Unmanned aerial vehicle airport system and unmanned aerial vehicle automatic recharging method

Abstract

The invention discloses an unmanned aerial vehicle airport system and an unmanned aerial vehicle automatic recharging method, and the system comprises an airport cabin which is internally and fixedly provided with a plurality of charging piles, and one side of the airport cabin is provided with an airport access; the parking apron is arranged on the outer side of the airport entrance and exit; a charging interface is formed in the side face of the charging pile and used for being connected with the unmanned aerial vehicle; the unmanned aerial vehicle comprises a fuselage and an undercarriage, an unmanned aerial vehicle battery and an auxiliary charging device are arranged on the fuselage, walking wheels and a driving motor are installed at the bottom of the undercarriage, the walking wheels can be used for running between the parking apron and the airport cabin, and the driving motor can drive the unmanned aerial vehicle to walk to the charging pile; a charging connector used for being in butt joint with a charging pile for charging is installed at one end of the undercarriage, the charging connector is connected with the auxiliary charging device through a charging line, and the charging connector can be in butt joint with the charging interface to establish a charging loop. According to the invention, unmanned aerial vehicles of different brands and models can be charged, the economic cost is reduced, and the multi-vehicle recharging efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of drone airport charging technology, specifically to a drone airport system and a method for automatic drone recharging. Background Technology

[0002] As a fully automated operational hub, drone airports solve the challenges of takeoff and landing in complex terrains by providing standardized takeoff and landing platforms, enabling unattended continuous inspections. Their automatic charging function overcomes the bottleneck of single-drone endurance, ensuring uninterrupted inspection of long-distance pipelines, power grids, and other targets; significantly improving inspection efficiency and safety, reducing the risk of manual intervention and maintenance costs, and becoming a core infrastructure for large-scale inspection operations, playing a crucial role in drone inspection missions.

[0003] The design of existing drone airport systems has the following drawbacks during the drone return and recharging process: 1. Traditional drone airports are typically designed with complex mechanical structures, such as multi-degree-of-freedom robotic arms, precision guide rails, and lifting platforms, as well as expensive high-precision sensor systems and temperature control systems, in order to achieve precise guidance, charging docking, and storage protection. This results in high equipment costs and difficult maintenance, which limits the large-scale deployment of drone airports.

[0004] 2. Most existing drone airports are designed for specific models or specifications of drones. Their charging port locations, compatible fuselage sizes, landing gear layouts, etc., are highly customized and cannot be compatible with drones of different brands and models. At the same time, the physical space and charging port limitations of drone airports mean that a single airport can usually only accommodate a very small number of drones or even a single drone, making it difficult to meet the needs of multi-drone collaborative operations and high-frequency missions.

[0005] 3. Traditional drone airports mostly require drones to land precisely in narrow target areas, which places extremely high demands on the drone's navigation and positioning system, wind resistance, and airport guidance system. In complex environments such as wind disturbance and GPS signal blockage, the landing failure rate is relatively high, which seriously affects the efficiency and reliability of drone recharging operations.

[0006] 4. Most existing drone airports prioritize charging based on a "first-come, first-served" principle or according to remaining battery power. This rigid priority system fails to consider factors such as mission urgency and overall time consumption, resulting in low efficiency when multiple drones return to charge. Summary of the Invention

[0007] To address one or more shortcomings of the existing technology, this invention provides a drone airport system and an automatic drone recharging method, which can be compatible with drones of different brands and models for charging, improves the landing success rate of drones, simplifies the drone airport structure, reduces economic costs, and achieves scientific scheduling, thereby improving the recharging efficiency of multiple drones.

[0008] To achieve the above objectives, the present invention adopts one or more of the following technical solutions: Firstly, a drone airport system is provided, comprising: An airport cabin, in which several charging piles are fixedly installed, and an airport entrance / exit is opened on one side of the airport cabin; The apron is located outside the airport entrance / exit. The charging station has a charging interface on its side, which is used to connect to the drone. The drone includes a fuselage and landing gear. The fuselage is equipped with a drone battery and an auxiliary charging device. The landing gear is equipped with wheels and a drive motor at the bottom. The wheels are used to move between the apron and the airport cabin. The drive motor can drive the drone to the charging station. One end of the landing gear is equipped with a charging connector for docking with the charging station. The charging connector is connected to the auxiliary charging device via a charging cable. The charging connector can dock with the charging interface to establish a charging circuit.

[0009] Preferably, it also includes an airport main control system, which is located inside the airport cabin and is communicatively connected to the charging pile and the drone respectively.

[0010] Preferably, a guide rail is fixedly connected to the side of the charging pile facing the drone body. The guide rail is laid on the ground and has a set length to guide the wheels of the drone that are close to the charging pile, so as to ensure that the charging connector and the charging interface are accurately connected. The free end of the guide rail is provided with a guide groove, the width of which gradually increases from the near end to the far end of the charging pile, so as to guide the walking wheels into the guide rail and improve the efficiency of the drone body reaching the charging pile.

[0011] Preferably, the UAV is equipped with a flight control system, which is communicatively connected to the airport's main control system. The flight control system includes an integrated RTK positioning module and a main processor, with the main processor connected to the drive motor. The RTK positioning module can be combined with the BeiDou navigation system to navigate the UAV, and the drive motor can be activated when movement is required via control commands from the main processor, achieving intelligent navigation and positioning as well as automatic charging.

[0012] Preferably, the charging pile is equipped with multiple infrared transmitters on one side, and the landing gear is equipped with left and right infrared receivers. The left and right infrared receivers can respectively receive the infrared signals emitted by the infrared transmitters and obtain deviation information. The infrared receivers are connected to the flight control system, and the flight control system controls the drive motor according to the deviation information, thereby realizing the travel speed and turning of the UAV body.

[0013] Preferably, an outer ring magnet is fixedly arranged around the charging connector, and an outer ring electromagnet is fixedly arranged around the charging interface; when the outer ring magnet and the outer ring electromagnet are attracted to each other, the charging connector and the charging interface are in contact, which can improve the stability of the charging process and prevent the charging connector from detaching from the charging interface.

[0014] Preferably, the outer ring magnets are arranged in a circular pattern, the charging connector is coaxially arranged with the outer ring magnets, and an insulating layer is provided between the charging connector and the outer ring magnets to avoid short circuits and magnetic field interference.

[0015] Preferably, the top of the airport cabin is provided with a canopy to form a closed structure. The canopy is made of glass, which can reduce interference with RTK and BeiDou positioning signals.

[0016] Preferably, a meteorological monitoring pole is fixedly installed on the apron, and a meteorological observation component is installed on the meteorological monitoring pole. The meteorological observation component includes a wind speed and direction sensor, a temperature, humidity and air pressure sensor, a precipitation sensor and a visibility sensor, so that the airport main control system can accurately determine whether the conditions for UAV take-off and landing are met based on meteorological monitoring information and temperature information.

[0017] Secondly, a method for automatic recharging of a drone based on a drone airport system described in any of the above-mentioned aspects is provided, comprising the following steps: After the drone returned and landed on the tarmac, the automatic access control system detected the drone's identity and opened, allowing the drone to enter the airport cabin. The airport's main control system performs scheduling based on the status information of charging piles and drones, obtaining time-space scheduling information. The airport's main control system sends instructions to the drone and the target charging station respectively based on time-space scheduling information. The charging station starts the infrared guidance mode. The drone's self-driving component adjusts its direction of travel based on the infrared guidance signal, turns into the guide rail and continues to move until the drone's charging connector is physically connected to the charging interface of the target charging station and is locked by magnetic attraction, thus establishing a stable charging circuit. After receiving the takeoff inspection command, the airport's main control system determines whether the takeoff conditions are met based on the meteorological and temperature information obtained by the meteorological observation components. If the takeoff conditions are met, the system automatically detects the status of each drone, selects the available drones that meet the mission requirements, and issues control commands. The drones then activate their self-propulsion components to move through the airport entrance and exit, leave the airport cabin, and enter the waiting area on the external apron. After completing the takeoff preparation and self-check actions in the waiting area, the drones enter the waiting state.

[0018] Preferably, the airport's main control system performs scheduling based on the status information of charging piles and drones, and the specific process for obtaining time-space scheduling information is as follows: S1. Obtain the status data of each charging pile and the status data of each returning drone, and construct a compatibility matrix and a time consumption matrix; S2. Based on the urgency of the task, perform preliminary screening and sorting of the returning drones to obtain the queue to be scheduled; S3. Based on the compatibility matrix and time consumption matrix, the optimal allocation algorithm is used to allocate charging piles to the queue to be scheduled, and the pile allocation data is obtained. S4. Based on the pile location allocation data, the time slot reservation method is used to allocate departure time to each UAV and plan conflict-free paths to obtain time-space scheduling information.

[0019] By adopting the above technical solution, the beneficial effects of the present invention are as follows: 1. This invention enables charging via a charging interface and charging connector, eliminating the need for complex mechanical structures to disassemble the drone battery. The charging station is small in size and requires minimal space, making it possible to deploy large numbers of drones within drone airports. 2. The charging interface and connector can be standardized, and multiple charging stations of different models and charging power can be installed within a drone airport, meeting the charging needs of different drone models and significantly improving the versatility of drone airports. This effectively reduces construction costs and provides endurance for drone swarms to perform multi-drone collaborative operations and high-frequency missions. 3. The self-propelled component enables wheeled movement for the drone, reducing the need for precise takeoff and landing, allowing for successful application in complex environments and greatly improving landing success rate and charging efficiency.

[0020] 2. In this invention, the drone airport, charging station and drone can be managed, scheduled and executed through a unified platform, realizing a high degree of automation and intelligence in the drone recharging process, and realizing unmanned management of the airport as well as efficient fully automatic detection, scheduling and execution.

[0021] 3. In the scheduling process of UAVs returning to UAV airports for charging, this invention comprehensively considers factors such as mission urgency, overall time cost, and path conflicts. It adopts an optimal allocation algorithm, departure time allocation, and time slot reservation mechanism to allocate charging pile positions and plan spatiotemporal paths for UAVs. This balances charging efficiency with the safe operation of UAVs. Compared with the traditional single scheduling principle, it significantly improves the utilization rate of UAV airport channels and the charging efficiency of multiple UAVs. At the same time, it enables UAVs to respond quickly to emergency tasks and improves the overall scheduling level of UAV airports. Attached Figure Description

[0022] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0023] Figure 1 This is a schematic diagram of the system structure in one or more embodiments of the present invention; Figure 2 This is a schematic diagram of an airport structure according to one or more embodiments of the present invention; Figure 3 This is a schematic diagram of the drone and charging pile structure in one or more embodiments of the present invention. Figure 1 ; Figure 4 This is a schematic diagram of the drone and charging pile structure in one or more embodiments of the present invention. Figure 2 ; Figure 5 This is a schematic diagram of a charging pile structure in one or more embodiments of the present invention; Figure 6 This is a schematic diagram of the charging connector structure in one or more embodiments of the present invention; Figure 7 This is a flowchart of an automatic recharging method for unmanned aerial vehicles (UAVs) according to one or more embodiments of the present invention; Figure 8 This is a flowchart of the unmanned aerial vehicle (UAV) airport charging scheduling process in one or more embodiments of the present invention; Figure 9 This is a schematic diagram of the drone's travel path in one or more embodiments of the present invention.

[0024] In the image: 1. Airport cabin; 2. Apron; 3. Charging station; 4. Drone; 102. Canopy; 103. Automatic access control module; 104. Temperature and humidity control module; 105. Airport entrance / exit; 201. I-shaped takeoff and landing sign; 202. Waiting area; 203. Weather monitoring pole; 204. Weather observation module; 301. Charging interface; 302. Outer ring electromagnet; 303. Infrared transmitter; 304. Guide rail; 305. Guide groove; 401. Fuselage; 402. Landing gear; 403. Drone battery; 404. Auxiliary charging device; 405. Charging cable; 406. Flight control system; 407. Drive motor; 408. Front wheel; 409. Rear wheel; 410. Charging connector; 411. Outer ring magnet; 412. Infrared receiver. Detailed Implementation

[0025] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0026] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0027] Example 1 In one typical embodiment of this application, an unmanned aerial vehicle (UAV) airport system is provided, such as... Figures 1-6 As shown, it includes: Airport cabin 1, several charging piles 3 are fixedly installed inside the airport cabin 1, and an airport entrance / exit 104 is opened on one side of the airport cabin 1. Apron 2 is located outside airport entrance / exit 104; The charging station 3 has a charging interface 301 on its side, which is used for physical docking with the drone 4. The drone 4 includes a fuselage 401 and a landing gear 402. The fuselage 401 is equipped with a drone battery 403 and an auxiliary charging device 404. The landing gear 402 is equipped with a self-drive component, which includes wheels and a drive motor 407. The wheels can be used to move between the apron and the airport cabin, and the drive motor can drive the drone to the charging station. One end of the landing gear 402 is equipped with a charging connector 410 for docking with the charging station 3. The charging connector 410 is connected to the auxiliary charging device 404 through a charging cable 405. The charging connector 410 can dock with the charging interface 301 to establish a charging circuit.

[0028] Specifically, such as Figure 1 and Figure 2As shown, the interior of the airport cabin 1 is a rectangular area, with the apron 2 located adjacent to the outer side, serving as a platform for drone takeoff and landing. The airport cabin 1 houses the airport main control system, which is communicatively connected to the charging piles and the drones.

[0029] In this embodiment, several charging piles 3 are fixedly installed inside the airport cabin 1, and can connect to the drone 4 through the charging interface 301 to charge the drone battery 403. For example, Figure 3 and Figure 4 As shown, the charging port of the drone battery 403 is plugged into the auxiliary charging device 404, and the connection is detachable. The auxiliary charging device 404 uses an existing adapter and includes a circuit board, an input interface, an output interface, and a housing. Its circuit board is encapsulated within the housing and includes two input interfaces, a positive terminal and a negative terminal. These two input interfaces are connected to left and right charging connectors respectively via charging cables. Figure 4 As shown, the charging connectors 410 are located at the front ends of the left and right sides of the bottom of the landing gear 402. The two charging connectors 410 are the positive and negative terminals, respectively, and can be connected to the charging interfaces 301 at both ends of the side of the charging pile. In this embodiment, the charging connectors use charging copper sheets, and the charging interfaces use charging copper cores. When the charging connectors and charging interfaces are stably connected, a charging circuit is established between the drone and the charging pile, and the drone battery is charged through an auxiliary charging device.

[0030] By adopting the above solution, the UAV airport system of this embodiment eliminates the need for complex mechanical structures to disassemble UAV batteries. The charging piles are small in size and require little space, making it possible to deploy large numbers of UAVs within the airport and improving its capacity. Furthermore, the presence of auxiliary charging devices allows for standardized design of charging interfaces and connectors. Multiple charging piles with different charging power can be installed within the airport to match and charge different UAV battery models, thus meeting the recharge needs of different UAV models, improving the airport's versatility, effectively reducing construction costs, and providing endurance for UAV swarms to perform multi-aircraft collaborative operations and high-frequency missions. In addition, this embodiment achieves wheeled movement for UAVs through self-drive components, reducing the requirements for UAV takeoff and landing accuracy, making it well-suited for complex environments, and significantly improving the success rate of UAV landings and charging efficiency.

[0031] To further improve the versatility of charging stations, such as Figure 3 and Figure 5As shown, multiple positive and negative charging ports 301 are installed at both ends of the charging pile 3, which can be adapted to the landing gear width of different drone models. Therefore, for a given charging pile, as long as the charging power and current of the drone battery are matched, the distance between the multiple ports on the charging pile in this embodiment can match the landing gear width of most drones currently on the market, making the charging pile more compatible and further improving the versatility of the airport where the charging pile is located.

[0032] To ensure the stability of the charging process, this embodiment is equipped with a magnetic locking component, such as... Figure 4 and Figure 6 As shown, an outer ring magnet 411 is fixedly arranged around the charging copper sheet, and an outer ring electromagnet 302 is fixedly arranged around the charging interface 301. The positions of the outer ring magnet 411 and the outer ring electromagnet 302 are correspondingly arranged. When the outer ring magnet and the outer ring electromagnet are attracted to each other, the charging connector and the charging interface are precisely aligned and tightly contacted to achieve locking, improving the stability of the contact at the charging interface and effectively preventing the charging connector from detaching from the charging interface. The charging connector 410 is a circular charging copper sheet, and the outer ring magnet 411 is coaxially arranged in a ring around the outer ring of the charging copper sheet. An insulating layer is provided between the outer ring magnet 411 and the charging copper sheet to prevent current short circuits or magnetic field interference. Similarly, an insulating layer is also provided between the outer ring electromagnet 302 and the charging copper core, serving the same purpose.

[0033] The outer ring magnet is a permanent magnet, and the outer ring electromagnet is a normally closed electromagnet. The permanent magnet, coil, and iron core are connected in series in the same main magnetic circuit. Under normal conditions, the permanent magnet attracts the outer ring magnet using its magnetism. When charging is complete, the coil is energized, and the magnetism inside the outer ring electromagnet cancels out, thus unlocking the drone from the charging station.

[0034] In this embodiment, the charging pile is equipped with a local controller and an AC / DC converter. The local controller communicates with the airport's main control system and can report data such as the charging pile ID, charging status, power level, and error codes to the airport's main control system in real time. The AC / DC converter converts the AC input of the charging pile into DC output. The AC / DC converter is connected to the outer electromagnet through an electromagnet drive circuit. When a drone on a charging pile finishes charging, the airport's main control system sends a command to the local controller. The local controller sends a low-level signal to trigger the electromagnet drive circuit, which then powers on and unlocks the outer electromagnet, allowing the drone to detach from the charging pile.

[0035] To achieve automatic charging of drones, such as Figure 4As shown, a flight control system 406 is installed on the upper part of the fuselage 401. The flight control system 406 is connected to the drive motor 407. The flight control system 406 integrates a main processor, an RTK positioning module, an inertial measurement unit, and a 5G module. The 5G module receives correction data sent by the ground reference station and forwards it to the RTK positioning module. The RTK positioning module receives satellite signals from the Beidou navigation system and correction data from the reference station. After RTK calculation, it sends high-precision positioning data to the main processor. The main processor can receive high-precision positioning data sent by the RTK positioning module and deviation information sent by the infrared receiver, and then control the flight drive motor of the UAV and the drive motor in this embodiment, so that the UAV can land in the vicinity of the charging pile and accurately walk to the charging pile for precise docking under infrared guidance.

[0036] To achieve self-propelled movement and flexible steering for the UAV, the self-propelled assembly includes two front wheels 408, two rear wheels 409, and two drive motors 407. The two drive motors 407 are respectively mounted on the left and right crossbars at the bottom of the landing gear 402, and their output shafts are connected to the rear wheels 409 for driving. The two drive motors 407 are electrically connected to the flight control system 406. During steering, directional deflection is achieved by controlling the different speeds of the two drive motors. In this embodiment, both the front wheels 408 and rear wheels 409 are high-strength polyurethane casters with a wheel diameter of 60mm, ensuring both support strength and flexible steering in conjunction with the different states of the left and right drive motors.

[0037] To improve the navigation accuracy of the drone to the target charging station, this embodiment includes an infrared module for infrared guidance. For example... Figures 3-5 As shown, multiple infrared transmitters 303 are installed on one side of the charging pile 3, and these transmitters 303 are integrated between the two charging ports 301 of the charging pile 3. Left and right infrared receivers 412 are fixedly installed on the landing gear 402. The infrared receivers 412 on both sides are electrically connected to the flight control system 406. The infrared receivers 412 can receive the infrared signals emitted by the infrared transmitters 303 and obtain deviation information. The main processor in the flight control system 406 controls the drive motors based on the deviation information, thereby controlling the speed and direction of the UAV.

[0038] Using the above scheme, the infrared transmitter, infrared receiver, and main processor of the flight control system work together. The infrared transmitter continuously emits infrared signals at different frequencies or in different encoding methods to form a clear spatial guidance reference. The infrared receiver can receive these signals in real time and determine the deviation information of its own position and direction based on the difference in the strength of the signals received from the left, right, front, and back. The flight control system continuously adjusts the speed and direction of the wheels based on the deviation information, so that the UAV can automatically correct its course and gradually align itself with the charging pile.

[0039] To further guide the drone accurately to the charging station and quickly achieve precise docking between the charging connector and the charging interface, a guide rail 304 is also provided on one side of the charging station 3 in this embodiment. Figures 3-5 As shown, the guide rail 304 is laid on the ground and fixed to it to guide the wheels approaching the charging pile, ensuring precise alignment between the charging connector and the charging interface. One end of the guide rail 304 extends below the charging interface 301 and connects to the charging pile 3. The other end of the guide rail 304 is provided with a guide groove 305. The width of the guide groove 305 gradually increases from the near end to the far end of the charging pile 3, forming a planar horn shape, which facilitates guiding the wheels into the guide rail and prevents the wheels from getting stuck outside the guide rail, thus improving the efficiency of the drone reaching the charging interface.

[0040] Using the above scheme, when the drone approaches a charging station at a certain distance, its wheels enter the guide rail via guide grooves, and then travel along the guide rail to accurately align the charging connector with the charging port of the charging station, establishing a charging circuit. This effectively improves the accuracy of the drone's movement and docking position with the charging station. As the drone moves directionally along the guide rail, it can sense the distance to the charging station using an infrared rangefinder on its fuselage, and the flight control system controls the drive motor to gradually decelerate until the outer ring magnet on the landing gear attracts the outer ring electromagnet on the charging station, thus making contact between the charging connector and the charging port of the charging station, ensuring charging stability.

[0041] To avoid confusion regarding the take-off and landing locations of different drones, such as Figure 2 As shown, circular area markers and I-shaped take-off and landing markers 201 are painted or pasted on the surface of the helipad 2. The I-shaped take-off and landing markers 201 are located in the center of the circular area markers to guide the drones to the optimal take-off and landing positions. The area outside the circular area markers on the helipad 2 is the drone waiting area 202.

[0042] In this embodiment, as Figure 2 As shown, a canopy 101 is fixedly installed on the top of the airport cabin 1, forming a closed structure to protect the drones and charging piles parked inside from damage caused by severe weather. In this embodiment, the canopy 101 is made of glass, which can reduce the interference of the canopy on RTK positioning signals and Beidou navigation positioning signals, ensuring the navigation accuracy of the drones.

[0043] To facilitate unified scheduling of takeoffs and landings, an airport entrance / exit 104 is located on one side of the airport cabin 1, allowing drones to enter or exit the airport cabin from the same direction. For example... Figure 2As shown, airport entrance / exit 104 is equipped with an automatic access control component 102 that can automatically open and close the door according to central control commands. The automatic access control component 102 adopts an existing structure, including a roller shutter door, a motor, a transmission chain, and a control element. The control element establishes communication with the airport's main control system. When an authorized drone needs to enter or exit, such as when a drone receives a mission command to go out or when a drone needs to enter the station after completing an inspection, the control element receives the command, identifies the authorized drone, and controls the motor to start. The transmission chain drives the roller shutter door's roller shaft to rotate, opening the roller shutter door. Under normal circumstances, the roller shutter door is closed to prevent rain, snow, or unauthorized personnel or objects from entering the airport cabin. At the same time, infrared photoelectric sensors are installed on both sides of the roller shutter door frame. If a person or object passes by when the roller shutter door is closing, the roller shutter door will immediately stop and open in the reverse direction to ensure safety.

[0044] To protect the electronic equipment in the airport cabin, such as Figure 1 and Figure 2 As shown, the airport cabin 1 is equipped with a temperature and humidity control module 103. The temperature and humidity control module 103 can adopt a constant temperature and humidity precision air conditioning system and is fixedly installed on the side wall of the airport cabin 1. It can accurately maintain a constant temperature and humidity environment inside the airport, effectively protect the drone and other electronic equipment, and thus extend the service life of the drone.

[0045] To improve the safety of drone operations, such as Figure 1 and Figure 2 As shown, a meteorological monitoring pole 203 is fixedly installed on one corner of the apron 2. A meteorological observation component 204 is installed on the upper part of the meteorological monitoring pole 203. The meteorological observation component 204 includes a wind speed and direction sensor, a temperature, humidity and air pressure sensor, a precipitation sensor and a visibility sensor. The meteorological observation component 204 is connected to the airport main control system and can send the monitoring data to the airport main control system in real time. The airport main control system determines whether the conditions are suitable for the UAV to go out to perform missions based on all the meteorological information obtained, so as to ensure the safety of the UAV's operation.

[0046] Example 2 In another typical embodiment of this application, an automatic recharging method for a drone is also provided, such as... Figures 7-9 As shown, it is based on the unmanned aerial vehicle airport system in Embodiment 1 and includes the following steps: After the drone returned and landed on the tarmac, the automatic access control system detected the drone's identity and opened, allowing the drone to enter the airport cabin. The airport's main control system performs scheduling based on the status information of charging piles and drones, including allocating charging piles to each drone, allocating departure times and planning conflict-free paths for drones based on the time slot reservation method, and finally obtaining time-space scheduling information. The airport's main control system sends instructions to the drone and the target charging station respectively based on time-space scheduling information. The charging station starts the infrared guidance mode. The drone's self-driving component adjusts its direction of travel based on the infrared guidance signal, turns into the guide rail and continues to move until the drone's charging connector is physically connected to the charging interface of the target charging station and is locked by magnetic attraction, thus establishing a stable charging circuit. After receiving the takeoff inspection command, the airport's main control system determines whether the takeoff conditions are met based on the meteorological and temperature information obtained by the meteorological observation components. If the takeoff conditions are met, the system automatically detects the status of each drone and charging station, selects available drones that meet the mission requirements, and issues control commands. The drone then activates its self-driving component, leaves the charging station, and enters the waiting area of ​​the apron through the airport entrance. After completing takeoff preparation and self-check actions in the waiting area, the drone enters the waiting state.

[0047] In this embodiment, during the scheduling process by the airport's main control system based on the status information of charging piles and drones, an optimal allocation algorithm is used to assign charging piles to drones in the current scheduling batch. This algorithm minimizes the total time spent by all assigned drones to complete the charging task, while also considering the status information of drones and charging piles, as well as model compatibility, to obtain comprehensively optimized charging pile allocation data. Furthermore, by triggering time allocation and time slot reservation mechanisms, the ground travel path of drones from their current location to the target charging pile is planned, and drones with priority allocation of charging piles are prioritized. Combined with the charging pile allocation data, this not only shortens the overall movement time of drones and effectively improves the overall scheduling efficiency of drones, but also ensures that available drones are available in the shortest possible time, guaranteeing a rapid response of drones to emergency tasks.

[0048] In this embodiment, the specific process by which the airport main control system performs scheduling based on the status information of charging piles and drones is as follows: S1. Obtain the status data of each charging pile and each returning drone, and construct a compatibility matrix and a time consumption matrix.

[0049] Specifically, the main control system of the drone airport acquires real-time status data of all returning drones and all charging stations. The status data for returning drones includes drone ID, battery model, current location, current battery level, battery capacity, and mission urgency. The status data for charging stations includes current status, model, and power information. The status data for charging stations located within the airport includes their current status (idle / occupied / faulty), as well as their model and power information.

[0050] In this embodiment, a binary compatibility matrix M is constructed, where element Mij=1 indicates that drone i is compatible with charging pile j, that is, the charging power matches and charging is possible; Mij=0 indicates incompatibility.

[0051] For all combinations where Mij=1, calculate the total time C spent by drone i using charging station j. In this embodiment, the entrance and exit of the drone airport are combined into one airport entrance / exit. The formula for calculating the total time spent by drone i from landing on the apron to reaching a certain drone charging station j and then leaving from the airport entrance / exit is: C= T t(i,j) + T c(i,j) + T b(i,j) ,in, T t(i,j) This is the estimated travel time from the entrance of the drone airport to the charging station j, based on a road network model. T c(i,j) The charging time is calculated based on the remaining battery power and battery capacity of drone i and the power information of charging station j. T b(i,j) This represents the estimated travel time from charging station j back to the exit of the drone airport, based on a road network model.

[0052] in, T t(i,j) , T b(i,j) It only relates to the charging pile (j); T c(i,j) The charging current of drone i is related to the charging power of charging station j. Therefore, when drone i selects charging station j for charging, its total time cost C can be determined. When m drones enter a drone airport with n charging stations, considering the charging compatibility between drones and charging stations, the time cost matrix can be expressed as: (1) Among them, C ij The total time spent by drone i entering drone charging station j.

[0053] Among them, for Mij Let the combination of =0 be given. Cij =INF, where INF is a maximum value, such as the maximum value that the system can recognize, indicating that the combination cannot be assigned.

[0054] S2. Based on the urgency of the task, the returning drones are initially screened and sorted to obtain the queue to be scheduled.

[0055] Specifically, the system prioritizes drones that need to complete recharging tasks based on task urgency (e.g., "urgent," "normal," "low priority"). These high-priority drones are then added to the current scheduling batch, while low-priority drones are temporarily stored in a waiting-to-schedule pool. The drones within the current batch are then sorted by urgency from highest to lowest, forming a waiting-to-schedule queue Dpriority, for example: Drone_3 (urgent) → Drone_1 (urgent) → Drone_5 (normal).

[0056] S3. Based on the compatibility matrix and time cost matrix, the optimal allocation algorithm is used to allocate charging piles to the queue to be scheduled, and the pile allocation data is obtained.

[0057] Specifically, it includes the following steps: S301. Based on the time cost matrix, determine the combination of returning drones and charging piles that require priority charging using a greedy algorithm.

[0058] Identify the drones that need to complete their recharging tasks first, so that usable drones can be obtained in the shortest possible time, for example, using a time-cost matrix. : (2) in, This indicates that the drone model i and the charging station model j are incompatible.

[0059] If one drone needs to be prioritized for recharging, then according to the greedy algorithm, the solution corresponding to the minimum value is found, that is, the allocation solution with the minimum time cost. In this embodiment, it is C. 14 =1 and C 26 =1. When the minimum value is greater than one, meaning there are multiple options with the same time cost, the selection is based on the following formula: (3) After removing mismatched model data from the row and column containing the minimum value, the scheme corresponding to the minimum value with the largest sum of the row and column is selected to reduce the overall time cost of recharging the remaining drones, optimize the scheduling scheme, and maximize the overall recharging efficiency.

[0060] In this embodiment, =13, =15. Therefore, drone number 2 is given priority to be assigned to charging station number 6 for recharging.

[0061] S302. Remove the allocated returning drones and charging stations from the time cost matrix to obtain the reduced time cost matrix.

[0062] Since drone #2 has been assigned to charging station #6, the time cost matrix needs to be recalculated to reduce the problem size. The adjusted time cost matrix is ​​as follows. It becomes: (4) Similarly, the greedy algorithm continues to search for the solution that minimizes the current time cost, i.e. =1, drone number 1 has been assigned to charging station number 4, then the reduced matrix It becomes: (5) S303. Reduce the reduced time cost matrix and find the optimal solution to obtain the pile location allocation data.

[0063] Time Spending Matrix Perform row reduction and column reduction separately: (6) That is, subtract the minimum value of its row and column from each element in the matrix. Not participating in the calculation can generate more zero elements, which represent relatively optimal allocation options, thus making it easier to find the optimal solution.

[0064] Perform row reduction on the matrix in equation (5) to ensure that each row has at least one zero element, resulting in the row-reduced time cost matrix. : (7) Perform column reduction on the matrix in equation (7) to ensure that each column has at least one zero element. The time cost matrix after column reduction is... for: (8) Finding the optimal solution: For the matrix in equation (8), the minimum number of lines covering all zero elements is used to find the minimum number of lines. If the number of lines is equal to the matrix order, that is, the number of drones is equal to the number of charging piles, then the optimal allocation scheme is found: each zero element corresponds to a set of "drone-charging pile" allocation schemes, and there are no repetitions. If the number of lines is less than the matrix order, then the minimum value of the uncovered elements in the matrix needs to be calculated, the minimum value is subtracted from the uncovered elements, and the minimum value is added to the elements at the intersection of the two covering lines. This step is repeated until the number of lines is equal to the matrix order.

[0065] Map the zero-element allocation scheme in the reduced matrix back to the original time-cost matrix. The final pile location allocation data is obtained. , }

[0066] Based on the optimal solution, the charging station allocation data was obtained. Drone 2 was assigned to charging station 6 to ensure that a usable drone was available in the shortest possible time. Then, drone 1 was assigned to charging station 4; drone 3 to charging station 1; and drone 4 to charging station 3. According to the original time cost matrix, the total time cost under this allocation scheme is 1 + 1 + 2 + 2 = 6.

[0067] S4. Based on the pile location allocation data, the time slot reservation method is used to allocate departure time to each UAV and plan conflict-free paths to obtain time-space scheduling information.

[0068] In this embodiment, in the two-dimensional planar road network model, the time slot reservation method is used to plan the shortest conflict-free path for the drones that have been allocated charging piles, which can avoid channel occupation conflicts and reduce the risk of drone collisions and blockages.

[0069] In the two-dimensional planar road network model, the internal passages of the airport are abstracted as edges divided into multiple road segments, such as "segment 1-2" and "segment 3-4". Key locations such as intersections, buffer zones, and charging pile entrances are abstracted as vertices V (such as "apron exit V1" and "charging pile entrance V5"). The occupancy status r(e,t)∈{0,1} of each passage e∈E at time t is defined, where r(e,t)=1 indicates that passage e is occupied at time t, and r(e,t)=0 indicates that it is idle. For bidirectional passages, an additional constraint on the opposite passage is added: r(e,t)+r(eo,t)≤1 (eo is the opposite passage of e), that is, bidirectional passages cannot be occupied simultaneously in the same time slot.

[0070] The specific process of allocating departure times for each drone and planning conflict-free paths to obtain time-space scheduling information is as follows: S401. Plan the static shortest path for each UAV, divide the airport passage into multiple segments, and identify potential conflict points between all static shortest paths.

[0071] Based on the road network model, Dijkstra's algorithm is used to plan the static shortest path from the current location to the target charging station.

[0072] S402. Calculate an allowed departure time window for each drone, including the earliest departure time and the latest departure time, and use a greedy insertion algorithm to assign a specific departure time to the drone.

[0073] Specifically, the main control system calculates the allowed departure time window [ESTi,LSTi] for each drone, where ESTi is the earliest departure time, which refers to the time after the drone lands and completes its self-check, and is ready on the tarmac. LSTi is the latest departure time, which can be calculated backward from the mission deadline. For example, if the mission requires the drone to be ready before 10:00 and the total recharge time is about 30 minutes, then LSTi = 9:30.

[0074] Based on the greedy insertion strategy, the current system time is obtained, and all assigned drones with an earliest departure time no later than the system time are filtered. The selected drones are then simulated to travel from the current system time T, following the static shortest path from their current location to the target charging station obtained in step S401, and using the time slot reservation table of the current airport passage. The charging completion time is calculated. The drone with the earliest charging completion time is selected, and its departure time is set to the system time. After setting this, the system status is updated, including the current system time, the time slot reservation table of the current airport passage, and the status of the remaining drones. This process is repeated until the departure times of all assigned drones are determined.

[0075] S403. Based on the departure time of each UAV, reserve an exclusive time window for each potential conflict point on its static shortest path and generate time-space scheduling information.

[0076] Based on the departure time of each drone, a time window for exclusive passage is reserved for each potential conflict point on its static shortest path, forming a time slot reservation table for multiple potential conflict points. Potential conflict points include path intersections, overlapping path segments, and shared path segments.

[0077] When making a reservation plan time window for each drone, it is necessary to calculate the time window based on the length of each channel on the static shortest path and the drone's speed, and then check whether the time window conflicts with existing reservations in the time slot reservation table.

[0078] If there is no conflict with an existing reservation, mark the time slot as "occupied (drone i)" directly in the time slot reservation table of the potential conflict point, and complete the reservation.

[0079] If there is a conflict with an existing reservation, the drone can be adjusted by slightly adjusting its speed or waiting in a non-conflicting section to ensure it operates strictly according to the reservation schedule, thus avoiding any spatial conflicts. Specifically, try slightly adjusting the drone's speed, such as increasing it from 1 m / s to 1.2 m / s, to shorten the passage time. If adjusting the speed cannot resolve the conflict, have the drone wait at a node on the path until the conflicting time slot ends, recalculate the time window, and check for conflicts until a conflict-free time slot solution is found.

[0080] Among all conflict-free time slot options, the option that allows the drone to complete the entire "flight-charging-return" process earliest is selected. Its departure time is then officially assigned, and the time slot reservation results are written into the channel time slot reservation table. This ultimately obtains time-space scheduling information, determining the flight path for each drone. Finally, the drone airport's main control system, based on the time-space scheduling information, sends path instructions containing detailed departure times and time slot reservation points to each drone. The drones execute these instructions, achieving an efficient and conflict-free automatic charging process.

[0081] Specifically, after completing the pile location allocation and path planning to obtain the time-space scheduling information of each returning UAV, the self-driving component, infrared module, etc., execute the above scheduling plan. During the path execution process, to further ensure the operational safety of the UAVs and avoid collisions between them, this embodiment also performs safe distance monitoring.

[0082] Among them, a safety R is set for each drone. safe (e.g., 0.5 meters, adjustable according to drone size) No other drones are allowed to enter within the safety radius. The main control system obtains the real-time position coordinates of each drone through BeiDou and RTK navigation and positioning, and calculates the distance d between any two drones. ij (t). Once d is detected... ij (t)<R safe The system immediately sends a stop or speed setting command to the drone behind, forcing it to slow down or stop until the distance between the two drones is restored to R. safe above.

[0083] Furthermore, in a preferred embodiment, if the position of the UAV deviates after entering the channel at the allocated time, it can be corrected in real time by an obstacle avoidance sensor. The obstacle avoidance sensor is installed on the edge of the UAV. When the UAV approaches the target stake within 2-3 meters, it switches to infrared guidance mode for final precise adjustment.

[0084] The charging pile's infrared transmitter continuously emits coded infrared signals, avoiding interference with other devices' signals; the left and right infrared receivers on the bottom of the drone receive the signals respectively, and the signal strength difference is calculated according to formula (9): (9) in I L I represents the signal strength of the left receiver. R To determine the signal strength of the right receiver, the proportional control algorithm of formula (10) is used to automatically adjust the steering speed of the UAV chassis, so that ΔI gradually approaches 0, that is, the UAV's central axis is aligned with the charging pile docking axis, and finally the UAV and the charging pile are docked with millimeter-level precision, ensuring accurate connection of the charging interface.

[0085] (10) in, k is the chassis steering angular velocity. p This is a proportionality coefficient, which can be optimized through debugging.

[0086] In this embodiment, during the drone charging process, the current detection device inside the charging pile monitors the charging status (such as voltage, current, temperature, etc.), the charging station's own operating status, and docking status in real time, and uploads the monitoring information to the airport's main control system for remote monitoring and fault early warning. The control terminal inside the drone airport detects the temperature and humidity conditions inside the airport and maintains a constant temperature and humidity environment through the airport's internal temperature and humidity control module, protecting the drone's electronic equipment and extending its service life. All status data, including charging progress, environmental parameters, and equipment health, are aggregated at the airport control terminal, generating an operation and maintenance report and synchronizing it to the airport's main control system, providing a basis for decision-making in task scheduling, battery maintenance, and airport management.

[0087] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An unmanned aerial vehicle (UAV) airport system, characterized in that, include: An airport cabin, in which several charging piles are fixedly installed, and an airport entrance / exit is opened on one side of the airport cabin; The apron is located outside the airport entrance / exit. The charging station has a charging interface on its side, which is used to connect to the drone. The drone includes a fuselage and landing gear. The fuselage is equipped with a drone battery and an auxiliary charging device. The landing gear is equipped with wheels and a drive motor at the bottom. The wheels are used to move between the apron and the airport cabin. The drive motor can drive the drone to the charging station. One end of the landing gear is equipped with a charging connector for docking with the charging station. The charging connector is connected to the auxiliary charging device via a charging cable. The charging connector can dock with the charging interface to establish a charging circuit.

2. The unmanned aerial vehicle (UAV) airport system as described in claim 1, characterized in that, It also includes an airport main control system, which is located inside the airport cabin and is communicatively connected to the charging pile and the drone, respectively.

3. The unmanned aerial vehicle (UAV) airport system as described in claim 1, characterized in that, The charging pile is fixedly connected to a guide rail on the side facing the drone body. The guide rail is laid on the ground and has a set length. The free end of the guide rail is provided with a guide groove, and the width of the guide groove gradually increases from the near end to the far end of the charging pile.

4. The unmanned aerial vehicle (UAV) airport system as described in claim 2, characterized in that, The fuselage is equipped with a flight control system, which is communicatively connected to the airport's main control system. Multiple infrared transmitters are located on one side of the charging pile, and left and right infrared receivers are located on the landing gear. The left and right infrared receivers can receive the infrared signals emitted by the infrared transmitters and obtain deviation information. The infrared receivers are connected to the flight control system, which controls the drive motor based on the deviation information.

5. The unmanned aerial vehicle (UAV) airport system as described in claim 1, characterized in that, An outer ring magnet is fixedly arranged around the charging connector, and an outer ring electromagnet is fixedly arranged around the charging interface; when the outer ring magnet and the outer ring electromagnet are attracted to each other, the charging connector and the charging interface are in contact.

6. The unmanned aerial vehicle (UAV) airport system as described in claim 5, characterized in that, The outer ring magnets are arranged in a circular pattern, the charging connector is coaxially arranged with the outer ring magnets, and an insulating layer is provided between the charging connector and the outer ring magnets.

7. The unmanned aerial vehicle (UAV) airport system as described in claim 1, characterized in that, The top of the airport cabin is equipped with a canopy, forming a closed structure, and the canopy is made of glass.

8. The unmanned aerial vehicle (UAV) airport system as described in claim 1, characterized in that, A meteorological monitoring pole is fixedly installed on the helipad, and a meteorological observation component is installed on the meteorological monitoring pole. The meteorological observation component includes a wind speed and direction sensor, a temperature, humidity and air pressure sensor, a precipitation sensor and a visibility sensor.

9. A method for automatic recharging of unmanned aerial vehicles (UAVs), based on an UAV airport system as described in any one of claims 1-8, characterized in that, Includes the following steps: After the drone returned and landed on the tarmac, the automatic access control system detected the drone's identity and opened, allowing the drone to enter the airport cabin. The airport's main control system performs scheduling based on the status information of charging piles and drones, obtaining time-space scheduling information. The airport's main control system sends instructions to the drone and the target charging station respectively based on time-space scheduling information. The charging station starts the infrared guidance mode. The drone's self-driving component adjusts its direction of travel based on the infrared guidance signal, turns into the guide rail and continues to move until the drone's charging connector is physically connected to the charging interface of the target charging station and is locked by magnetic attraction, thus establishing a stable charging circuit. After receiving the takeoff inspection command, the airport's main control system determines whether the takeoff conditions are met based on the meteorological and temperature information obtained by the meteorological observation components. If the takeoff conditions are met, the system automatically detects the status of each drone, selects the available drones that meet the mission requirements, and issues control commands. The drones then activate their self-propulsion components to move through the airport entrance and exit, leave the airport cabin, and enter the waiting area on the external apron. After completing the takeoff preparation and self-check actions in the waiting area, the drones enter the waiting state.

10. The automatic recharging method for a drone as described in claim 9, characterized in that, The airport's main control system performs scheduling based on the status information of charging piles and drones, and the specific process by which it obtains time-space scheduling information is as follows: S1. Obtain the status data of each charging pile and the status data of each returning drone, and construct a compatibility matrix and a time consumption matrix; S2. Based on the urgency of the task, perform preliminary screening and sorting of the returning drones to obtain the queue to be scheduled; S3. Based on the compatibility matrix and time consumption matrix, the optimal allocation algorithm is used to allocate charging piles to the queue to be scheduled, and the pile allocation data is obtained. S4. Based on the pile location allocation data, the time slot reservation method is used to allocate departure time to each UAV and plan conflict-free paths to obtain time-space scheduling information.

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