire collaborative work process.

[0059] S501. Confirmation and Reporting of Rescue Status The unmanned surface vessel (USV) continuously observes the target area via its onboard electro-optical pod. The central controller operates an image analysis thread, analyzing the relative positions of personnel and rescue equipment in consecutive video frames to determine whether personnel have successfully boarded or grabbed the equipment. Upon confirmation of a successful initial rescue, the mission logging service in the central controller marks the mission status as "initial rescue completed" and packages all key data, including mission start time, target discovery time, rescue completion time, final target location, and type and quantity of deployed supplies, into a standard-format rescue completion report.

[0060] The report was automatically submitted via the satellite communication link of the unmanned surface vessel, using the standard interface provided by the National Maritime Search and Rescue Information System, thus completing the official mission filing.

[0061] S502, Cooperative Guidance and Multi-Link Communication Assurance If it is necessary to transfer rescued personnel to support vessels, the unmanned surface vessel (USV) will set its Automatic Identification System (AIS) to transmit, continuously broadcasting its position and navigation status. Simultaneously, a drone still hovering in the air will continuously illuminate the location of the life raft with its laser designator, providing visual guidance to distant rescue forces.

[0062] Throughout the collaborative operation, if there is no public network signal coverage in the operational sea area, the unmanned surface vessel (USV) and unmanned aerial vehicle (UAV) will automatically establish and maintain an integrated air-sea multi-link communication network. The USV's communication controller simultaneously manages the link with the Tiantong-1 satellite, the VHF radio link, and the air-sea data link with the UAV. After the UAV takes off, its onboard VHF signal relay repeater automatically activates, receiving VHF signals from the USV or other rescue vessels, amplifying and frequency-converting them before retransmitting to extend the VHF communication coverage.

[0063] The communication controller internally runs a link quality monitoring and automatic switching program, which polls and checks the signal-to-noise ratio, bit error rate, and transmission latency of each communication link every 1 second. When the signal-to-noise ratio of the 5G link is detected to be below a preset threshold or synchronization signals are continuously lost, the program immediately and seamlessly switches the data stream to the satellite link. Once the 5G signal is restored and its quality stabilizes, the program automatically switches the data stream back to the high-bandwidth 5G link. The entire switching process is transparent to upper-layer applications, and the end-to-end data transmission latency is controlled to within 2 seconds.

[0064] Example 2 This embodiment applies the method described in Embodiment 1 to a search and rescue scenario for fishing vessels that have lost contact in typhoon-affected sea areas, in order to demonstrate its execution process and effectiveness in an extremely realistic environment.

[0065] The incident occurred approximately 80 kilometers from the coast. Affected by the outer bands of the typhoon, the wind force reached level 7, and the waves were 4 meters high. A fishing boat carrying five crew members went missing. Upon receiving the alarm, the maritime search and rescue command center activated its emergency response and dispatched an unmanned surface vessel (USV) of this invention to carry out the search and rescue mission.

[0066] The unmanned surface vessel (USV) departed from Haikou Port. En route to the target area, its semi-submersible control module detected sea conditions exceeding a preset threshold using meteorological satellite data and onboard 3D wave sensors, automatically triggering a deep semi-submersible mode. Ballast tanks were filled, submerging the vessel to a depth of 8 meters, where the roll angle was suppressed to within 5 degrees. Upon reaching the area where contact was lost in this semi-submersible state, the intelligent driving module automatically selected a parallel search mode based on the rectangular search area, setting the route spacing to 180 meters. Side-scan sonar continued operating throughout the voyage, emitting 455kHz acoustic pulses underwater and receiving echoes.

[0067] After approximately one hour of searching, the side-scan sonar detected an anomalous echo with strong angular reflections and a distinct acoustic shadow at a depth of 30 meters underwater. A deep convolutional neural network model on the onboard data processing terminal analyzed the sonar waterfall diagram in real time, outputting the target category as shipwreck debris with a confidence level of 0.92. The terminal calculated the target's absolute coordinates (20°N, 110°E) and assigned a temporary number. The central controller generated a mission data packet containing the target's coordinates and type information, which was transmitted to the shore-based platform via satellite link and simultaneously to the onboard UAV-8S unmanned aerial vehicle (UAV) via a 5.8GHz air-sea data link. Subsequently, the semi-submersible control module initiated the surfacing procedure, and the ballast water was discharged at a flow rate of 50 L / min, allowing the vessel to surface within 10 minutes. The UAV hangar door opened, and the attitude control system maintained the roll angle within 5 degrees.

[0068] The drone took off autonomously in strong winds and hovered after reaching the target coordinates. Due to low visibility, the mission management computer automatically activated the IR-800 infrared night vision pod. Thermal imaging clearly showed two humanoid heat sources floating on the water. The YOLOv7 model on the edge computing module confirmed the two people in the water with a confidence level of 0.95 and assessed their condition as exhaustion. The drone triggered a preliminary rescue subroutine, using laser ranging and ballistic calculations to precisely drop lifebuoys with positioning capabilities from the emergency drop pod to the vicinity of the two crew members in two separate operations. A loudspeaker continuously played reassuring messages, and a green laser pointer continuously illuminated the location of the lifebuoys.

[0069] The unmanned surface vessel (USV) received real-time target coordinates from the drone, and its intelligent driving module switched to search and rescue target priority mode, planning the shortest approach path. Both 200kW main waterjet propulsion units operated at full power, propelling the USV towards the target at a speed of 30 knots. Approximately 25 minutes later, it approached to within 50 meters, reducing its speed to 5 knots. The electro-optical pod locked onto the target, and the response control unit, based on the "exhaustion" status reported by the drone, decided to deploy a 6-person self-inflating life raft. The JL-50 electric life-saving throwing device, aided by electro-optical aiming and ballistic compensation, precisely launched the life raft between the two crew members. The life raft automatically inflated and deployed within 3 seconds of hitting the water. Guided by drone voice commands, the two crew members successfully boarded the raft.

[0070] After the unmanned surface vessel (USV) confirmed that the crew had boarded the raft via its electro-optical pod, the mission recording service generated a rescue completion report, including mission time, location, and deployed supplies. This report was automatically uploaded to the National Maritime Search and Rescue Information System via satellite link. The USV established communication with the arriving coast guard vessel via VHF channel 16, maintaining laser guidance to direct the crew transfer. Throughout the process, there was no public network signal in the operating area, and the communication system automatically operated in satellite plus VHF link mode. The USV acted as a VHF relay node to extend communication coverage, and the end-to-end data transmission latency remained within 2 seconds. Ultimately, two of the five crew members of the missing fishing vessel were successfully rescued, and the locations of the remaining three victims were also pinpointed.

[0071] This application example fully demonstrates the execution process of the method under extreme sea conditions, and verifies the feasibility of technical features such as deep semi-submersible wave resistance, closed-loop collaborative operation, and multi-link communication assurance in real rescue scenarios, which significantly improves search and rescue efficiency compared to traditional methods.

[0072] Example 3: A Collaborative Operation System for Unmanned Surface Vessels and Unmanned Aerial Vehicles This embodiment provides a collaborative operation system for unmanned surface vessels (USVs) and unmanned aerial vehicles (UAVs). The system consists of three main parts: an USV, at least one UAV, and a shore-based control platform. It forms an integrated sea-air collaborative operation network through multiple wireless communication links. Figure 2 As shown, it specifically includes: Unmanned Surface Vessel Unmanned surface vessels (USVs) are the core surface platform and mobile command node of the entire system.

[0073] In terms of hull structure, the unmanned surface vessel (USV) adopts a manta ray-inspired monohull structure with a total length of 16 meters, a beam of 4.8 meters, and a design draft of 1.2 meters. The bow features a 0.8-meter-high, 15-degree outward-sloping wave-breaking bulwark. At the stern, there are two fixed stabilizing fins, each 1.2 meters long with a symmetrical airfoil profile, on either side. The hull is a deep V-shape, with the lateral lift angle gradually transitioning from 18 degrees mid-ships to 24 degrees stern. The main hull is constructed using modified domestically produced T1100 carbon fiber composite material with 2% nano-silica particles added by mass, manufactured through a vacuum-assisted resin transfer molding process. The critical pressure bulkhead thickness is 15 millimeters. All external hatch covers, cable penetrations, and shaft seals are designed and tested to IP68 protection standards. Two automatically backup pumps are installed at the bottom of the critical equipment compartment, each with a rated flow rate of 50 L / min, controlled by a water level sensor-linked controller.

[0074] In terms of power and energy systems, the unmanned surface vessel (USV) adopts a "2 main, 1 backup" power redundancy architecture. The two main thrusters are 200kW waterjet propulsion units, symmetrically mounted on the port and starboard sides of the stern. They are driven directly by motors to a multi-stage axial-flow pump impeller, achieving thrust vectoring through deflectable nozzles. The emergency thruster, model QDJ-100, with a rated power of 100kW, is a retractable pod thruster installed in a recess 0.5 meters from the baseline in the middle of the hull. During normal navigation, the pod is retracted into the recess and closed by a hydraulically operated flap door. When the central controller detects a main thruster malfunction, it sends a command to the hydraulic system to open the flap door, and an electric push rod extends the pod out from under the hull into its working position; the entire deployment process is completed within 5 seconds. The energy system consists of a 600kWh lithium iron phosphate battery pack, composed of multiple battery modules connected in series and parallel. Each module has an independent battery management system slave control unit. The main battery management system controller aggregates data from each slave control unit, estimates the overall state of charge, and communicates with the central controller via the controller local area network bus. The system has a built-in search and rescue mode energy management strategy: when the state of charge drops to 20%, the power supply to low-priority loads is automatically cut off by controlling the solid-state relays in the load distribution cabinet; when the state of charge drops to 10%, all non-highest priority loads are further cut off to ensure that the core equipment is powered for no less than 4 hours.

[0075] In terms of the semi-submersible control module, the perception layer consists of two sensor subsystems: one is a data receiving terminal for the Fengyun-4 meteorological satellite with a 0.6-meter diameter parabolic antenna; the other is six three-dimensional wave sensors installed on the bow, port and starboard sides (forward, mid- and aft), each integrating a three-axis accelerometer and a high-precision pressure sensor, with a sampling frequency of 100Hz. The decision layer is an embedded industrial control computer running a sea state-resistant control algorithm based on model predictive control. The execution layer is the ballast water system, including four independent ballast water tanks, inlet and outlet pipes, electrically controlled valves, and four high-flow seawater pumps. When the decision layer determines that the sea state has reached the trigger condition, it issues a command to the execution layer to submerge the hull to a depth of 8 to 12 meters through injection and discharge control.

[0076] In terms of sensing and handling payloads, the multi-dimensional sensing system includes: an SSS-50 side-scan sonar installed on the underwater side of the midship section of the hull, with a towed transducer array fixed by vibration-damping brackets; and a BR-100 rescue beacon receiver installed on the top of the superstructure, capable of simultaneously demodulating 121.5MHz and 406MHz distress beacon signals. The handling module includes a JL-50 electric rescue throwing device installed on the bow deck, with a base that can rotate 360 ​​degrees horizontally and adjust pitch from -10 degrees to +60 degrees. The launch power comes from replaceable compressed carbon dioxide high-pressure cylinders, and the release pressure is controlled by an electromechanical proportional valve. A closed UAV hangar is located at the stern, capable of accommodating two UAV-8S multi-rotor UAVs. The hangar integrates an automatic centering device, a fast-charging plate based on a wireless charging protocol, and a servo-motor driven top sliding hatch.

[0077] drones The UAV-8S model, a six-rotor drone, serves as the system's aerial sensing and rapid response node.

[0078] Regarding the mission payload, the visual perception payload is integrated into a high-precision three-axis self-stabilized gimbal, including: an IR-800 high-definition infrared night vision pod, employing a 640x512 resolution uncooled vanadium oxide focal plane detector, operating in the 8-14 micrometer wavelength range; and a GC-500 high-definition zoom camera, using a 5-megapixel CMOS sensor and a 30x optical zoom lens. Both payloads are connected to the onboard mission management computer via a high-speed serial interface. The initial rescue payload includes: an emergency drop capsule mounted under the fuselage via two electromagnetic latches, capable of carrying two independent roll-up single-person lifebuoys, each integrating a miniature global navigation satellite system positioning module and a water-activated lithium battery; a directional high-volume broadcaster mounted on the side of the fuselage, with a maximum sound pressure level of 100dB (measured at 1 meter), and built-in solid-state memory pre-stored standardized rescue commands; and a green laser designator mounted on the side of the gimbal, emitting at a wavelength of 532 nanometers.

[0079] In terms of avionics systems, the flight control computer is responsible for low-level attitude stabilization, flight control, and navigation, while the mission management computer is responsible for high-level mission scheduling, payload control, and collaborative logic execution. The mission management computer internally stores and runs the executable code for the target confirmation subroutine and the initial rescue subroutine. The onboard data terminal maintains two-way communication with the unmanned surface vessel via a 5.8GHz air-sea data link.

[0080] shore-based control platform The shore-based control platform is deployed at the maritime search and rescue command center and serves as the system's remote command and monitoring node.

[0081] The hardware components include: a rack-mounted high-performance server, multiple dual-screen operator workstations, and a large-screen display wall composed of multiple LCD displays. The server is connected to the data interface of the National Maritime Search and Rescue Information System via a dedicated fiber optic line, and also maintains a connection with the Tiantong-1 satellite system through a rooftop satellite ground station.

[0082] The core software component is the "Maritime Search and Rescue Command Panel" software system, which adopts a browser / server architecture. Functional modules include: an electronic chart display and plotting module, which overlays the positions and trajectories of unmanned surface vessels (USVs), drones, search and rescue targets, and support vessels onto the chart in real time; a task management and issuance module, allowing operators to generate and issue task commands with a single click by selecting areas or clicking locations; a video and data monitoring module, which receives, decodes, and displays high-definition video streams and sensor data transmitted from USVs and drones; and a search and rescue emergency takeover module, which, once activated, establishes a low-latency remote control channel with the USV via a virtual private network. Control commands issued by the operator via joystick, keyboard, and mouse are sent to the USV's central controller with the highest priority via the server and satellite link, with end-to-end response latency controlled within 100 milliseconds.

[0083] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for collaborative operation of unmanned surface vessels and unmanned aerial vehicles, characterized in that, Includes the following steps: S1. Autonomous cruise and wide-area target detection of unmanned surface vessels: The unmanned surface vessel receives mission instructions from the shore-based system and navigates autonomously in the target sea area in a fan-shaped search mode or a parallel search mode. It collects environmental data and identifies targets through the onboard side-scan sonar and navigation radar. After discovering a suspicious target, it calculates its absolute coordinates. S2. The collaborative mission is initiated and the unmanned surface vessel (USV) and unmanned aerial vehicle (UAV) missions are handed over. The USV sends a mission data package containing the coordinates of the suspected target and the initial screening type information to the shore-based platform and the UAV mounted on the USV via satellite link and air-sea data link, respectively. If the USV is in deep semi-submersible mode, it will automatically surface and open the UAV hangar door and suppress the hull roll angle to takeoff conditions through the attitude control system based on inertial measurement unit feedback carried by the USV. S3. Precise UAV Authentication and Autonomous Initial Rescue Execution: After receiving the mission data packet, the UAV takes off autonomously and flies to the target area. It collects target images through the onboard visual payload and uses the target detection model to confirm the target category. When the target is confirmed to be a person to be rescued, the UAV autonomously executes the initial rescue subroutine, including deploying life-saving equipment with positioning function and providing audio-visual guidance. S4. Dynamic trajectory optimization and adaptation final processing of unmanned surface vessels: The unmanned surface vessel receives the real-time coordinates and status assessment information of the target transmitted back by the drone, switches the trajectory planning to the search and rescue target priority mode and sails towards the target area; upon arrival, it makes decisions based on the target status assessment information and deploys the appropriate type of rescue equipment. S5. Mission closed-loop confirmation and coordinated evacuation guidance: After the unmanned surface vessel confirms the successful rescue, it generates a rescue report and automatically reports it; if personnel transfer is required, the unmanned surface vessel broadcasts its own position, and the drone uses laser pointers to visually guide the target position.

2. The method according to claim 1, characterized in that, In step S1, the sector search mode is: taking the known target point coordinates as the center, a set of sector scanning lines covering a preset central angle are generated, and the sonar detection range between adjacent scanning lines has a preset connection overlap rate; the parallel search mode is: the spacing between adjacent parallel lines is determined according to the effective single-side scanning width of the side-scan sonar, and the spacing between lines is the product of the single-side scanning width and the preset overlap coefficient.

3. The method according to claim 1, characterized in that, In step S2, the semi-submersible mode is as follows: the ballast tanks of the unmanned surface vessel are filled with water to a preset capacity ratio, and the hull is located at a preset underwater depth range; the surfacing procedure is as follows: the ballast tank filling valves are closed, and the drainage pumps are started to discharge the ballast water until the water level in each ballast tank drops below a preset empty threshold; the attitude control system uses the angular velocity and acceleration data output by the inertial measurement unit to calculate the anti-roll torque using a PID controller, and adjusts the direction and thrust of the tail water jet propulsion nozzles and the angle of attack of the tail stabilizing fins by differential adjustment, so that the hull roll angle meets the takeoff conditions of the unmanned surface vessel.

4. The method according to claim 1, characterized in that, In step S3, the specific execution process of the preliminary rescue subroutine is as follows: the UAV measures the vertical distance to the sea surface using a laser rangefinder, the flight control computer reads wind speed and direction data, calls the ballistic calculation function to calculate the coordinate offset of the forward delivery point, and hovers directly above the delivery point after adjusting the horizontal position. Send an opening command to the emergency drop chamber, release the electromagnetic locking pin, and the rescue equipment falls freely; after the drop is completed, the loudspeaker plays the pre-stored rescue guidance voice in a loop mode, and the green laser pointer emits a laser beam, with the light spot continuously illuminating the location where the rescue equipment fell into the water.

5. The method according to claim 1, characterized in that, In step S4, the search and rescue target priority mode is: in improved A In the cost function of the algorithm, the weight of the target point heuristic function term is increased, while the weight of the collision avoidance cost terms related to static and dynamic obstacles is reduced. The decision logic of the adaptive type of life-saving equipment is as follows: if the target state is a single person with normal physical strength, a life ring with a positioning beacon is deployed; if the target state is multiple people, or a single person with insufficient physical strength or signs of hypothermia, an automatically inflatable life raft is deployed.

6. The method according to claim 1, characterized in that, Throughout the collaborative operation, the unmanned surface vessel and the unmanned aerial vehicle (UAV) communicate through a multi-link communication network consisting of a 5G communication module, a satellite terminal, a VHF relay module, and an air-sea data link. After the UAV takes off, its onboard VHF relay transponder is automatically activated as an airborne auxiliary communication node. The communication controller monitors the quality indicators of each link, and when the quality of the first link is detected to be lower than the preset conditions, it automatically switches the data stream to the second link.

7. A collaborative operation system for unmanned surface vessels and unmanned aerial vehicles, the system performing the method as described in any one of claims 1 to 6, characterized in that, This includes unmanned surface vessels, at least one drone, and a shore-based control platform; The unmanned surface vessel includes a central controller, an intelligent driving module, a multi-dimensional perception system, a semi-submersible control module, a disposal module, a communication module, and an onboard UAV library, used to perform maritime patrol, target detection, mission data packet generation and distribution, UAV release control, dynamic trajectory optimization, and final rescue disposal. The drone, mounted on the unmanned surface vessel, includes a flight control computer, a mission management computer, a visual perception payload, a preliminary rescue payload, and an airborne data terminal, used to receive mission data packets, fly to the target, perform visual confirmation, perform preliminary rescue, and transmit information back. The shore-based control platform is communicatively connected to the unmanned surface vessel and is used for mission issuance, remote monitoring and emergency takeover. The unmanned surface vessel and the unmanned aerial vehicle communicate with each other via an air-sea data link, forming a collaborative operation network.

8. The system according to claim 7, characterized in that, The unmanned surface vessel has a hull made of carbon fiber composite material, featuring a manta ray-inspired deep-V monohull structure with a stabilizing fin at the tail. Its propulsion system includes two main waterjet propulsion units and one emergency pod propulsion unit. The energy system is a lithium iron phosphate battery pack and is equipped with a search and rescue mode energy management strategy. The semi-submersible control module includes a meteorological satellite data receiving terminal, a three-dimensional wave sensor, a model predictive control-based anti-sea state control algorithm, and a ballast water system.

9. An electronic device comprising a processor, a memory, and a computer program stored in the memory, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 6.

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