Marine electromagnetic take-off and landing transportation system based on heavy-load unmanned aerial vehicle

Abstract

The invention provides a marine electromagnetic take-off and landing transportation system based on a heavy-load unmanned aerial vehicle, and belongs to the technical field of unmanned aerial vehicle marine heavy-load transportation. The system comprises a shipborne electromagnetic take-off and landing subsystem, a shore-based electromagnetic take-off and landing subsystem, a heavy-load fixed-wing unmanned aerial vehicle, a marine low-altitude communication monitoring network and a comprehensive scheduling platform; the shipborne electromagnetic take-off and landing subsystem is of a multi-section coil array structure, the effective length of a coil array of the shipborne electromagnetic take-off and landing subsystem can be matched with the available space of a fishing ship deck, the take-off and landing distance is controllable, and therefore the problem of take-off and landing in the narrow space of the deck is solved. The shore-based electromagnetic take-off and landing subsystem is integrated with a three-dimensional terrain modeling module, the real-time environment of a landing area is pre-judged through laser radar and satellite remote sensing data, parameters of an electromagnetic propulsion device and an electromagnetic adsorption device of the shore-based electromagnetic take-off and landing subsystem are dynamically adjusted, then the shore-based electromagnetic take-off and landing subsystem adapts to rugged terrain, and the limitation that a traditional unmanned aerial vehicle depends on a flat take-off and landing field is avoided. And through data linkage and intelligent scheduling of multiple subsystems, the overall efficiency and reliability of marine transportation are greatly improved.

Description

Technical Field

[0001] This application belongs to the field of heavy-load maritime transportation technology for unmanned aerial vehicles (UAVs), and specifically relates to a maritime electromagnetic take-off and landing transportation system based on heavy-load UAVs. Background Technology

[0002] With the rapid development of the marine economy, the scope of offshore fishing operations is constantly expanding. The demand for fish transfer between fishing ports and deep-sea fishing vessels, the supply of daily necessities to island residents, and the delivery of emergency medical supplies is becoming increasingly urgent. Traditional maritime transport relies on ships or small helicopters, which presents a challenge in balancing transport capacity and flexibility. Meanwhile, breakthroughs in heavy-load drone technology have provided a new direction for maritime transport. However, the complex spatial conditions, weather environment, and communication interference at sea place higher demands on the stability of drone takeoff and landing, flight controllability, and transport efficiency. In the practice of traditional heavy-load maritime transport and drone takeoff and landing technologies, there are two main technical implementation paths for short-distance "shore-ship" and "shore-island" transport scenarios. One type relies on ship transportation, using small fishing auxiliary vessels or transport ships to transfer goods. Its core is to rely on the ship's own power system for navigation and to load and unload goods through docks or ship cranes. The other type uses helicopters or conventional drones for transportation. Helicopters rely on pilots to operate and take off and land on ship decks or temporary take-off and landing points on islands. Conventional drones mostly use runway take-off and landing or vertical take-off and landing methods, relying on pre-set flat take-off and landing sites and planning flight paths through radio remote control or basic navigation systems. During transportation, they only use simple weather monitoring equipment to avoid extreme weather.

[0003] Among them, the existing patent CN110979568A proposes a maritime supply method based on multi-rotor UAVs, which alleviates to some extent the problems of traditional ship transportation, such as the inability to connect in real time, low loading and unloading efficiency, and the high requirements of conventional UAVs for deck stability. However, it still has obvious shortcomings: the method is mainly applicable to "ship-to-ship" or "ship-to-ship" material transfer scenarios, and is not suitable for take-off, landing, and supply in rugged and complex "shore-to-island" terrain environments; at the same time, the method mainly relies on satellite positioning and simple image recognition, with limited environmental perception and avoidance capabilities, and its reliability is still poor in the face of complex sea conditions and extreme weather. Therefore, there is an urgent need for a heavy-load UAV take-off, landing, and transportation coordination technology solution adapted to maritime scenarios. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a maritime electromagnetic take-off and landing transportation system based on heavy-load UAVs, which can significantly improve the spatial adaptability of heavy-load UAVs in the limited space at sea, and greatly enhance the environmental adaptability of heavy-load UAV maritime transportation operations.

[0005] This application provides a maritime electromagnetic take-off and landing transportation system based on a heavy-load unmanned aerial vehicle (UAV), including a shipborne electromagnetic take-off and landing subsystem, a shore-based electromagnetic take-off and landing subsystem, a heavy-load fixed-wing UAV, a maritime low-altitude communication and monitoring network, and an integrated dispatching platform. During the takeoff and landing preparation phase, the shipborne electromagnetic takeoff and landing subsystem or the shore-based electromagnetic takeoff and landing subsystem generates propulsion force through an electromagnetic propulsion device based on the total weight of the heavy-load fixed-wing UAV and the preset target takeoff and landing distance. The generated propulsion force is matched with the landing gear electromagnetic coupling module of the heavy-load fixed-wing UAV so that the actual takeoff and landing distance does not exceed the target takeoff and landing distance. During the takeoff phase, the electromagnetic propulsion device drives the heavy-load fixed-wing UAV to reach the takeoff speed threshold within a set distance. During the flight transport phase, the integrated scheduling platform dynamically adjusts the flight path based on the effective payload of the heavy-duty fixed-wing UAV's high-load cargo hold within a single flight, combined with real-time data transmitted by the maritime low-altitude communication monitoring network. During the landing phase, the heavy-load fixed-wing UAV docks with the electromagnetic adsorption device of the shipborne electromagnetic take-off and landing subsystem or the shore-based electromagnetic take-off and landing subsystem through the landing gear electromagnetic coupling module to control the landing speed and attitude.

[0006] In some embodiments, the electromagnetic propulsion device employs a multi-segment coil array structure, and the propulsion force is calculated using the following formula:

[0007] in, For system constants, To propel the current, The effective length of the coil array. is the magnetic permeability.

[0008] In some embodiments, the shipborne electromagnetic take-off and landing subsystem is deployed on the deck of a salvage vessel, and the shore-based electromagnetic take-off and landing subsystem is deployed on a ground platform of a fishing port or island hub. The effective length of the coil array of the electromagnetic propulsion device in both the shipborne and shore-based electromagnetic take-off and landing subsystems is adapted to the working space of the salvage vessel deck and the ground platform, respectively, and satisfies the following requirements: ,in, For safety redundancy distance, The target takeoff and landing distance.

[0009] In some embodiments, the electromagnetic adsorption device of the shipborne electromagnetic take-off and landing subsystem is disposed at the end of the ship deck and includes an adsorption coil group corresponding to the landing gear electromagnetic coupling module of the heavy-duty fixed-wing UAV. The adsorption force of the adsorption coil group is dynamically adjusted based on the total weight of the heavy-duty fixed-wing UAV.

[0010] In some embodiments, the shore-based electromagnetic take-off and landing subsystem also integrates a three-dimensional terrain modeling module, which is used to predict the real-time environment of the landing area through lidar and satellite remote sensing data, and dynamically adjust the parameters of its electromagnetic propulsion device and electromagnetic adsorption device.

[0011] In some embodiments, the maritime low-altitude communication monitoring network includes satellite communication base stations, 5G / 4G relay devices, and AI data fusion platforms deployed on fishing vessels, shore-based hubs, and small islands, to provide a network for the collaborative operation of multiple heavy-load fixed-wing UAVs in a swarm, and to complete the synchronization scheduling and obstacle avoidance of multiple heavy-load fixed-wing UAVs in formation flight through a low-latency data link.

[0012] In some embodiments, the AI ​​data fusion platform integrates multi-source data to generate flight commands in real time and transmits them in encrypted form; the multi-source data includes meteorological data, the flight status of heavy-load fixed-wing UAVs, and the task priorities issued by the integrated scheduling platform.

[0013] In some embodiments, the integrated scheduling platform includes a data acquisition module and an AI route planning module. The AI ​​route planning module dynamically calculates the transportation route based on the three-dimensional terrain model obtained by the data acquisition module through the three-dimensional terrain modeling module and the real-time meteorological information obtained through the maritime low-altitude communication monitoring network, and determines the optimal transportation route based on flight resistance.

[0014] In some embodiments, the integrated scheduling platform further includes a task allocation module, used to predict transportation demand through machine learning algorithms and automatically match available heavy-duty fixed-wing UAVs; and based on historical fishing operation information and preset maximum effective payload of the UAVs per trip. Construct a transportation demand forecasting model and calculate the demand matching coefficient. Transportation demand forecasting is performed; the demand matching coefficient is calculated using the following formula.

[0015]

[0016] in This represents the average transport volume for the same historical period. This represents the transportation volume converted from current real-time market demand orders. A value greater than 1 indicates that a single heavy-load fixed-wing UAV cannot meet the current requirements. A value less than 1 indicates that a single heavy-duty fixed-wing UAV has already covered the demand.

[0017] In some embodiments, when automatically matching available heavy-load fixed-wing UAVs, the task allocation module first obtains real-time flight status data of all heavy-load fixed-wing UAVs from the maritime low-altitude communication monitoring network, including total battery capacity, remaining battery power, distance between current location and target transport starting point, and flight time. This data is then combined with the effective length of the coil arrays of the shipborne electromagnetic take-off and landing subsystem and the shore-based electromagnetic take-off and landing subsystem. Target takeoff and landing distance Calculate the payload capacity adaptability coefficient for each available heavy-load fixed-wing UAV. And prioritize the demand matching coefficient Matching and capacity adaptation coefficient The largest heavy-load fixed-wing UAV assignment task; whereby the capacity matching coefficient is calculated using the following formula:

[0018] in, Indicates the total battery capacity. Indicates the safety redundancy distance. This represents the distance between the current location of the heavy-load fixed-wing UAV and the target transport starting point. To standardize the dimensions of distance, The closer the value is to 1, the better the heavy-duty fixed-wing UAV is suited for the current transportation mission.

[0019] This application describes a maritime electromagnetic take-off and landing transportation system based on heavy-duty unmanned aerial vehicles (UAVs). The shipborne electromagnetic take-off and landing subsystem employs a multi-segment coil array structure. The effective length of its coil array can be adapted to the available space on the deck of a fishing vessel, and the take-off and landing distance is controllable, thus solving the problem of take-off and landing in confined deck spaces. The shore-based electromagnetic take-off and landing subsystem integrates a 3D terrain modeling module. It uses lidar and satellite remote sensing data to predict the real-time environment of the landing area and dynamically adjusts the parameters of its electromagnetic propulsion and electromagnetic adsorption devices, thereby adapting to rugged terrain and avoiding the limitations of traditional UAVs relying on flat take-off and landing sites. Furthermore, through data linkage and intelligent scheduling of multiple subsystems, the overall efficiency and reliability of maritime transportation are significantly improved. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This application illustrates a flowchart of the workflow of the heavy-load unmanned aerial vehicle (UAV)-based maritime electromagnetic take-off and landing transportation system according to an embodiment of the present application. Figure 2 A schematic diagram of the structure of the shipborne electromagnetic take-off and landing subsystem described in an embodiment of this application is shown; Figure 3 A schematic diagram of the structure of the maritime low-altitude communication and monitoring network described in an embodiment of this application is shown; Figure 4 A schematic diagram of the integrated scheduling platform described in an embodiment of this application is shown. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0023] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0024] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0025] In view of the technical problems raised in the background art, this application provides a maritime electromagnetic take-off and landing transportation system based on heavy-load UAVs, which can significantly improve the spatial adaptability of heavy-load UAVs in the limited space at sea, and greatly enhance the environmental adaptability of heavy-load UAV maritime transportation operations.

[0026] See the instruction manual appendix Figure 1This application provides a maritime electromagnetic take-off and landing transportation system based on heavy-load unmanned aerial vehicles (UAVs), including a shipborne electromagnetic take-off and landing subsystem, a shore-based electromagnetic take-off and landing subsystem, a heavy-load fixed-wing UAV, a maritime low-altitude communication and monitoring network, and an integrated dispatch platform. The system achieves safe take-off and landing and efficient transportation within the limited space at sea through the following steps: Step 1: Takeoff and Landing Preparation Phase. The shipborne or shore-based electromagnetic takeoff and landing subsystem will determine the takeoff weight of the heavy-load fixed-wing UAV based on the total weight of the UAV. and the preset target take-off and landing distance Controllable propulsion force is generated through an electromagnetic propulsion device. propulsion Matching with the electromagnetic coupling module of the landing gear of heavy-duty fixed-wing UAVs to ensure actual takeoff and landing distance. No more than ; Step 2: During the takeoff phase, the electromagnetic propulsion device of the shipborne or shore-based electromagnetic takeoff and landing subsystem releases electromagnetic energy in pulses, driving the heavy-load fixed-wing UAV to reach the takeoff speed threshold within a very short distance. ; Step 3: During the flight transport phase, the integrated scheduling platform utilizes heavy-load fixed-wing UAVs for single-flight operations. Effective payload of the inner high-load cargo compartment By combining real-time data from the maritime low-altitude communication and monitoring network, the flight path is dynamically adjusted to avoid obstacles and optimize energy consumption. Step 4: During the landing phase, the heavy-load fixed-wing UAV docks with the electromagnetic adsorption device of the shipborne or shore-based electromagnetic take-off and landing subsystem via the landing gear electromagnetic coupling module, using electromagnetic braking force to precisely control the landing speed. The system coordinates the attitude to ensure a safe landing. Throughout the process, the integrated dispatch platform integrates fishing operation information, drone capacity status, and market demand data.

[0027] See the instruction manual appendix Figure 2 The shipborne electromagnetic take-off and landing subsystem includes an electromagnetic propulsion device (responsible for the take-off propulsion of heavy-load fixed-wing UAVs) integrated on the deck of the fishing vessel and an electromagnetic adsorption device (responsible for the landing adsorption of heavy-load fixed-wing UAVs). The electromagnetic propulsion device adopts a multi-segment coil array structure, and its effective coil array length... It is adapted to the available space on the deck of the target fishing vessel. The shore-based electromagnetic take-off and landing subsystem is deployed on ground platforms in key fishing ports and island hubs, with an effective coil array length... The configuration should be based on the actual space requirements of the island's docks or fishing ports. It should also be noted that the effective length of the coil array for both shipborne and shore-based electromagnetic take-off and landing subsystems... Also need to satisfy ,in To ensure a safe redundancy distance and provide a buffer for the uncertainties of actual take-off and landing scenarios at sea, this design avoids heavy-load fixed-wing UAVs from exceeding take-off and landing limits and overrunning the deck / shore platform due to errors, fluctuations, or emergencies.

[0028] Specifically, during the takeoff and landing preparation phase, the integrated dispatch platform first transmits core parameters to the shipborne electromagnetic takeoff and landing subsystem or the shore-based electromagnetic takeoff and landing subsystem. These core parameters include the total weight of the heavy-load fixed-wing UAV at takeoff. Preset target take-off and landing distance and the effective length of the coil array of the corresponding subsystem. Safety redundancy distance The basic configuration parameters are then received; subsequently, the shipborne or shore-based electromagnetic take-off and landing subsystem, after receiving the parameters transmitted by the integrated dispatch platform, initiates the equipment self-test process, performing functional integrity checks on the coil array and circuit connection status of the electromagnetic propulsion device, as well as the adsorption coil group of the electromagnetic adsorption device, to ensure there are no hardware faults; the subsystem, based on the received parameters... and Combined with the electromagnetic propulsion formula ,in For system constants, To propel the current, Given the magnetic permeability, calculate the required propulsion force. The specific value, and determine the propulsion current to match the thrust. The adjustment range is then determined; next, the landing gear electromagnetic coupling module of the heavy-load fixed-wing UAV initiates a self-test, establishes a preliminary communication connection with the shipborne electromagnetic take-off and landing subsystem or the shore-based electromagnetic take-off and landing subsystem, and provides feedback on the electromagnetic response status of the landing gear coupling module; finally, the subsystem will calculate the thrust... The compatibility threshold of the landing gear electromagnetic coupling module of the fixed-wing UAV was compared and verified, and the actual take-off and landing distance of the UAV under the action of this propulsion force was confirmed through simulation. Satisfy ≤ Complete takeoff and landing preparations.

[0029] During takeoff, the shipborne or shore-based electromagnetic takeoff and landing subsystem operates based on the propulsion current determined during the takeoff and landing preparation phase. The system adjusts the current range and outputs a current adjustment command to the electromagnetic propulsion device, adjusting the propulsion current to the target value to prepare for energy release. Upon receiving the command, the electromagnetic propulsion device activates a pulsed energy release mechanism, releasing electromagnetic energy to the coil array according to a preset pulse frequency and energy intensity, generating propulsion force to drive the heavy-load fixed-wing UAV to accelerate along the takeoff and landing track. The landing gear electromagnetic coupling module of the heavy-load fixed-wing UAV collects the UAV's flight attitude data and real-time propulsion force sensing data in real time, transmitting the data to the shipborne or shore-based electromagnetic takeoff and landing subsystem. The subsystem receives the data from the landing gear electromagnetic coupling module; if it detects attitude deviation or changes in propulsion demand of the heavy-load fixed-wing UAV, it fine-tunes the propulsion current in real time. In turn, adjust the propulsion force The system corrects the drone's attitude to ensure stability during acceleration; the heavy-load fixed-wing drone continues to accelerate, and the subsystem monitors the drone's flight speed in real time, determining when the speed reaches a preset takeoff speed threshold. At that time, the electromagnetic propulsion device stops releasing pulse energy, and the UAV leaves the takeoff and landing track and takes off, completing the takeoff maneuver.

[0030] Furthermore, the shore-based electromagnetic takeoff and landing subsystem also integrates a 3D terrain modeling module. This module uses lidar or satellite remote sensing data to predict the real-time environment of the landing area and dynamically adjusts the parameters of its electromagnetic propulsion and electromagnetic adsorption devices. To achieve precise matching between the terrain environment and electromagnetic parameters, the terrain adaptation coefficient of the landing area must first be calculated. This coefficient is related to the effective length of the coil array. Target takeoff and landing distance and safety redundancy distance At the same time, the maximum terrain height difference extracted from the three-dimensional terrain model is introduced. The specific formula is as follows:

[0031] The purpose of the above formulas is to quantify the impact of terrain undulations on the takeoff and landing process. When it increases, A decrease indicates increased interference from terrain on takeoff and landing; in this case, the shore-based electromagnetic takeoff and landing subsystem will adjust accordingly. Dynamically adjust electromagnetic propulsion With electromagnetic attraction force The thrust adjustment follows ;in, As the baseline propulsion force under flat terrain, the suction force adjustment follows ;in, As the benchmark adsorption force under flat terrain, this parameter linkage mechanism ensures that the shore-based electromagnetic take-off and landing subsystem can still meet the requirements under complex terrain environments. ≤ The system requirements provide support for the precise docking of heavy-load fixed-wing UAVs with the electromagnetic adsorption device and the safe landing.

[0032] During the flight transport phase, after the heavy-load fixed-wing UAV takes off, it completes its effective payload through the high-load cargo hold. The loading was confirmed to ensure that the cargo was securely fastened and that the load did not exceed the permitted voyage distance. The corresponding maximum load limit is set; the maritime low-altitude communication and monitoring network activates its real-time data transmission function, transmitting meteorological data, maritime obstacle distribution data, and real-time flight status data of heavy-load fixed-wing UAVs collected by equipment deployed on fishing vessels, shore-based hubs, and small islands to the integrated dispatch platform; the integrated dispatch platform receives the above real-time data, combines it with the terrain data provided by the three-dimensional terrain modeling module of the shore-based subsystem, dynamically calculates the optimal transportation path, and prioritizes the selection of flight resistance... The flight corridor is relatively small; the integrated scheduling platform transmits the optimized flight path instructions to the heavy-load fixed-wing UAV with encryption. After receiving the instructions, the heavy-load fixed-wing UAV adjusts its flight attitude and begins flight transport according to the optimal path. During the flight, the maritime low-altitude communication monitoring network continuously transmits real-time data. The AI ​​path planning module dynamically adjusts the path according to the data changes, and the heavy-load fixed-wing UAV responds and adjusts synchronously to ensure obstacle avoidance and optimize energy consumption until it approaches the target landing area.

[0033] During the landing phase, the integrated dispatch platform transmits landing parameters to the shipborne or shore-based electromagnetic take-off and landing subsystems landing at the target location, as well as to the heavy-load fixed-wing UAV. These landing parameters include the target landing position and the maximum permissible landing speed. The total weight of the UAV (including payload), etc.; after receiving the landing parameters, the shipborne or shore-based subsystem activates the electromagnetic adsorption device and adjusts the adsorption force of the adsorption coil group according to the current total weight of the heavy-load fixed-wing UAV. Preset values ​​ensure the adsorption force is suitable for the drone's weight. After receiving landing parameters, the heavy-load fixed-wing drone adjusts its altitude and speed, gradually approaching the subsystem's landing area. The landing gear electromagnetic coupling module establishes precise positioning communication with the subsystem's electromagnetic adsorption device to confirm the docking position. The heavy-load fixed-wing drone adjusts to the optimal landing attitude, and the landing gear electromagnetic coupling module and the subsystem's electromagnetic adsorption device complete precise docking. The subsystem immediately applies electromagnetic braking force, gradually reducing the drone's landing speed and controlling it within a certain range. Within the range; after the heavy-load fixed-wing UAV lands smoothly, the subsystem shuts down the electromagnetic braking force and adsorption device, the integrated scheduling platform records the key data of this transportation mission, and updates the capacity status of the heavy-load fixed-wing UAV and its subsystems, completing the landing phase and the entire transportation process.

[0034] See the appendix to the instruction manual. Figure 3 Included with instruction manualFigure 4 The aforementioned low-altitude maritime communication and monitoring network includes satellite communication base stations, 5G / 4G relay devices, and an AI data fusion platform deployed on fishing vessels, shore-based hubs, and small islands. The network supports collaborative operations of multiple heavy-duty fixed-wing UAVs in a swarm, achieving synchronized scheduling and obstacle avoidance during formation flight through a low-latency data link. The integrated scheduling platform includes a data acquisition module, an AI path planning module, and a task allocation module. The AI ​​path planning module dynamically calculates the optimal transportation route based on a 3D terrain model and real-time meteorological information.

[0035] Specifically, the integrated scheduling platform, as the core scheduling hub of the heavy-load UAV maritime electromagnetic take-off and landing transportation system, has a key role in its AI path planning module. Within the system's pre-set flight corridor, it combines 3D terrain model data output by the shore-based electromagnetic take-off and landing subsystem's 3D terrain modeling module with real-time meteorological information transmitted from the maritime low-altitude communication and monitoring network. Through quantitative calculations, it selects the flight resistance... To find the minimum optimal transportation route, we first need to construct a comprehensive adaptation coefficient for the flight corridor. The computational model needs to be associated with the key parameters already defined in the system. The specific formula is as follows:

[0036] in, The meteorological adaptability coefficient, obtained by normalizing real-time wind speed, rainfall, and visibility data collected by the low-altitude maritime communication and monitoring network, is used to quantify the impact of meteorological conditions on track. and Together, they reflect the connectivity and adaptability between the takeoff and landing areas and the flight corridor. To reduce the flight drag of heavy-load fixed-wing UAVs within the current flight corridor, This is for a single flight of the drone; thus, through multi-dimensional parameter coupling, the comprehensive adaptability to different flight corridors can be quantified. A higher value indicates better weather conditions for the corresponding flight corridor, smoother connection with the takeoff and landing area, and lower flight drag. The AI ​​path planning module will prioritize selecting this corridor. The flight corridor with the highest value is taken as the optimal transportation route. Through this quantitative calculation process, it is ensured that the planned route not only meets the system's requirements for take-off and landing connections, but also effectively reduces the energy consumption of UAVs and improves transportation efficiency. This provides accurate path data support for the subsequent task allocation module to match available UAVs based on the optimal path.

[0037] In a real-world operational scenario of a heavy-duty UAV-based maritime electromagnetic take-off and landing transportation system, when a heavy-duty fixed-wing UAV needs to transport cargo from fishing port A (where the shore-based electromagnetic take-off and landing subsystem is located) to fishing vessel B (where the shipborne electromagnetic take-off and landing subsystem is located), the AI ​​path planning module of the integrated scheduling platform initiates optimal path calculation. This process requires the linkage of the pre-take-off and landing preparation stage, the flight transportation stage, and the core parameters of related subsystems. A specific example process is as follows: First, the data acquisition module obtains the parameters required in the preceding steps, including the 3D terrain model data of the sea area from fishing port A to fishing vessel B generated by the 3D terrain modeling module of the shore-based electromagnetic take-off and landing subsystem, and the meteorological information transmitted in real time by the maritime low-altitude communication monitoring network. At the same time, it retrieves the effective length of the coil array of the shore-based electromagnetic take-off and landing subsystem preset by the system. Safety redundancy distance and the single flight range of heavy-load fixed-wing UAVs. Design flight speed Next, the AI ​​path planning module first uses the 3D terrain model data, combined with... and Three candidate flight corridors that meet the takeoff and landing connection requirements were calculated. Then, for each candidate corridor, flight drag was quantified based on real-time meteorological information. ; For the three candidate corridors Comparative analysis revealed that the first corridor had a real-time wind speed of 5 m / s and a visibility of 800 m, resulting in flight resistance. The wind speed is 200N, the real-time wind speed in the second corridor is 8m / s, the visibility is 500m, and the flight resistance is... The wind speed is 350N, the real-time wind speed in the third corridor is 10m / s, the visibility is 300m, and the flight resistance is... The value is 500N; ultimately, the AI ​​path planning module prioritizes flight resistance. The first corridor with the shortest distance is selected as the optimal transportation path, which meets the requirements for takeoff and landing distance during the pre-landing preparation phase. This meets the requirements while reducing the energy consumption of drones during the flight transport phase and shortening transport time. The extra time spent in the process provides a path basis for the subsequent task allocation module to match the heavy-duty fixed-wing UAV with the transportation task and monitor the battery status.

[0038] The task allocation module uses machine learning algorithms to predict transportation demand and automatically match available heavy-load fixed-wing UAVs, while simultaneously monitoring the battery status of these UAVs. As the core execution unit of the integrated scheduling platform, the task allocation module needs to be deeply integrated with the overall framework of the heavy-load UAV-based maritime electromagnetic take-off and landing transportation system. Its process of predicting transportation demand, automatically matching available heavy-load fixed-wing UAVs, and monitoring battery status through machine learning algorithms requires connection to the data transmission function of the maritime low-altitude communication monitoring network, the take-off and landing capability parameters of the shore-based and shipborne electromagnetic take-off and landing subsystems, and the flight performance parameters of the heavy-load fixed-wing UAVs. In the transportation demand prediction stage, a time-series prediction algorithm is used, based on historical fishing operation information (including cargo transportation volume between fishing ports and fishing vessels at different times of the day), real-time market demand data (including fish catch purchase orders), and the system's preset maximum effective payload per UAV. The core of constructing a transportation demand forecasting model is to calculate the demand matching coefficient. To achieve accurate predictions, the formula is:

[0039] in, This represents the average transport volume for the same historical period. This represents the transportation volume converted from current real-time market demand orders. The purpose of this formula is to quantify the matching relationship between current transportation demand and the single-flight capacity of drones. A value greater than 1 indicates that a single heavy-load fixed-wing UAV cannot meet the current demand and multiple UAVs need to be dispatched, while a value less than 1 indicates that a single heavy-load fixed-wing UAV can cover the demand. This coefficient helps avoid overcapacity or undercapacity. In the automatic matching of available heavy-load fixed-wing UAVs, real-time flight status data of all UAVs is first obtained from the maritime low-altitude communication monitoring network, including remaining battery power, distance from the current location to the target transport starting point, and flight time. This data is then combined with the effective length of the coils of the shore-based and shipborne electromagnetic take-off and landing subsystems. Target takeoff and landing distance Calculate the capacity fit coefficient for each available drone. The formula is:

[0040] in Represents the total battery capacity of the drone. Represents the safety redundancy distance. This represents the distance between the current location of the heavy-load fixed-wing UAV and the target transport starting point. To standardize distance dimensions, this formula aims to comprehensively evaluate the endurance, location adaptability, and takeoff and landing adaptability of heavy-load fixed-wing UAVs. A value closer to 1 indicates that the heavy-duty fixed-wing UAV is more suitable for the current transportation mission; the module will prioritize selecting it. Match and The largest heavy-load fixed-wing UAV assignment task.

[0041] After using machine learning algorithms to predict transportation demand and automatically match available drones, it is necessary to continuously coordinate with the maritime low-altitude communication and monitoring network to obtain the remaining battery power of the allocated drones in real time. Data, combined with the total battery capacity of the drone The core of building a battery status monitoring model is to calculate the percentage of remaining battery capacity. To achieve dynamic monitoring, the formula is:

[0042] in This is the percentage of remaining battery capacity. The remaining battery power of drones is collected and transmitted in real time by the maritime low-altitude communication monitoring network. The system presets the total battery capacity of the drones. This parameter, along with the task allocation module, calculates the capacity matching coefficient during the automatic drone matching process. The battery parameters used are consistent to ensure data synchronization.

[0043] Furthermore, the task allocation module will pre-calculate based on the single flight range of the heavy-load fixed-wing UAV. Average flight speed and flight resistance The minimum battery charge percentage threshold required for the current transportation task is calculated using the system energy consumption model. This threshold must simultaneously ensure that the UAV, after completing its current transport mission, still has the power reserve required for a safe landing with the shipborne or shore-based electromagnetic take-off and landing subsystem, and that it is compatible with the take-off and landing energy consumption requirements of the electromagnetic take-off and landing subsystem (e.g., the electromagnetic coupling module needs to consume a certain amount of power to dock with the electromagnetic adsorption device during the landing phase). During the flight transport phase of the heavy-load fixed-wing UAV, the task allocation module calculates in real time... and When a comparison is performed, Descending to In such cases, the battery warning information will be immediately fed back to the integrated dispatch platform. The integrated dispatch platform will then combine real-time meteorological data transmitted from the maritime low-altitude communication monitoring network, the current location information of the UAV, and the real-time status of the shore-based / shipborne electromagnetic take-off and landing subsystem to dynamically adjust the subsequent execution strategy. This will provide data support to ensure the continuous progress of the transportation mission or to activate the backup plan, thus ensuring the stability and safety of the overall transportation process of the system.

[0044] The application provides a maritime electromagnetic take-off and landing transportation system based on heavy-load unmanned aerial vehicles (UAVs). The shipborne electromagnetic take-off and landing subsystem adopts a multi-segment coil array structure. By matching the total take-off weight of the UAV to generate controllable propulsion, and combining it with an electromagnetic adsorption device to dynamically adjust the adsorption force, it ensures that the UAV can stably reach the take-off speed threshold and accurately control the landing speed even in confined spaces such as the deck of a fishing vessel. The shore-based electromagnetic take-off and landing subsystem uses a 3D terrain modeling module to predict the environment using lidar or satellite remote sensing data and dynamically optimize electromagnetic parameters to adapt to the complex terrain of fishing ports and islands. At the same time, a maritime low-altitude communication and monitoring network constructs a low-latency data link through satellite communication base stations and 5G / 4G relay devices to support UAV swarm collaborative operations. In conjunction with the AI ​​path planning module of the integrated scheduling platform, it selects the path with less flight resistance based on real-time meteorological data and 3D terrain models, effectively avoiding maritime obstacles and reducing energy consumption. This allows heavy-load UAVs to stably complete high-load transportation tasks within a single flight, breaking the spatial and environmental limitations of traditional maritime transportation.

[0045] Furthermore, through data linkage and intelligent scheduling across multiple subsystems, the overall efficiency and reliability of maritime transportation have been significantly improved. The task allocation module of the integrated scheduling platform utilizes machine learning algorithms to calculate the demand matching coefficient by combining historical transportation data with real-time market demand. This accurately predicts transportation needs and automatically matches the drone with the optimal capacity adaptation coefficient. Simultaneously, the platform monitors the drone's remaining battery power percentage in real time. When the battery power drops to the minimum threshold required for the mission, it immediately coordinates with the communication network and takeoff and landing subsystem to adjust strategies, ensuring smooth connection of transportation tasks. This comprehensive coordination not only reduces errors caused by human intervention but also dynamically responds to complex weather and terrain changes at sea, significantly improving the stability, timeliness, and economy of heavy-load drone maritime transportation, providing efficient technical solutions for scenarios such as maritime fisheries and material supply.

[0046] Finally, it should be noted that the above embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A maritime electromagnetic take-off and landing transportation system based on heavy-load unmanned aerial vehicles (UAVs), characterized in that, It includes a shipborne electromagnetic take-off and landing subsystem, a shore-based electromagnetic take-off and landing subsystem, a heavy-load fixed-wing UAV, a maritime low-altitude communication and monitoring network, and an integrated dispatch platform. During the takeoff and landing preparation phase, the shipborne electromagnetic takeoff and landing subsystem or the shore-based electromagnetic takeoff and landing subsystem generates propulsion force through an electromagnetic propulsion device based on the total weight of the heavy-load fixed-wing UAV and the preset target takeoff and landing distance. The generated propulsion force is matched with the landing gear electromagnetic coupling module of the heavy-load fixed-wing UAV so that the actual takeoff and landing distance does not exceed the target takeoff and landing distance. During the takeoff phase, the electromagnetic propulsion device drives the heavy-load fixed-wing UAV to reach the takeoff speed threshold within a set distance. During the flight transport phase, the integrated scheduling platform dynamically adjusts the flight path based on the effective payload of the heavy-duty fixed-wing UAV's high-load cargo hold within a single flight, combined with real-time data transmitted by the maritime low-altitude communication monitoring network. During the landing phase, the heavy-load fixed-wing UAV docks with the electromagnetic adsorption device of the shipborne electromagnetic take-off and landing subsystem or the shore-based electromagnetic take-off and landing subsystem through the landing gear electromagnetic coupling module to control the landing speed and attitude.

2. The maritime electromagnetic take-off and landing transportation system based on a heavy-load unmanned aerial vehicle (UAV) as described in claim 1, characterized in that, The electromagnetic propulsion device employs a multi-segment coil array structure, and the propulsion force is calculated using the following formula: in, For system constants, To propel the current, The effective length of the coil array. is the magnetic permeability.

3. The maritime electromagnetic take-off and landing transportation system based on a heavy-load unmanned aerial vehicle (UAV) according to claim 2, characterized in that, The shipborne electromagnetic take-off and landing subsystem is deployed on the deck of the salvage vessel, and the shore-based electromagnetic take-off and landing subsystem is deployed on the ground platform of the fishing port and island hub. The effective length of the coil array of the electromagnetic propulsion device in both the shipborne and shore-based electromagnetic take-off and landing subsystems is adapted to the working space of the salvage vessel deck and the ground platform, respectively, and satisfies the following requirements. ,in, For safety redundancy distance, The target takeoff and landing distance.

4. The maritime electromagnetic take-off and landing transportation system based on a heavy-load unmanned aerial vehicle (UAV) according to claim 3, characterized in that, The electromagnetic adsorption device of the shipborne electromagnetic take-off and landing subsystem is located at the end of the ship deck and includes an adsorption coil group corresponding to the landing gear electromagnetic coupling module of the heavy-duty fixed-wing UAV. The adsorption force of the adsorption coil group is dynamically adjusted based on the total weight of the heavy-duty fixed-wing UAV.

5. The maritime electromagnetic take-off and landing transportation system based on a heavy-load unmanned aerial vehicle (UAV) according to claim 1, characterized in that, The shore-based electromagnetic take-off and landing subsystem also integrates a three-dimensional terrain modeling module, which is used to predict the real-time environment of the landing area through lidar and satellite remote sensing data, and dynamically adjust the parameters of its electromagnetic propulsion device and electromagnetic adsorption device.

6. The maritime electromagnetic take-off and landing transportation system based on a heavy-load unmanned aerial vehicle (UAV) according to claim 5, characterized in that, The maritime low-altitude communication and monitoring network includes satellite communication base stations, 5G / 4G relay devices, and AI data fusion platforms deployed on fishing vessels, shore-based hubs, and small islands. It provides a network for the coordinated operation of multiple heavy-load fixed-wing UAVs in a swarm, and completes the synchronous scheduling and obstacle avoidance of multiple heavy-load fixed-wing UAVs in formation flight through a low-latency data link.

7. The maritime electromagnetic take-off and landing transportation system based on a heavy-load unmanned aerial vehicle (UAV) according to claim 6, characterized in that, The AI ​​data fusion platform integrates multi-source data to generate flight commands in real time and transmit them in encrypted form. The multi-source data includes meteorological data, the flight status of heavy-load fixed-wing UAVs, and the task priorities issued by the integrated scheduling platform.

8. The maritime electromagnetic take-off and landing transportation system based on a heavy-load unmanned aerial vehicle (UAV) according to claim 7, characterized in that, The integrated scheduling platform includes a data acquisition module and an AI route planning module. The AI ​​route planning module dynamically calculates the transportation route based on the three-dimensional terrain model obtained by the data acquisition module through the three-dimensional terrain modeling module and the real-time meteorological information obtained through the maritime low-altitude communication monitoring network, and determines the optimal transportation route based on flight resistance.

9. A maritime electromagnetic take-off and landing transportation system based on a heavy-load unmanned aerial vehicle (UAV) according to claim 8, characterized in that, The integrated scheduling platform also includes a task allocation module, which uses machine learning algorithms to predict transportation demand and automatically match available heavy-duty fixed-wing UAVs; and a module based on historical fishing operation information and preset maximum effective payload of UAVs per trip. Construct a transportation demand forecasting model and calculate the demand matching coefficient. Transportation demand forecasting is performed; the demand matching coefficient is calculated using the following formula. in This represents the average transport volume for the same historical period. This represents the transportation volume converted from current real-time market demand orders. A value greater than 1 indicates that a single heavy-load fixed-wing UAV cannot meet the current requirements. A value less than 1 indicates that a single heavy-duty fixed-wing UAV has already covered the demand.

10. A maritime electromagnetic take-off and landing transportation system based on a heavy-load unmanned aerial vehicle (UAV) according to claim 9, characterized in that, When automatically matching available heavy-load fixed-wing UAVs, the task allocation module first obtains real-time flight status data of all heavy-load fixed-wing UAVs from the maritime low-altitude communication monitoring network, including total battery capacity, remaining battery power, distance from the current location to the target transport starting point, and flight time. This data is then combined with the effective length of the coil arrays of the shipborne electromagnetic take-off and landing subsystem and the shore-based electromagnetic take-off and landing subsystem. Target takeoff and landing distance Calculate the payload capacity adaptability coefficient for each available heavy-load fixed-wing UAV. And prioritize the demand matching coefficient Matching and capacity adaptation coefficient The largest heavy-load fixed-wing UAV assignment task; whereby the capacity matching coefficient is calculated using the following formula: in, Indicates the total battery capacity. Indicates the safety redundancy distance. This represents the distance between the current location of the heavy-load fixed-wing UAV and the target transport starting point. To standardize the dimensions of distance, The closer the value is to 1, the better the heavy-duty fixed-wing UAV is suited for the current transportation mission.

Images