Multi-mode wave-propelled unmanned vehicle control system

Abstract

The invention discloses a multi-mode wave-propelled unmanned vehicle control system, relates to the technical field of unmanned autonomous system control, and is used for controlling a multi-mode wave-propelled unmanned vehicle comprising a high lift-drag ratio pressure-resistant structure vehicle main body, a dynamic buoyancy adjusting module, a multifunctional intelligent sensing and communication system and a dual-mode propelling system. According to the control system, an aircraft onboard control subsystem and a shore-based control subsystem are integrated, and the two subsystems cooperatively work through an optimized link. The onboard subsystem is used for realizing accurate dynamic buoyancy adjustment; and collision is efficiently and autonomously avoided. The shore-based subsystem is characterized in that adaptive communication link optimization and dynamic management are realized; carrying out local processing and analysis on the aircraft data by utilizing the shore-based edge calculation capability; and on-demand dynamic reconstruction of the shore-based function is realized. According to the system, the multi-mode operation capability, the autonomous collision avoidance safety, the communication and data processing efficiency, the task adaptation flexibility and the overall performance of the unmanned aircraft are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned autonomous system control, and in particular to a multi-modal wave-propelled unmanned vehicle control system. Background Art

[0002] Wave-propelled unmanned vehicles (such as wave gliders) use renewable wave energy to achieve ultra-long endurance operations and have great potential in fields such as marine environmental monitoring and resource exploration.

[0003] However, existing technologies face many challenges that limit their effectiveness and scope of application. Specific issues are as follows:

[0004] 1. Limited navigation mode and survivability: Traditional wave gliders are mostly surface platforms that lack diving capabilities. They are unable to circumvent adverse sea conditions, strong surface currents, or effectively avoid surface collision threats, and cannot operate covertly.

[0005] Second, there is a lack of precise multi-modal motion control: Achieving stable switching between surface, near-surface, and underwater modes and precise depth maintenance requires advanced dynamic buoyancy adjustment capabilities, which are generally lacking in existing technologies.

[0006] 3. Collision avoidance strategies are inefficient and not adapted to platform characteristics: Wave-propelled platforms have low speeds and poor maneuverability. Traditional collision avoidance strategies that rely on horizontal avoidance are difficult to handle dynamic targets on the water surface. Poor platform stability also affects the performance of sensing equipment.

[0007] 4. Bottlenecks in shore-based control communications and data processing: Long-duration missions generate large amounts of data, placing high demands on shore-based communication links (especially satellite links). Existing shore-based systems lack intelligence in link selection and tend to transmit raw data back, resulting in high bandwidth pressure and delayed decision-making.

[0008] 5. The shore-based system has rigid functions and poor mission adaptability: Faced with diversified tasks, the existing shore-based system is difficult to flexibly and quickly adapt to new data processing or mission support functions. Summary of the Invention

[0009] The technical problem to be solved by the present invention is to provide a multimodal wave-propelled unmanned vehicle control system that can accurately control the multimodal motion of the vehicle, achieve efficient autonomous collision avoidance under its low-speed characteristics, intelligently optimize shore-based communications and process massive data, and flexibly adapt to diverse mission requirements.

[0010] The technical solution of the present invention is achieved as follows:

[0011] A multi-mode wave-propelled unmanned vehicle control system is used to control a multi-mode wave-propelled unmanned vehicle (including a wave drive unit and a vector propeller) comprising a high lift-to-drag ratio pressure-resistant structure vehicle body (including a wing-body fusion shape or a rotating body with a large wingspan), a dynamic buoyancy adjustment module (including a ballast water tank and a pump-valve assembly), a multi-function intelligent perception and communication system (including a multi-source collaborative perception module and a multi-mode communication module), and a dual-mode propulsion system.

[0012] The control system includes a vehicle onboard control subsystem and a shore-based control subsystem;

[0013] The onboard control subsystem of the vehicle runs on a controller inside the vehicle body. The subsystem is configured to perform:

[0014] I. Dynamic Buoyancy Adjustment Control: Utilizing the dynamic buoyancy adjustment module, the ballast water volume is precisely controlled through a dual closed-loop control method based on a fuzzy adaptive PID. This method includes: acquiring the current depth and vertical velocity in real time; calculating the error relative to the target depth and velocity; inputting the error into a fuzzy adaptive PID algorithm, which dynamically adjusts the PID parameters based on a preset fuzzy rule base (e.g., adjusting PID parameters based on the error magnitude) to adapt to hydrodynamic changes and disturbances; generating control instructions for the pump and valve components based on the adjusted PID parameters, adjusting the ballast water volume, achieving precise control of the dive speed and depth, and supporting the stable switching and maintenance of the vehicle between surface, near-surface, and underwater modes.

[0015] II. Efficient Autonomous Collision Avoidance Control: Utilizing the multi-source collaborative perception module (integrated with AIS, millimeter-wave radar, and cameras) of the multifunctional intelligent perception and communication system, the target confidence and situation are judged through preset weighted fusion to establish a graded threat response mechanism. This mechanism triggers at least one of the following actions based on the calculated target distance and / or collision risk level: level one alert (e.g., folding the mast and lowering the feature at long distances), level two alert (e.g., pre-buoyancy system at medium distances), and level three alert (e.g., utilizing the dynamic buoyancy adjustment capability of step a) to perform an emergency dive at close ranges to achieve vertical collision avoidance).

[0016] III. Dual-mode propulsion coordinated control: Based on the navigation status (such as speed, route deviation) and wave energy conversion efficiency, the wave drive unit and vector thruster are coordinated and controlled. When necessary (such as when the speed is below the threshold and the yaw exceeds the limit), the vector thruster is activated to provide auxiliary thrust or the vector thruster is powered off and switched to active propulsion mode to ensure basic maneuverability and route tracking capabilities during multi-mode conversion or collision avoidance.

[0017] The shore-based control subsystem includes a shore-based control center, a built-in multi-mode communication interface group, at least one generalized expansion interface, and shore station core software. This subsystem is configured to work in cooperation with the on-board control subsystem of the vehicle and achieve the following:

[0018] Ⅰ. Intelligent communication link optimization and management: The shore station core software includes a communication link intelligent decision-making engine. Based on multi-dimensional information obtained from the multi-dimensional state perception module (at least including the quality, cost of each available link, and the state of the vehicle such as battery power, task priority, and data type to be transmitted), it automatically selects the optimal communication link or combination to communicate with the vehicle according to the strategy, and realizes dynamic switching through the link seamless switching execution unit;

[0019] Ⅱ. Shore-based edge data processing: The shore-based control center uses its processing unit to run the shore-based edge data processing module group in the shore station core software to perform local processing (such as compression, feature extraction, and target pre-screening) on the data received from the vehicle (such as sonar images, video streams), reducing the transmission burden and accelerating information acquisition;

[0020] Ⅲ. Dynamic function reconstruction: Connect pluggable dedicated task processing adaptation modules (such as RTK solution modules, underwater acoustic signal processing modules) through the generalized expansion interface, and the dynamic function loading and management mechanism of the shore station core software automatically identifies, loads, and integrates their functions, enabling the shore-based subsystem to be reconfigured as needed to support specific tasks executed by the vehicle;

[0021] Among them, the on-board control subsystem of the vehicle and the shore-based control subsystem perform two-way information interaction through the intelligently optimized communication link to achieve remote monitoring, command issuance, status reporting, data transmission, and collaborative task execution.

[0022] After adopting the above technical solutions, the beneficial effects of the present invention are as follows:

[0023] 1. Improve the multi-modal operation ability and environmental adaptability of the vehicle: Precise dynamic buoyancy control enables the vehicle to operate flexibly on the water surface, near the water surface, and underwater, adapting to different task requirements and marine environments;

[0024] 2. Significantly improve the safety of autonomous collision avoidance: Combining multi-source perception fusion and innovative vertical diving avoidance strategies effectively solves the problem that it is difficult for low-speed wave propulsion platforms to avoid dynamic obstacles on the water surface;

[0025] 3. Enhance concealment and survivability: The multi-modal ability combined with mast folding and diving collision avoidance can actively reduce the exposure characteristics and avoid surface threats and severe sea conditions;

[0026] 4. Optimize communication efficiency and data processing efficiency: The intelligent link optimization on the shore improves communication reliability and efficiency, and shore-based edge processing reduces the data transmission pressure and accelerates information acquisition and decision-making;

[0027] 5. Enhance system flexibility and mission adaptability: The shore-based dynamic function reconfiguration ability enables the entire system to quickly and economically adapt to diverse mission requirements, improving the system's scalability and lifecycle value;

[0028] 6. Achieve system collaborative optimization: By organically combining advanced on-board control strategies, unique vehicle platform capabilities, and intelligent shore-based management functions, the overall system performance improvement of 1 + 1 > 2 is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0030] Figure 1 It is a three-dimensional structure diagram of a multi-modal vehicle (with a wing-body fusion shape);

[0031] Figure 2 It is a three-dimensional structure diagram of a multi-modal vehicle (with a body of revolution plus wings);

[0032] Figure 3 For Figure 1 the internal structure diagram of the vehicle body in

[0033] Figure 4 It is a schematic diagram of the multi-modal navigation of the vehicle;

[0034] Figure 5 It is a working principle diagram of the dynamic buoyancy adjustment module;

[0035] Figure 6 It is a working principle diagram of the multi-functional intelligent perception and communication system;

[0036] Figure 7 It is a flow schematic diagram of the dynamic buoyancy adjustment method;

[0037] Figure 8 It is a flow schematic diagram of the efficient collision avoidance method;

[0038] Figure 9 It is a schematic diagram of the overall architecture of the shore-based control subsystem;

[0039] Figure 10 It is a schematic diagram of the main internal function modules and their interaction relationships of the core software of the shore-based control subsystem;

[0040] Figure 11Schematic diagram of the shore-based control subsystem accessing different types of adapter modules through a generalized expansion interface to achieve dynamic function reconstruction;

[0041] Markings in the figure: 100 - Shore-based control center; 110 - Core processor unit; 115 - Enhanced processing unit; 120 - Internal data exchange module; 130 - Energy management module; 140 - Basic display and control interface module; 150 - Satellite communication terminal; 160 - Radio communication module; 170 - Broadband wireless transmission module; 180 - Underwater acoustic communication machine interface module; 190 - Wired connection interface; 195 - Generalized expansion interface; 197 - Communication adapter module; 198 - Special task processing adapter module; 198a - RTK module; 198b - Underwater acoustic processing module; 198c - AIS module;

[0042] 200 - Maritime unmanned autonomous system;

[0043] 300 - Portable display and control terminal;

[0044] 400 - Shore station core software; 401 - Multi-dimensional state perception module; 402 - Communication link intelligent decision-making engine; 403 - Link seamless switching execution unit; 404 - Shore-based edge data processing module group; 405 - Lightweight intelligent analysis module; 406 - Dynamic function loading and management mechanism; 410 - Task template management module;

[0045] 500 - Vehicle body; 501 - Dynamic buoyancy adjustment module; 502 - Multi-functional intelligent perception and communication system; 503 - Dual-mode propulsion system. Detailed implementation mode

[0046] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0047] I. Characteristics of the vehicle platform (basis of the control system)

[0048] The vehicle applied in this control system has the following key characteristics, which are the basis for realizing advanced control:

[0049] I. Vehicle body 500: Adopts wing-body fusion (refer to Figure 1 ) or a body of revolution plus wings (refer to Figure 2 ) design, with good hydrodynamic performance and stability. The pressure-resistant structure allows it to dive to a predetermined depth (for example, 200 meters); The airfoil design (such as the NACA asymmetric airfoil) helps to utilize wave energy (refer toFigure 4 )

[0050] II. Dynamic buoyancy adjustment module 501: Integrated inside the first section (refer to Figure 3 ), including a ballast tank and a pump valve assembly (refer to Figure 5 ), which is the core actuator for realizing vertical motion control.

[0051] III. Multifunctional intelligent perception and communication system 502: Can be foldably deployed on the upper surface of the vehicle body 500, integrating multi-source sensors (AIS, millimeter-wave radar, camera, refer to Figure 6 ) and multimode communication units (such as satellite, wireless), which is the basis for environmental perception, collision avoidance decision-making, and communication with shore-based stations.

[0052] IV. Dual-mode propulsion system 503: Connected to the lower part of the vehicle body 500, which combines a wave-driven unit and a vector thruster. The wave-driven unit provides long-endurance power, and the vector thruster provides the necessary active control ability.

[0053] 2. Onboard control subsystem (controller running inside the vehicle body 500)

[0054] I. Dynamic buoyancy adjustment control (refer to Figure 5 , Figure 7 ):

[0055] Obtain the current depth d_current and vertical speed v_current in real time (S501);

[0056] Calculate the errors e_d and e_v with the target depth d_target and target speed v_target (S502);

[0057] Input the errors into the fuzzy adaptive PID controller (S503); This controller dynamically adjusts the P, I, D parameters according to the preset fuzzy rules (if |e_w|>0.025L, |e_v|>0.1m / s, |e_d|>0.02m, then increase Kp), which overcomes the limitations of fixed-parameter PID in nonlinear and time-varying systems;

[0058] Calculate the control command u(t) (S504), drive the pump valve to adjust the water volume in the ballast tank (S505), change the buoyancy, and realize the double closed-loop control of depth and speed (S506);

[0059] This function is the key to realizing multi-modal (refer to 4) switching and vertical collision avoidance.

[0060] II. Efficient autonomous collision avoidance control (refer to Figure 6 , Figure 8 ):

[0061] Multi-source sensors (AIS, radar, camera) detect surrounding targets in real time (S601);

[0062] The controller fuses data (S602), for example, calculates the target confidence, distance D_target, and situation using weighted average (such as AIS 0.3, radar 0.4, camera 0.3 weights);

[0063] Execute hierarchical response (S603):

[0064] Level 1 (such as D_target > 300m): Fold the mast (S604a) to reduce the signature;

[0065] Level 2 (such as 150m < D_target <= 300m): Prepare the buoyancy system (S604b) to prepare for rapid response;

[0066] Level 3 (such as D_target <= 150m): Trigger an emergency dive (S604c), instruct the dynamic buoyancy adjustment module 501 to execute a rapid dive to a safe depth (such as 50 meters), which is the core of using the unique capabilities of the platform for efficient collision avoidance;

[0067] Report the status through the communication module (S605).

[0068] III. Dual-mode propulsion collaborative control: The controller monitors the ship speed and course deviation; when the wave energy is insufficient and the ship speed is lower than the threshold (such as 0.2 knots) and the course deviation exceeds the threshold (such as 200 meters), the vector thruster is automatically started to compensate for the thrust at a set power (such as 150 - 300W) to maintain the course tracking accuracy; during the collision avoidance dive / ascent process, if necessary, the vector thruster can also be started to assist in maneuvering.

[0069] III. Shore-based control subsystem (refer to Figure 9 , Figure 10 , Figure 11 ):

[0070] I. Architecture: The shore-based control center 100 is the core, integrating a processor (such as GPU / FPGA), a multi-mode communication interface (such as the Beidou / Tiantong integrated terminal providing dual-satellite link redundancy), a general expansion interface, and running the shore station core software 400. A portable display and control terminal can be optionally configured.

[0071] II. Intelligent communication link optimization and management:

[0072] The status perception module collects the real-time quality (RSSI, SNR, RTT, bandwidth), cost of all available links, and the status (battery power, mission phase, data type) transmitted from the vehicle.

[0073] The intelligent decision-making engine runs an optimization algorithm (such as weighted scoring) to calculate the utility of each link according to the selected strategy (such as "lowest cost", "highest reliability", "lowest latency" or a composite strategy defined based on a task template), and selects the optimal link (or combination, such as controlling to use satellite and data to use 4G).

[0074] The link switching unit performs automatic and seamless (such as first connect then disconnect) switching.

[0075] III. Shore-based edge data processing:

[0076] When the vehicle transmits a large amount of data (such as sonar waterfall diagrams, high-definition videos) through a high-bandwidth link, the edge processing module group of the shore-based control center 100 performs local processing. For example:

[0077] Video stream: Perform real-time target detection (such as using the YOLO model), only upload target metadata and screenshots, or upload the compressed original video according to instructions.

[0078] Sonar data: Perform preliminary processing, such as extracting seabed classification features, reducing the amount of data that needs to be manually interpreted or finely processed at the backend.

[0079] This significantly reduces the demand for communication bandwidth (especially expensive satellite links) and accelerates the extraction of key information.

[0080] IV. Dynamic function reconstruction:

[0081] The general expansion interface is the key. When specific task support is required (such as high-precision positioning or specific underwater acoustic analysis), the corresponding dedicated task processing adaptation module 198 can be inserted into this interface. For example, insert the RTK base station module (refer to Figure 11 ).

[0082] The dynamic loading mechanism automatically detects the module, identifies its function (such as through a device descriptor), and loads the driver and application plug-ins.

[0083] The shore station software interface automatically integrates the RTK base station management function, enabling the shore-based system to have the ability to broadcast differential data to the vehicle. After the task is completed, the module is unplugged and the function is automatically unloaded.

[0084] This enables the shore-based system to flexibly adapt to the diverse tasks performed by the vehicle without having to re-develop or purchase a brand-new system. The task template management module 410 can pre-store the configurations (communication strategies, edge processing processes, required adaptation modules) required for specific tasks.

[0085] IV. System collaborative work example

[0086] Ⅰ. Task Planning and Startup: The operator loads the "Seabed Topography Survey" task template in the shore-based subsystem. The template requires connecting the RTK base station module and enabling sonar data edge compression processing. The shore-based system sends task instructions to the vehicle via an intelligently optimized link.

[0087] Ⅱ. Navigation and Operation: The vehicle sails along the planned route, uses dynamic buoyancy control to maintain the optimal operation depth; the dual-mode propulsion system 503 ensures route tracking; sonar data is transmitted back to the shore-based via an optimized link.

[0088] Ⅲ. Shore-based Processing and Support: The shore-based system receives data, and the edge processing module performs sonar data compression. At the same time, the RTK module 198a broadcasts differential correction data to the vehicle via an optimized link to ensure positioning accuracy.

[0089] Ⅳ. Autonomous Collision Avoidance and Reporting: The vehicle's perception system detects approaching ships. The on-board collision avoidance logic triggers responses based on the distance: first, fold the mast (level 1), then prepare the buoyancy system (level 2), and finally execute an emergency dive (level 3), and report the collision avoidance event and status to the shore-based via an optimized link (d).

[0090] Ⅴ. Remote Intervention and Mode Switching: The shore-based operator receives an alarm and can monitor the collision avoidance process on the shore-based interface. When necessary, remote instructions can be sent via the satellite link, such as commanding the vehicle to dive to a deeper depth or surface.

[0091] In summary, through the deep integration and intelligent collaboration of the on-board subsystem and the shore-based subsystem, a powerful, adaptable, safe and reliable multi-modal wave propulsion unmanned vehicle control system is constructed.

[0092] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A multi-modal wave propulsion unmanned vehicle control system for controlling a multi-modal wave propulsion unmanned vehicle comprising a high lift-drag ratio pressure-resistant structure vehicle body, a dynamic buoyancy adjustment module, a multi-functional intelligent perception and communication system, and a dual-mode propulsion system; Characterized in that, The control system includes an on-vehicle control subsystem of the vehicle and a shore-based control subsystem; The on-vehicle control subsystem of the vehicle runs on a controller inside the vehicle body, and is configured to at least execute: Ⅰ. Dynamic buoyancy adjustment control: Using the dynamic buoyancy adjustment module, through a double closed-loop control method based on fuzzy adaptive PID, precisely regulate the ballast water volume to control the depth and vertical speed of the vehicle, and achieve stable switching and maintenance of multi-modal motion; Ⅱ. Efficient autonomous collision avoidance control: Using the multi-source collaborative perception module of the multi-functional intelligent perception and communication system, fuse sensor data for target detection and situation assessment, and according to a hierarchical threat response mechanism, when it is judged that there is a high collision risk, instruct the dynamic buoyancy adjustment module to execute an emergency diving action for vertical collision avoidance; Ⅲ. Dual-mode propulsion collaborative control: According to the navigation state and wave energy conversion efficiency, collaboratively control the wave drive unit and the vector thruster, and start the vector thruster to provide auxiliary thrust when necessary or power off the vector thruster and switch to the active propulsion mode to ensure the basic maneuverability and route tracking ability during multi-modal conversion or collision avoidance; The shore-based control subsystem includes a shore-based control center, a built-in multi-mode communication interface group, at least one generalized expansion interface, and shore station core software, and is configured to work in cooperation with the on-vehicle control subsystem of the vehicle, and at least achieve: Ⅰ. Intelligent communication link optimization and management: Through the shore station core software including a communication link intelligent decision-making engine and a link seamless switching execution unit, based on multi-dimensional information including communication link status, vehicle status, and task requirements, automatically optimize and select and dynamically manage the communication link with the vehicle; Ⅱ. Shore-based edge data processing: Use the processing power of the shore-based control center to run the shore-based edge data processing module group in the shore station core software, and perform local edge computing or lightweight intelligent analysis on the data received from the vehicle; Ⅲ. Dynamic function reconstruction: Connect a pluggable dedicated task processing adapter module through the generalized expansion interface, and realize the on-demand dynamic reconstruction of the shore-based system function by the dynamic function loading and management mechanism of the shore station core software to support specific tasks executed by the vehicle; Among them, the on-vehicle control subsystem of the vehicle and the shore-based control subsystem perform two-way information interaction through an intelligently optimized communication link.

2. The multi-modal wave propulsion unmanned vehicle control system according to claim 1, wherein: In the dynamic buoyancy adjustment executed by the on-vehicle control subsystem, the fuzzy adaptive PID control algorithm dynamically adjusts the proportional, integral, and differential parameters of the PID controller based on a preset fuzzy rule base according to the depth error and speed error.

3. The multimodal wave propulsion unmanned vehicle control system according to claim 2, characterized in that: The fuzzy rule base includes at least one of the following rules for adjusting the proportional parameter according to the magnitude of the error: if the absolute value of the water volume error exceeds the first preset threshold, increase the proportional parameter; if the absolute value of the speed error is greater than the second preset threshold, increase the proportional parameter; if the absolute value of the depth error is greater than the third preset threshold, increase the proportional parameter.

4. The multimodal wave propulsion unmanned vehicle control system according to claim 1, characterized in that: In the efficient autonomous collision avoidance control executed by the on-board control subsystem, the hierarchical threat response mechanism includes: when the target distance is greater than the first distance threshold, it is determined as a first-level alert, and the foldable mast is controlled to fold; when the target distance is between the second distance threshold and the first distance threshold, it is determined as a second-level alert, and the dynamic buoyancy adjustment module is prepared; when the target distance is less than the second distance threshold, it is determined as a third-level alert, and an emergency dive is executed.

5. The multimodal wave propulsion unmanned vehicle control system according to claim 4, characterized in that: The multi-source collaborative perception module uses the weighted average method for fusion processing to calculate the comprehensive confidence level or risk assessment value, and the preset weights of the AIS, millimeter-wave radar, and camera detection data can be dynamically adjusted according to the sensor status, environmental conditions, or target characteristics.

6. The multimodal wave propulsion unmanned vehicle control system according to claim 1, characterized in that: The built-in multi-mode communication interface group of the shore-based control subsystem includes at least one Beidou / Tiantong integrated satellite communication terminal.

7. The multimodal wave propulsion unmanned vehicle control system according to claim 1, wherein: The shore-based control subsystem further includes a portable display and control terminal, which is communicatively connected to the shore-based control center.

8. The multimodal wave propulsion unmanned vehicle control system according to claim 1, characterized in that: The shore-based control center is configured with an enhanced processing unit, which is used to accelerate the execution of computationally intensive tasks in the shore-based edge data processing module group.

9. The multimodal wave propulsion unmanned vehicle control system according to claim 1, characterized in that: The dedicated task processing adaptation module instance of the shore-based control subsystem is selected from at least one of the following: RTK base station solution module, underwater acoustic signal real-time processing module, ocean environment model calculation module, AIS reception and processing module, meteorological data fusion processing module, or hardware-in-the-loop simulation test module.

10. The multi-modal wave propulsion unmanned vehicle control system according to claim 1, characterized in that: The shore station core software also includes a task template management module, which allows users to define, save, and load task templates. Each template contains system configurations for specific tasks, including preferred communication strategies, enabled edge processing procedures and parameters, and recommended dedicated task processing adaptation modules to be connected.

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