A method and device for controlling charging of a drone nest, and related media

Abstract

The application discloses a kind of unmanned aerial vehicle nest charging control method, device and related medium, the method includes the multiple layer of the nest layer position configuration data is divided into at least two mutually exclusive charging group, and the battery capacity information of the unmanned aerial vehicle in empty and the unmanned aerial vehicle in nest is collected respectively and the unmanned aerial vehicle state is updated, and initial landing scheduling data is obtained by integration;Initial landing scheduling data is checked to layer position occupation state, and final landing scheduling data is obtained;Accordingly, the charging layer list of this round is generated and mutual exclusion verification operation is executed, and anti-interference charging control data is obtained;Anti-interference charging control data is periodically polled, and charging polling synchronization data is obtained.The final landing scheduling data generated by calculation in the application generates anti-interference charging control data, and anti-interference charging control data is periodically polled, and charging polling synchronization data is obtained, so that the coupling interference caused by simultaneous charging of adjacent layers in unmanned aerial vehicle nest can be effectively avoided.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) technology, and in particular to a UAV nest charging control method, device, and related medium. Background Technology

[0002] As drone swarm performances continue to expand in scale, vertically stacked drone nests are used for centralized parking and automatic charging of multiple drones. These nests often employ transmitting coils on the sidewalls of the drone nests in conjunction with receiving coils on the sidewalls of the drones for wireless power transmission. Due to the dense arrangement of multiple drones, electromagnetic coupling interference can easily occur between adjacent coil layers during charging. When adjacent layers are charging simultaneously, the alternating magnetic field can induce unexpected electrical signals in nearby receiving coils and conduct them to the rectifier circuit, leading to abnormal voltage in the rectifier circuit and the risk of device overheating, resulting in unstable charging. Existing methods, such as increasing the interlayer spacing or adding shielding materials, are insufficient to address this charging instability. Summary of the Invention

[0003] This invention provides a method, device, and related medium for controlling the charging of drone nests, aiming to solve the technical problem in the prior art where simultaneous wireless charging of adjacent layers of stacked nests causes electromagnetic coupling interference, resulting in abnormal rectification circuits and unstable charging.

[0004] In a first aspect, embodiments of the present invention provide a method for controlling the charging of a drone's nest, comprising:

[0005] Obtain the nest layer configuration data, and divide the multiple layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data;

[0006] Based on the hierarchical charging strategy data, the battery power information of the airborne drones and the drones in the nest are collected and the drone status is updated. The data is then integrated to obtain the initial landing scheduling data.

[0007] The initial landing scheduling data is checked for layer occupancy status. When the target layer is occupied, the comprehensive priority score of the returning UAV is calculated, and the scheduling is performed according to the comprehensive priority score to obtain the final landing scheduling data.

[0008] Based on the final landing scheduling data, generate the current round charging layer list and perform mutual exclusion verification operation to obtain anti-interference charging control data;

[0009] The anti-interference charging control data is periodically polled and updated synchronously to obtain charging polling synchronization data.

[0010] Secondly, embodiments of the present invention provide a drone nest charging control device, comprising:

[0011] The data acquisition unit is used to acquire the nest layer configuration data and divide the multiple layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data.

[0012] The data update unit is used to collect battery power information of the airborne drone and the drone in the nest according to the hierarchical charging strategy data and update the drone status, and integrate them to obtain the initial landing scheduling data.

[0013] The data scheduling unit is used to check the layer occupancy status of the initial landing scheduling data. When the target layer is occupied, it calculates the comprehensive priority score of the returning UAV and performs scheduling processing according to the comprehensive priority score to obtain the final landing scheduling data.

[0014] The data verification unit is used to generate a charging layer list for this round based on the final landing scheduling data and perform a mutual exclusion verification operation to obtain anti-interference charging control data.

[0015] The data synchronization unit is used to periodically poll the anti-interference charging control data and perform data synchronization updates to obtain charging polling synchronization data.

[0016] Thirdly, embodiments of the present invention provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the UAV nest charging control method of the first aspect.

[0017] Fourthly, embodiments of the present invention provide a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, it implements the UAV nest charging control method of the first aspect.

[0018] This invention provides a method for controlling drone nest charging, including acquiring nest layer configuration data, dividing multiple layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data; collecting battery power information of airborne drones and drones in the nest according to the layered charging strategy data and updating the drone status, integrating them to obtain initial landing scheduling data; checking the layer occupancy status of the initial landing scheduling data, and when the target layer is occupied, calculating the comprehensive priority score of the returning drone, and performing scheduling processing according to the comprehensive priority score to obtain final landing scheduling data; generating a current-cycle charging layer list based on the final landing scheduling data and performing a mutual exclusion verification operation to obtain anti-interference charging control data; periodically polling the anti-interference charging control data and updating the data synchronously to obtain charging polling synchronization data. This invention generates anti-interference charging control data by calculating the final landing scheduling data and periodically polls the anti-interference charging control data to obtain charging polling synchronization data, thus effectively avoiding coupling interference caused by simultaneous charging of adjacent layers in the drone nest.

[0019] This invention also provides a drone nest charging control device, a computer device, and a storage medium, which have the same beneficial effects as described above. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A flowchart illustrating a method for controlling the charging of a drone's nest, provided in an embodiment of the present invention;

[0022] Figure 2 This is a schematic block diagram of a drone nest charging control device provided in an embodiment of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0025] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0026] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0027] Please see below. Figure 1 , Figure 1 The flowchart of a drone nest charging control method provided in an embodiment of the present invention specifically includes steps S101 to S105.

[0028] S101. Obtain the nest layer configuration data, and divide the multiple layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data.

[0029] S102. Collect battery power information of airborne and nested drones according to the hierarchical charging strategy data and update the drone status, and integrate them to obtain the initial landing scheduling data.

[0030] S103. Check the layer occupancy status of the initial landing scheduling data. When the target layer is occupied, calculate the comprehensive priority score of the returning UAV and perform scheduling processing according to the comprehensive priority score to obtain the final landing scheduling data.

[0031] S104. Generate the current round charging layer list based on the final landing scheduling data and perform a mutual exclusion check operation to obtain anti-interference charging control data;

[0032] S105. Periodically poll the anti-interference charging control data and update the data synchronously to obtain charging polling synchronization data.

[0033] In step S101, the nest layer configuration data is obtained, the layer number and availability status of each layer are parsed, and multiple layers are divided into at least two mutually exclusive charging groups, such as grouping and managing by odd-numbered layers and even-numbered layers; at any given time, only one group of charging is activated, and when switching groups, the previous group is stopped and shut down first, and then the currently activated charging group is updated after the safety delay ends to obtain the layered charging strategy data.

[0034] In one embodiment, step S101 includes:

[0035] The data parsing layer number of the nest layer is configured and grouped into odd and even arrays to obtain charging status identification data;

[0036] The charging status identifier data is compared with the layer start request, and the current charging group is determined according to the odd and even groups of the target layer to obtain the verification result data.

[0037] When the verification data triggers a switch, a stop charging command is sent and the coil power supply and rectification path are turned off. After a safety delay, the current charging group is updated to obtain the switching control data.

[0038] The hardware interlock is configured using the switching control data to connect interlock relays in series in the coil circuits of the odd and even arrays, so that only one path is turned on at any given time, thus obtaining the interlock configuration data;

[0039] Anomaly monitoring and processing are performed on the interlock configuration data to obtain hierarchical charging strategy data.

[0040] In this embodiment, nest layer configuration data can be obtained in advance. This data includes at least the total number of layers, layer numbers, and the availability status of each layer. Taking a five-layer vertically stacked nest as an example, the layer numbers in the nest layer configuration data are parsed, and multiple layers are divided into at least two mutually exclusive charging groups based on the parity of the layer numbers. The odd-numbered groups include layers 1, 3, and 5, while the even-numbered groups include layers 2 and 4. At any given time, only one charging group is allowed to be in a wireless charging enabled state, and the layer above and below the currently charging layer is kept in a non-charging state, thus preventing adjacent layers from charging simultaneously under dense multi-layered layout conditions. After grouping the layer numbers, charging status identification data is maintained to characterize the currently active charging group status. Specifically, a global variable `current_charging_group` is set to indicate the currently active charging group, with values ​​including ODD, EVEN, and IDLE. ODD represents the currently active odd-numbered group, EVEN represents the currently active even-numbered group, and IDLE indicates that no layer is currently charging. The current_charging_group has an exclusive characteristic, allowing it to be in only one valid value at any given time, and the previous charging group is completely shut down before the charging group switch is performed, so that the charging status identification data is consistent with the actual charging status of the nest.

[0041] Upon receiving a layer-level initiation request, the charging status identifier data is compared with the layer-level initiation request. The current charging group is determined based on the odd / even group of the target layer, and verification result data is output. When the scheduling module requests to initiate wireless charging for the 3rd layer, it determines that the 3rd layer belongs to the odd group and reads current_charging_group: if current_charging_group is EVEN, verification result data rejecting immediate initiation is output, and the layer-level initiation request is placed in the waiting queue or a charging group switch is triggered; if current_charging_group is ODD or IDLE, verification result data allowing initiation of charging for the odd group is output. Correspondingly, when the target layer belongs to the even group, verification result data allowing initiation is output only when current_charging_group is not ODD, thereby ensuring at the logical level that wireless charging is not initiated simultaneously for odd and even groups.

[0042] When the verification result data triggers a charging group switch, a switching control process is executed and switching control data is generated. Specifically, a stop-charging command is sent to all layers in the currently active charging group. Upon receiving the stop-charging command, the local control unit of each layer shuts off the power supply to the transmitting coil and disconnects the UAV rectification path, causing the corresponding layer to enter a non-charging state. A safety delay is then initiated, typically 300-500ms, to allow the magnetic field to decay and residual circuit energy to be released. After the safety delay ends, the value of `current_charging_group` is updated, for example, from `ODD` to `EVEN`, and a start command is sent to the layers in the newly activated charging group, causing the corresponding layers to enter a charging state. The safety delay is configurable and can also be used in conjunction with current or magnetic field sensors to detect the decay state. The update of `current_charging_group` and the activation of the new group are only executed after the detection result meets the zeroing condition, thereby improving the safety and consistency of the switching process.

[0043] After generating the switching control data, the hardware interlock is further configured using the switching control data to obtain interlock configuration data, ensuring that the odd and even arrays remain mutually exclusive at the hardware execution level. A hardware interlock relay is set in the power drive circuit, allowing the odd and even array transmitting coil power supply circuits to share a single double-throw relay. This relay physically connects only one power supply circuit at any given time, ensuring that only one circuit is active at any given moment. When the switching control data is output, the interlock relay is synchronously driven to switch its contact position, providing power to the coil circuit corresponding to the current_charging_group while keeping the other coil circuit disconnected. This provides hardware-level mutual exclusion protection in addition to software control. After completing the interlock configuration, the interlock configuration data undergoes anomaly monitoring and processing, and hierarchical charging strategy data is output accordingly. The current output status of the odd and even array transmitting coils is continuously monitored using a current sensor. When both sets of transmitting coils are detected to have current output simultaneously, an emergency power-off is triggered, a fault log is reported, and all drones are placed in a charging disabled state. This charging disabled state remains in effect until manually reset or after a self-test. Through the collaborative processing of the above grouping, comparison and verification, switching control, hardware interlocking and anomaly monitoring, hierarchical charging strategy data that can be used for subsequent steps is output.

[0044] In step S102, under the management framework of the hierarchical charging strategy data, the ground station collects battery power information of both airborne and nested UAVs and updates the UAV status according to a unified standard. Specifically, the airborne UAV's onboard battery management unit samples voltage, current, temperature, remaining capacity, and battery state of charge percentage, which is periodically reported to the ground station by the flight control system. The nested UAV's local control unit reads the battery state of charge percentage through a local interface or short-range communication, or the UAV maintains a low-power reporting mode and sends simplified heartbeat information. The ground station writes the above multi-source data into the global UAV status table and updates the records, thereby integrating the initial landing scheduling data.

[0045] In one embodiment, step S102 includes:

[0046] Based on the hierarchical charging strategy, the identifier of the airborne drone is extracted to obtain the power collection target data.

[0047] The onboard battery management unit is invoked to sample the battery power based on the power collection object data to obtain battery power information;

[0048] The battery power information is encapsulated into messages according to the flight control cycle, and the reporting code rate is set to obtain battery status message data.

[0049] The battery status message data is sent to the ground station via a wireless data transmission module, and the ground station receives the data.

[0050] The data received by the ground station is analyzed for power level, and the UAV status is updated based on the power level analysis results to obtain the initial landing scheduling data.

[0051] In this embodiment, based on the obtained hierarchical charging strategy data, the status of UAVs inside and outside the UAV nest is filtered. UAVs that are in flight and need to continuously report their battery status are extracted as in-flight UAV identifiers. Collection task parameters are assigned to each in-flight UAV identifier. These collection task parameters include at least the UAV number, sampling period, reporting code rate, and message type identifier, thereby obtaining the power collection object data. The power collection object data can be used as input for ground station polling scheduling and flight control reporting configuration, enabling each in-flight UAV to output battery power information under the same collection caliber. The onboard battery management unit (BMS) is invoked to sample power based on the power collection object data. Specifically, each in-flight UAV is equipped with a smart battery, which integrates a battery management system (BMS). The BMS reads the individual cell voltage, total voltage and current, temperature, remaining capacity (mAh), and state of charge (SOC) at sampling periods. The SOC is expressed as a percentage (%). The BMS encapsulates the above sampling results into battery power information, along with a sampling timestamp and UAV number, for subsequent consistency verification and status updates at the ground station. After obtaining battery power information, the UAV flight controller encapsulates the battery power information into a message according to the flight control cycle and sets the reporting code rate to obtain battery status message data. The reporting code rate can be set to 1-5Hz. The flight controller packages the battery power information into the BATTERY_STATUS message or a custom message in the MAVLink protocol. The battery status message data includes fields such as UAV number, timestamp, SOC, total voltage, current, temperature, and remaining capacity (mAh), and can be output periodically according to the reporting code rate to meet the real-time maintenance needs of the ground station for the battery status of in-flight UAVs.

[0052] Furthermore, the battery status message data is transmitted to the ground station via a wireless data transmission module, and the ground station receives the data. The wireless data transmission module can be a 900MHz or 2.4GHz module, or a 4G / 5G communication module. During transmission, the flight controller sends the battery status message data frame by frame according to the reporting code rate. The ground station buffers and reassembles the messages at the receiving end, and aggregates them according to the UAV number to form the corresponding ground station received data, so as to continuously update the battery status record at the same UAV level. Finally, the ground station performs battery level analysis on the received data and updates the UAV status based on the analysis results to obtain the initial landing scheduling data. The ground station performs protocol parsing on the BATTERY_STATUS or custom messages, extracting power fields such as SOC, total voltage, current, temperature, remaining capacity (mAh), and timestamp, and writes the parsing results into the corresponding record in the UAV status table. The ground station then updates the UAV status to the current power status according to the latest timestamp, and outputs initial landing scheduling data for scheduling purposes. The initial landing scheduling data includes at least the airborne UAV identifier, the latest SOC percentage (%), the power sampling timestamp, and the task tag associated with the hierarchical charging strategy data, which is used for subsequent steps to uniformly process return landing and layer allocation.

[0053] In one embodiment, step S102 further includes:

[0054] The hierarchical charging strategy data is used for in-nest identification to determine the in-nest drone identifier and obtain in-nest data collection task data;

[0055] According to the in-nest data collection task call interface, the battery management system connects to the in-nest control unit via a contact interface or near-field communication to obtain the queried power data;

[0056] The queried power data is uploaded to the central controller and synchronized to the ground station to obtain the data reported in the nest;

[0057] Based on the data reported in the nest, the heartbeat energy level is sent to obtain the heartbeat energy level data;

[0058] The heart rate and charge data are written into a specific status table according to the weight of the timestamp source to obtain the initial landing scheduling data.

[0059] In this embodiment, after collecting the battery level of the drones in the air, in-nest identification processing is performed on the hierarchical charging strategy data. The central controller or ground station reads the layer number grouping information and available layer information of each layer in the hierarchical charging strategy data, and combines it with the layer occupancy status collection results to determine the set of drones in the nest parking state, and outputs the in-nest drone identifier; at the same time, in-nest collection task parameters are configured for each in-nest drone identifier. The in-nest collection task parameters include the target layer number, collection method flag, polling cycle, and reporting destination flag, thereby obtaining the in-nest collection task data. The collection method flag is used to select contact interface reading or near-field communication reading in the subsequent interface call stage, and to enable the heartbeat battery reporting mode when the low power reporting condition is met. Then, according to the in-nest collection task data, the interface is called to enable the battery management system of the in-nest drones to establish data interaction with the nest control unit to read the battery level. After the drone lands, the battery management system establishes a connection via a contact interface, such as a metal contact with the docking port of the nest control unit; or via near-field communication, such as NFC, Bluetooth Low Energy (BLE), or IRDA, to complete a handshake with the nest control unit. Once the connection is established, the nest control unit actively queries the battery's State of Charge (SOC, %) and can simultaneously read battery status fields such as voltage, current, and temperature to obtain the queried battery power data. To ensure data continuity, the nest control unit can repeatedly execute the query according to the polling cycle set for the nest data collection task, and append a timestamp and drone identifier to each query result.

[0060] After obtaining the queried power data, the nest control unit uploads the data to the central controller and synchronizes it with the ground station, obtaining the nest-reported data. The nest control unit can upload the queried power data to the central controller via a wired bus, such as CAN or RS485; or via a wireless network, such as Wi-Fi. Upon receiving the data, the central controller associates the nest-reported data of the same UAV with its layer information and forwards the nest-reported data to the ground station, enabling the ground station to maintain real-time power records of the UAVs in the nest under a unified data standard. If the UAV supports wireless charging status feedback extensions, such as Qi protocol extensions or custom protocols, the central controller can also combine the observable load status of the transmitter to make auxiliary estimations of the charging progress and verify its consistency with the queried power data, thereby improving the stability of the nest-reported power data. Based on this, a heartbeat power data is sent according to the nest-reported data to obtain the heartbeat power data. Some models maintain flight control standby mode within the nest, only disabling motor drives while retaining the data transmission module, enabling them to send simplified heartbeat packets to the ground station via the existing wireless data transmission method. These simplified heartbeat packets include at least battery, location, and status fields, and their transmission frequency can be reduced to 0.2-0.5Hz to lower energy consumption for maintaining communication within the nest. For models not maintaining standby mode, the nest control unit can periodically report heartbeat battery levels on behalf of the UAV, writing the latest SOC, timestamp, layer number, and charging status into the heartbeat payload and reporting it to the ground station, thus providing the ground station with a continuous stream of heartbeat battery data.

[0061] Finally, the heartbeat battery data is written into a specific status table according to the timestamp source weight to obtain the initial landing scheduling data. The ground station maintains a global UAV status table, with one status record for each UAV. After receiving in-nest reported data from the UAV control unit, heartbeat battery data from UAV standby mode, and battery data from other available channels, the ground station performs fusion writing on the multi-source data of the same UAV: ​​prioritizing the use of timestamps to update more recent data items, and assigning credibility weights to different sources. Conflicting fields are weighted and selected based on source weights, or multiple versions of fields are retained for use by the scheduling side. If an in-nest UAV does not update within a preset time, such as more than 10 seconds, the ground station marks the UAV status as having a communication anomaly and triggers an alarm or switches to the backup battery estimation method to prevent the scheduling side from using expired battery data. After completing the status table writing, the ground station summarizes and outputs the updated in-nest UAV identifier, latest SOC, timestamp, layer occupancy status, and charging status, etc., as part of the initial landing scheduling data, providing input for subsequent layer allocation and charging group switching.

[0062] In step S103, the initial landing scheduling data is checked for layer occupancy status, and a comprehensive priority score is calculated for the returning UAV when the target layer is occupied. The comprehensive priority score can be obtained by weighting factors such as battery charge percentage, mission type, and remaining return time. Then, the nest layer status table is read, and an available layer is searched in the corresponding charging group and the occupancy check is completed. If the search results show that there is no available layer in the target group, the landing assignment is updated according to the preset dynamic adjustment method, and the final landing scheduling data is output.

[0063] In one embodiment, step S103 includes:

[0064] Based on the initial landing scheduling data, extract the battery percentage, mission type, and remaining return time, and assign them to the comprehensive priority score accordingly to obtain the evaluation model data;

[0065] The evaluation model data is used to read the nest layer status, and the available layers are searched by odd or even arrays and checked for occupancy. If there are no available layers, dynamic adjustment trigger data is output to obtain matching result data.

[0066] The matching result data is dynamically adjusted according to a preset adjustment strategy to obtain adjustment scheduling data;

[0067] Based on the adjusted scheduling data, the target layer is pre-occupied and globally locked before allocation. At the same time, a preset aging factor is introduced to increase the comprehensive priority score according to the waiting time, so as to obtain the final landing scheduling data.

[0068] In this embodiment, when any returning drone initiates a landing request, the ground station extracts three fields from the initial landing scheduling data: State of Charge (SOC), mission type, and remaining return time. Weight parameters are then assigned to each of these three fields to calculate a comprehensive priority score P, resulting in evaluation model data. Specifically, SOC has a high weight (e.g., 0.6), with lower SOC resulting in a higher P, and a drone with SOC < 20% is marked as emergency. Mission type has a medium weight (e.g., 0.3), used to distinguish between main performance drones, backup drones, and test drones. Remaining return time has a low weight (e.g., 0.1), estimated from current battery power and hovering power consumption, and is included in the P calculation. The ground station records the P of each returning drone along with its target layer preference in the evaluation model data and sends the evaluation model data to the central controller for subsequent layer matching.

[0069] After receiving the evaluation model data, the nest layer status table is read to obtain the occupancy status of each layer. Layers are then searched and their occupancy checked according to odd or even numbers to output matching results. When the SOC of the returning UAV_088 is 18%, it is determined to be an urgent need and is prioritized for matching odd numbers. The central controller first searches for available layers in the odd number array (layers 1, 3, and 5). If available, an available layer is selected as the target layer and the pre-occupancy process begins. If all odd number layers are occupied, dynamic adjustment trigger data is output and written to the matching results, entering the dynamic adjustment phase. For non-urgent needs or backup aircraft, the central controller can prioritize searching for available layers in the even number array (layers 2 and 4) and perform the same occupancy check process to ensure that layer matching is consistent with the priority strategy of the returning queue.

[0070] When the matching result data contains dynamic adjustment trigger data, the central controller generates adjustment scheduling data according to a preset adjustment strategy. In this embodiment, the preset adjustment strategy includes three levels of dynamic adjustment. The first level is temporary cross-group admission within the same nest, used for high-priority special cases: when the returning UAV meets the emergency mission and SOC < 15%, it is allowed to temporarily land in an idle even-numbered layer, such as layer 2 (L2); the central controller marks this layer as an odd-numbered compatible mode and suspends the original even-numbered charging plan for this even-numbered layer in subsequent charging scheduling, while including this layer in the charging range in the next round of odd-numbered charging cycle; the ground station synchronously records alarm information, such as layer policy exception: UAV_088 occupies L2, is treated as an odd number, and the number of such special cases enabled in the same nest is set to an upper limit, such as a maximum of 1. The second level is delayed landing: When no vacant landing level is available and the special conditions are not met, the central controller instructs the returning UAV to enter the safe hovering point of the preset return waiting area and repeatedly queries the landing level status table every 10-15 seconds. At the same time, it calculates the maximum waiting time T_max for the returning UAV, T_max = (current remaining battery power / hovering power consumption) × 0.8. When the waiting time exceeds T_max, it is transferred to the backup nest scheduling. The third level is guidance to other nests: The ground station maintains a multi-nest resource pool, recording the real-time number of vacant landing levels, distance, and network status of each nest. When the current nest is continuously fully loaded, the central controller selects the nearest nest with an available target landing level, such as L5 of N02, and issues a replanning route command to the flight control to guide the returning UAV to the new nest for landing. At the same time, the cross-nest scheduling information is synchronized to the central mission database for subsequent take-off mission recall and resource backfilling.

[0071] After outputting the adjusted scheduling data, the central controller pre-occupies the target layer and enables global locking before allocation to reduce allocation conflicts caused by multiple drones concurrently vying for space. Before writing the target layer allocation result, the central controller locks the target layer and marks it as pre-occupied. After confirming that the returning drone has been granted landing permission and that the target layer status has not changed, the pre-occupied status is updated to occupied status, and the locking flags of unrelated layers are released. If a change in the target layer status is detected during pre-occupancy, the pre-occupancy is rolled back, and the layer retrieval and dynamic adjustment process is re-executed. At the same time, to improve the availability of queue scheduling, the central controller introduces an aging factor, mapping the waiting time to a priority increment and adding it to the comprehensive priority score P. This causes the P of returning drones that have been waiting for a long time to increase with the waiting time, thereby reducing the risk of starvation caused by continuous waiting. The central controller records a scheduling log after each allocation, delay, cross-nest guidance, or rollback retry. The scheduling log includes at least the following fields: UAV identifier, SOC, mission type, remaining return time, P, target layer, adjustment level, and waiting time. This log is used to optimize the layer allocation strategy and calibrate parameters. The final output includes the final landing scheduling data containing the target layer result and the lock status.

[0072] In step S104, a charging layer list for this round is generated based on the final landing scheduling data, and a mutual exclusion verification operation is performed on the charging layer list: the central controller coordinates the local control units of each layer to verify the charging status of adjacent layers. When an adjacent layer is detected to be charging, the corresponding layer keeps the transmitting coil closed and the rectification path after the receiving coil is disconnected. When an adjacent layer stops charging and the layer is included in the charging layer list for this round, charging is started in the order of restoring the rectification path first and then starting the transmitting coil. During the charging process, the status of adjacent layers and current abnormalities are continuously monitored. Once an adjacent layer is charging or has a current abnormality, the transmitting coil is immediately stopped and the rectification path is disconnected, thereby obtaining anti-interference charging control data.

[0073] In one embodiment, step S104 includes:

[0074] The final landing scheduling data is parsed, and a charging layer list for this round is generated by grouping by odd and even numbers and by emergency priority, thus obtaining the layer list verification data.

[0075] Mutual exclusion verification is performed based on the layer list verification data to verify the transmitting coils and charging status of the upper and lower layers, and to obtain charging permission verification data.

[0076] A rectification enable signal is sent to the charging permission verification data to enable the local control unit to close the rectifier switch to connect the receiving coil and the battery, and the gate is turned on and off by low resistance field effect control to obtain the rectification path status data.

[0077] Based on the rectifier circuit state data, a time delay stabilization process is performed to obtain the energy transfer state data;

[0078] The system reports the energy transfer status data and monitors the adjacent layers and rectified current; if the adjacent layers are charging or the current is abnormal, the coil is turned off and the rectifier switch is disconnected to obtain anti-interference charging control data.

[0079] In this embodiment, after receiving the final landing scheduling data, the system first parses it to extract the target layer number, emergency priority flag, and odd / even grouping information for each returning drone. The layers to be charged are then merged according to the odd / even grouping rules. For returning drones with emergency priority flags, the central controller prioritizes their target layer for inclusion in the current charging layer list, obtaining layer list verification data. The layer list verification data includes at least a set of layer numbers, the drone identifier corresponding to each layer, the charging group flag, and the scheduling sequence flag, used for subsequent mutual exclusion verification and local execution. Then, based on the layer list verification data, mutual exclusion verification is performed on each target layer to verify the transmitting coils and charging status of the upper and lower layers, and charging permission verification data is output. During mutual exclusion verification, the system queries whether the wireless charging transmitting coils of adjacent layers are turned off via the state bus and reads whether the charging status of the local control unit of the adjacent layer is OFF. In an optional implementation, the central controller also reads the detection values ​​of current sensors or magnetic field probes to determine whether the residual energy of adjacent layers has decayed below a safe threshold, such as below 5% of the rated value. When any adjacent layer is still charging or in the shutdown delay phase, the central controller does not grant permission to the output of this layer and requires this layer to remain in the rectification disabled state; when all adjacent layers meet the conditions for stopping charging and this layer appears in the charging layer list for this round, the central controller grants permission to the output of this layer and generates charging permission verification data containing the layer number and permission bit.

[0080] After the charging permission verification data meets the permission conditions, a rectification enable signal is sent to the local control unit of the corresponding layer. This causes the local control unit to restore the rectification path before starting the transmitting coil, thus obtaining the rectification path status data. The specific execution sequence is as follows: the central controller sends a rectification enable command to the local control unit via digital I / O or communication bus. The local control unit drives the rectifier stage switch on the UAV power module side to turn on. The rectifier stage switch can be a MOSFET or a relay, used to connect the receiving coil to the DC-DC converter and the battery. In one specific implementation, a low on-resistance N-MOSFET, such as an AO3400, is connected in series between the output of the receiving coil and the rectifier bridge. Its gate is controlled by the MCU of the local control unit. When GATE=LOW, the rectification path is disconnected, and the receiving coil is in an open-circuit floating state, so as to maintain rectification disabled during the unpermitted phase. After the above rectification enable is completed, the local control unit writes the conduction state of the rectifier switch, the gate control state, and the timestamp into the rectification path status data and sends it back to the central controller.

[0081] After the rectifier circuit status data indicates that the rectifier circuit has been restored, the local control unit performs a delayed stabilization process to obtain the energy transfer status data. The delay of the delayed stabilization process can be set to 10-50ms to wait for the switching devices to complete conduction and suppress transient fluctuations. After the delay ends, the local control unit starts the wireless charging drive circuit of the transmitting coil of this layer, turns on the high-frequency inverter to enter the energy transfer state, and writes the transmitting coil enable flag, the rectifier circuit conduction flag, the delay parameters, and the start time into the energy transfer status data. The local control unit reports the charging ready status to the central controller as part of the closed-loop confirmation.

[0082] During charging, the central controller and local control unit continuously monitor the status of adjacent layers and the rectified current. Upon detecting an anomaly, they execute a shutdown process to output anti-interference charging control data. Monitoring includes: whether the charging status of adjacent layers changes, the start / stop signals of adjacent layers on the shared bus, whether the rectified current at the receiving end is abnormal, and whether the current at the transmitting end exceeds a threshold. When a sudden charging start is detected in an adjacent layer, the local control unit immediately shuts down the transmitting coil of that layer according to a preset protection procedure and disconnects the rectifier switch, while simultaneously reporting a charging interruption due to adjacent layer interference. When an abnormal rectified current is detected, or an abnormal current occurs despite rectification not being enabled, the local control unit performs verification based on the open-circuit voltage at the receiving end, triggering a hardware emergency stop if necessary. The central controller summarizes the reported energy transfer status, abnormal events, shutdown actions, timestamps, and layer numbers to obtain anti-interference charging control data, which is used for subsequent polling and synchronization update steps.

[0083] In step S105, the anti-interference charging control data is periodically polled and updated synchronously: the status of each layer is polled at a fixed period, collecting the layer occupancy status, UAV identifier, battery state of charge percentage, charging demand flag, rectification status, and charging status of adjacent layers, generating a snapshot of the nest status; after the polling period ends, the charging demand of odd-numbered and even-numbered layer groups is statistically analyzed and a charging group switching decision is made in conjunction with the landing command issued by the ground station and the current charging demand; when a switch is required, the charging of the current group is stopped and the rectification path of the relevant layer is disconnected, the currently active charging group is updated after the safety delay ends, and then the layer charging in the target group that meets the mutual exclusion check condition is activated, thereby obtaining the charging polling synchronization data.

[0084] In one embodiment, step S105 includes:

[0085] The anti-interference charging control data is polled to collect layer occupancy data, battery state of charge data, and rectifier closure status data, and integrated to obtain the nest status snapshot data;

[0086] Receive the nest status snapshot data and parse the landing command to generate a landing request queue and associate the target layer with the occupancy status to obtain landing request parsing data;

[0087] The parity of the landing request parsing data is statistically analyzed to determine the charging demand of the odd and even groups, and the emergency return to base group to be assigned within a preset time is predicted, so as to output charging group switching decision data.

[0088] The charging group switching decision data is used to stop charging and turn off rectification. After a preset delay, the charging group is updated and the target group is activated to obtain charging polling synchronization data.

[0089] In this embodiment, when polling the anti-interference charging control data, a fixed-period polling method is used to collect the status of each layer within the nest. The polling period can be set to 1-2 seconds. During the polling process, the central controller communicates with the local control unit of each layer via CAN bus, RS485, or Wi-Fi Mesh, reading the layer occupancy data layer by layer to determine whether a drone is docked at the corresponding layer; synchronously reading the drone ID to associate the layer status with the drone; synchronously reading the battery state of charge (SOC) data (which can be provided by the drone BMS or the nest's local reading interface); synchronously reading the charging demand flag, for example, marking a drone that is not fully charged and is not a standby drone if its SOC is <80%; synchronously reading the rectifier closure status data to characterize whether the rectifier circuit is in a closed conducting state; and synchronously reading the charging status data of adjacent layers for subsequent interference risk assessment. After completing this round of polling, the central controller summarizes and integrates the above-mentioned collection results by layer number to obtain the nest status snapshot data. The nest status snapshot data includes at least the occupancy status of each layer, UAV ID, SOC (%), charging demand flag, rectification closure status, and charging status of adjacent layers, and serves as the input for this round of scheduling decision.

[0090] After obtaining the nest status snapshot data, the system receives landing commands from the ground station and performs parsing processing to generate a landing request queue and associate the target layer with its occupancy status, thus obtaining landing request parsing data. The ground station can send structured landing commands to the central controller in scenarios such as the end of a performance, emergency return, or backup aircraft scheduling. Upon receiving the commands, the central controller parses the UAV identifier, desired layer group, priority marker, and target layer information from the landing commands and writes the parsing results into the landing request queue. During the writing process, the central controller associates the target layer in the landing request queue with the layer occupancy data in the nest status snapshot data, recording whether the target layer is currently occupied and the candidate set of alternative layers, thereby obtaining the landing request parsing data. This allows subsequent charging group switching decisions to simultaneously consider both current charging needs and the upcoming landing requirements.

[0091] At the end of each polling cycle, the central controller statistically analyzes the landing request data to determine the charging needs of odd and even groups, and predicts the group to which emergency return drones will be assigned within a preset time, outputting charging group switching decision data. The charging demand flags in the nest status snapshot data are grouped and statistically analyzed to obtain the number of drones waiting to be charged in the odd group (N_odd) and the number of drones waiting to be charged in the even group (N_even). Simultaneously, the central controller scans the landing request queue to predict whether any high-priority emergency return drones will enter a certain group within the next 10-30 seconds, and outputs the predicted emergency return group assignment. The necessity of switching is assessed by combining the current active charging group status variable `current_charging_group` (which can take values ​​of ODD, EVEN, and IDLE): For example, if ODD is currently being charged and N_odd=0 and N_even>0, or if an emergency return to the home group is predicted to be EVEN, then the switching target is set to EVEN; conversely, if EVEN is currently being charged and N_even=0 and N_odd>0, or if an emergency return to the home group is predicted to be ODD, then the switching target is set to ODD; when neither ODD nor EVEN has a charging requirement, the switching target can be set to IDLE and all layers can remain uncharged. The central controller writes the switching target, triggering reason, set of layers participating in the switching, and execution sequence into the charging group switching decision data to initiate the safe switching execution phase.

[0092] When the charging group switching decision data indicates a switching is needed, the central controller performs a safe switching in the order of stopping charging, shutting down, delaying, updating, and activating to obtain charging polling synchronization data. The central controller sends a CHARGE_STOP command to each layer's local control unit in the currently active charging group, causing the corresponding layer to stop wireless charging. Upon receiving the CHARGE_STOP command, each layer's local control unit shuts down the power supply to the transmitting coil and puts the rectifier circuit into an open state, ensuring the receiver is electrically isolated. Next, the central controller initiates a safety delay, which can be set to 300–500ms, with a typical value of 500ms, to wait for the magnetic field to decay and residual energy in the circuit to release. During the delay, the central controller continuously reads the coil status and rectifier closure status reported by the local control units to ensure that the current group has completed stopping charging and shutting down. Subsequently, the central controller updates the current_charging_group to the target group for switching, for example, from ODD to EVEN or from EVEN to ODD, and begins activating the target group. The central controller issues charging permission commands to the local control units of each layer according to the layer order within the target group, for example, sending CHARGE_ENABLE(layer_id=3) via CAN message, and requiring the local control units to close the rectification path before starting the transmit coil. During the activation process, the central controller still uses the nest state snapshot data as a reference to perform adjacent layer verification for each target layer, ensuring that the layer above and below the target layer is in a non-charging state before allowing it to enter the transmit energy state. After the target group is activated, the central controller summarizes the nest state snapshot data obtained in this round of polling, the landing request queue status, the current_charging_group value before and after the switch, the list of activated layers, the delay parameters, and the update results of the rectification closure status of each layer into charging polling synchronization data, and uses it synchronously for status updates and scheduling decisions in subsequent polling cycles.

[0093] In addition to fixed-period polling, the central controller can also use an event-triggered approach to process charging group switching in real time, thereby improving the response speed to emergency scenarios. When a drone in the nest or returning to base reports a SOC < 10% and is marked as an emergency low-battery event, the central controller can interrupt the current polling wait, directly generate a switching target, and execute the aforementioned safe switching process. Similarly, when the ground station issues a rapid recharging command for all drones, the central controller can set the switching target to a high-efficiency group and prioritize activating multiple layers that meet the adjacent layer verification conditions, thereby increasing the number of parallel charging layers without causing interference to adjacent layers. Throughout the switching process, the central controller ensures that the ODD and EVEN groups are never simultaneously in a transmitting energy state, and this safety requirement is guaranteed through the coordinated use of software mutual exclusion locks and hardware interlocking relays, ensuring that the output charging polling synchronization data can stably support subsequent polling and scheduling updates.

[0094] In a specific implementation scenario, taking a nighttime light show involving 200 drones as an example, after the performance, the ground station performs statistical analysis based on the power status data transmitted by each drone, identifies 60 drones with power below 20% and marks them as emergency charging targets; the central controller reads the occupancy status of the five-layer vertically stacked drone nest and executes landing scheduling. When there are empty spaces in odd-numbered layers, the emergency charging targets are guided to land in sequence to the 1st, 3rd and 5th layers, while the remaining drones with power above 50% that are returning or fully charged standby drones on the ground are guided to the 2nd and 4th layers to complete their entry into the nest; After all drones are in position, the central controller initiates the odd-array charging mode, powering the transmitting coils of layers 1, 3, and 5 and putting them into power transmission mode, while keeping the transmitting coils of layers 2 and 4 off and the receiving rectification path disconnected. Once the odd-array drones are charged to 80%, the central controller performs a safety delay and switches to the even-array charging mode to replenish power to layers 2 and 4. Throughout the charging and switching process, the system synchronizes the layer occupancy, battery charge status, and rectification closure status via CAN bus or Wi-Fi, ensuring a consistent and conflict-free scheduling process.

[0095] As can be seen from the above scenarios, this solution employs logical grouping and staggered charging to prevent adjacent layers from entering wireless charging state simultaneously at any given time, thereby reducing the risk of electromagnetic crosstalk and maintaining a stable charging process. It maintains a high-density stacking layout without increasing physical isolation or shielding structures, improving the utilization rate of the drone nest space. It dynamically allocates landing layers based on power status and prioritizes emergency charging targets, improving the speed of power replenishment response. Simultaneously, it employs a dual protection mechanism of transmitter shutdown and receiver circuit disconnection to reduce the risk of false triggering and device malfunctions, enhancing system reliability and making it suitable for large-scale automated operation and maintenance scenarios of various vertically stacked drone nests.

[0096] Combination Figure 2 As shown, Figure 2 This is a schematic block diagram of a drone nest charging control device provided in an embodiment of the present invention. The drone nest charging control device 200 includes:

[0097] The data acquisition unit 201 is used to acquire nest layer configuration data and divide multiple layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data.

[0098] Data update unit 202 is used to collect battery power information of airborne drones and nested drones according to the hierarchical charging strategy data and update the drone status, and integrate them to obtain initial landing scheduling data.

[0099] Data scheduling unit 203 is used to check the layer occupancy status of the initial landing scheduling data. When the target layer is occupied, it calculates the comprehensive priority score of the returning UAV and performs scheduling processing according to the comprehensive priority score to obtain the final landing scheduling data.

[0100] Data verification unit 204 is used to generate a charging layer list for this round based on the final landing scheduling data and perform a mutual exclusion verification operation to obtain anti-interference charging control data;

[0101] The data synchronization unit 205 is used to periodically poll the anti-interference charging control data and perform data synchronization updates to obtain charging polling synchronization data.

[0102] In this embodiment, the data acquisition unit 201 acquires nest layer configuration data and divides multiple layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data; the data update unit 202 collects battery power information of airborne UAVs and UAVs in the nest according to the layered charging strategy data and updates the UAV status, integrating them to obtain initial landing scheduling data; the data scheduling unit 203 checks the layer occupancy status of the initial landing scheduling data, and when the target layer is occupied, calculates the comprehensive priority score of the returning UAV, performs scheduling processing according to the comprehensive priority score, and obtains final landing scheduling data; the data verification unit 204 generates a current-round charging layer list based on the final landing scheduling data and performs mutual exclusion verification operation to obtain anti-interference charging control data; the data synchronization unit 205 periodically polls the anti-interference charging control data and performs data synchronization update to obtain charging polling synchronization data.

[0103] In one embodiment, the data acquisition unit 201 is specifically used for:

[0104] The data parsing layer number of the nest layer is configured and grouped into odd and even arrays to obtain charging status identification data;

[0105] The charging status identifier data is compared with the layer start request, and the current charging group is determined according to the odd and even groups of the target layer to obtain the verification result data.

[0106] When the verification data triggers a switch, a stop charging command is sent and the coil power supply and rectification path are turned off. After a safety delay, the current charging group is updated to obtain the switching control data.

[0107] The hardware interlock is configured using the switching control data to connect interlock relays in series in the coil circuits of the odd and even arrays, so that only one path is turned on at any given time, thus obtaining the interlock configuration data;

[0108] Anomaly monitoring and processing are performed on the interlock configuration data to obtain hierarchical charging strategy data.

[0109] In one embodiment, the data update unit 202 is specifically used for:

[0110] Based on the hierarchical charging strategy, the identifier of the airborne drone is extracted to obtain the power collection target data.

[0111] The onboard battery management unit is invoked to sample the battery power based on the power collection object data to obtain battery power information;

[0112] The battery power information is encapsulated into messages according to the flight control cycle, and the reporting code rate is set to obtain battery status message data.

[0113] The battery status message data is sent to the ground station via a wireless data transmission module, and the ground station receives the data.

[0114] The data received by the ground station is analyzed for power level, and the UAV status is updated based on the power level analysis results to obtain the initial landing scheduling data.

[0115] In one embodiment, the data update unit 202 is further specifically used for:

[0116] The hierarchical charging strategy data is used for in-nest identification to determine the in-nest drone identifier and obtain in-nest data collection task data;

[0117] According to the in-nest data collection task call interface, the battery management system connects to the in-nest control unit via a contact interface or near-field communication to obtain the queried power data;

[0118] The queried power data is uploaded to the central controller and synchronized to the ground station to obtain the data reported in the nest;

[0119] Based on the data reported in the nest, the heartbeat energy level is sent to obtain the heartbeat energy level data;

[0120] The heart rate and charge data are written into a specific status table according to the weight of the timestamp source to obtain the initial landing scheduling data.

[0121] In one embodiment, the data scheduling unit 203 is specifically used for:

[0122] Based on the initial landing scheduling data, extract the battery percentage, mission type, and remaining return time, and assign them to the comprehensive priority score accordingly to obtain the evaluation model data;

[0123] The evaluation model data is used to read the nest layer status, and the available layers are searched by odd or even arrays and checked for occupancy. If there are no available layers, dynamic adjustment trigger data is output to obtain matching result data.

[0124] The matching result data is dynamically adjusted according to a preset adjustment strategy to obtain adjustment scheduling data;

[0125] Based on the adjusted scheduling data, the target layer is pre-occupied and globally locked before allocation. At the same time, a preset aging factor is introduced to increase the comprehensive priority score according to the waiting time, so as to obtain the final landing scheduling data.

[0126] In one embodiment, the data verification unit 204 is specifically used for:

[0127] The final landing scheduling data is parsed, and a charging layer list for this round is generated by grouping by odd and even numbers and by emergency priority, thus obtaining the layer list verification data.

[0128] Mutual exclusion verification is performed based on the layer list verification data to verify the transmitting coils and charging status of the upper and lower layers, and to obtain charging permission verification data.

[0129] A rectification enable signal is sent to the charging permission verification data to enable the local control unit to close the rectifier switch to connect the receiving coil and the battery, and the gate is turned on and off by low resistance field effect control to obtain the rectification path status data.

[0130] Based on the rectifier circuit state data, a time delay stabilization process is performed to obtain the energy transfer state data;

[0131] The system reports the energy transfer status data and monitors the adjacent layers and rectified current; if the adjacent layers are charging or the current is abnormal, the coil is turned off and the rectifier switch is disconnected to obtain anti-interference charging control data.

[0132] In one embodiment, the data synchronization unit 205 is specifically used for:

[0133] The anti-interference charging control data is polled to collect layer occupancy data, battery state of charge data, and rectifier closure status data, and integrated to obtain the nest status snapshot data;

[0134] Receive the nest status snapshot data and parse the landing command to generate a landing request queue and associate the target layer with the occupancy status to obtain landing request parsing data;

[0135] The parity of the landing request parsing data is statistically analyzed to determine the charging demand of the odd and even groups, and the emergency return to base group to be assigned within a preset time is predicted, so as to output charging group switching decision data.

[0136] The charging group switching decision data is used to stop charging and turn off rectification. After a preset delay, the charging group is updated and the target group is activated to obtain charging polling synchronization data.

[0137] Since the embodiments of the apparatus and the embodiments of the method correspond to each other, please refer to the description of the embodiments of the method for the embodiments of the apparatus, which will not be repeated here.

[0138] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed, can perform the steps provided in the above embodiments. The storage medium may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0139] This invention also provides a computer device, which may include a memory and a processor. The memory stores a computer program, and when the processor calls the computer program in the memory, it can implement the steps provided in the above embodiments. Of course, the computer device may also include various network interfaces, a power supply, a graphics card, etc., to utilize the graphics card's performance to operate the model, such as for inference and training.

[0140] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to in the method section. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

[0141] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A method for controlling the charging of a drone's nest, characterized in that, include: Obtain the nest layer configuration data, and divide multiple layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data; Based on the hierarchical charging strategy data, the battery power information of the airborne drones and the drones in the nest are collected and the drone status is updated. The data is then integrated to obtain the initial landing scheduling data. The initial landing scheduling data is checked for layer occupancy status. When the target layer is occupied, the comprehensive priority score of the returning UAV is calculated, and the scheduling is performed according to the comprehensive priority score to obtain the final landing scheduling data. Based on the final landing scheduling data, generate the current round charging layer list and perform a mutual exclusion check operation to obtain anti-interference charging control data; The anti-interference charging control data is periodically polled and updated synchronously to obtain charging polling synchronization data.

2. The UAV nest charging control method according to claim 1, characterized in that, The process of acquiring nest layer configuration data and dividing multiple layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data includes: The data parsing layer number of the nest layer is configured and grouped into odd and even arrays to obtain charging status identification data; The charging status identifier data is compared with the layer start request, and the current charging group is determined according to the odd and even groups of the target layer to obtain the verification result data. When the verification result data triggers a switch, a stop charging command is sent and the coil power supply and rectification path are turned off. After a safety delay, the current charging group is updated to obtain the switching control data. The hardware interlock is configured using the switching control data to connect interlock relays in series in the coil circuits of the odd and even arrays, so that only one path is turned on at any given time, thus obtaining the interlock configuration data; Anomaly monitoring and processing are performed on the interlock configuration data to obtain hierarchical charging strategy data.

3. The UAV nest charging control method according to claim 1, characterized in that, The process involves collecting battery power information for both airborne and in-nest drones based on the hierarchical charging strategy data, updating the drone status, and integrating this information to obtain initial landing scheduling data, including: Based on the hierarchical charging strategy, the identifier of the airborne drone is extracted to obtain the power collection target data. The onboard battery management unit is invoked to sample the battery power based on the power collection object data to obtain battery power information; The battery power information is encapsulated into messages according to the flight control cycle, and the reporting code rate is set to obtain battery status message data. The battery status message data is sent to the ground station via a wireless data transmission module, and the ground station receives the data. The data received by the ground station is analyzed for power level, and the UAV status is updated based on the power level analysis results to obtain the initial landing scheduling data.

4. The UAV nest charging control method according to claim 1, characterized in that, The step of collecting battery power information of both airborne and in-nest drones based on the hierarchical charging strategy data and updating the drone status, and integrating this information to obtain initial landing scheduling data, also includes: The hierarchical charging strategy data is used for in-nest identification to determine the in-nest drone identifier and obtain in-nest data collection task data; According to the in-nest data collection task call interface, the battery management system connects to the in-nest control unit via a contact interface or near-field communication to obtain the queried power data; The queried power data is uploaded to the central controller and synchronized to the ground station to obtain the data reported in the nest; Based on the data reported in the nest, the heartbeat energy level is sent to obtain the heartbeat energy level data; The heart rate and charge data are written into a specific status table according to the weight of the timestamp source to obtain the initial landing scheduling data.

5. The UAV nest charging control method according to claim 1, characterized in that, The initial landing scheduling data is checked for layer occupancy status. When the target layer is occupied, a comprehensive priority score is calculated for the returning UAV. Scheduling is then performed according to the comprehensive priority score to obtain the final landing scheduling data, including: Based on the initial landing scheduling data, extract the battery percentage, mission type, and remaining return time, and assign them to the comprehensive priority score accordingly to obtain the evaluation model data; The evaluation model data is used to read the nest layer status, and the available layers are searched by odd or even arrays and checked for occupancy. If there are no available layers, dynamic adjustment trigger data is output to obtain matching result data. The matching result data is dynamically adjusted according to a preset adjustment strategy to obtain adjustment scheduling data; Based on the adjusted scheduling data, the target layer is pre-occupied and globally locked before allocation. At the same time, a preset aging factor is introduced to increase the comprehensive priority score according to the waiting time, so as to obtain the final landing scheduling data.

6. The UAV nest charging control method according to claim 1, characterized in that, The process of generating a current-round charging layer list based on the final landing scheduling data and performing a mutual exclusion check operation to obtain anti-interference charging control data includes: The final landing scheduling data is parsed, and a charging layer list for this round is generated by grouping by odd and even numbers and by emergency priority, thus obtaining the layer list verification data. Mutual exclusion verification is performed based on the layer list verification data to verify the transmitting coils and charging status of the upper and lower layers, and to obtain charging permission verification data. A rectification enable signal is sent to the charging permission verification data to enable the local control unit to close the rectifier switch to connect the receiving coil and the battery, and the gate is turned on and off by low resistance field effect control to obtain the rectification path status data. Based on the rectifier circuit state data, a time delay stabilization process is performed to obtain the energy transfer state data; The system reports the energy transfer status data and monitors the adjacent layers and rectified current; if the adjacent layers are charging or the current is abnormal, the coil is turned off and the rectifier switch is disconnected to obtain anti-interference charging control data.

7. The UAV nest charging control method according to claim 1, characterized in that, The process of periodically polling and synchronizing the anti-interference charging control data to obtain charging polling synchronization data includes: The anti-interference charging control data is polled to collect layer occupancy data, battery state of charge data, and rectifier closure status data, and integrated to obtain the nest status snapshot data; Receive the nest status snapshot data and parse the landing command to generate a landing request queue and associate the target layer with the occupancy status to obtain landing request parsing data; The parity of the landing request parsing data is statistically analyzed to determine the charging demand of the odd and even groups, and the emergency return to base group to be assigned within a preset time is predicted, so as to output charging group switching decision data. The charging group switching decision data is used to stop charging and turn off rectification. After a preset delay, the charging group is updated and the target group is activated to obtain charging polling synchronization data.

8. A drone nest charging control device, characterized in that, include: The data acquisition unit is used to acquire the nest layer configuration data and divide the multiple layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data. The data update unit is used to collect battery power information of the airborne drone and the drone in the nest according to the hierarchical charging strategy data and update the drone status, and integrate them to obtain the initial landing scheduling data. The data scheduling unit is used to check the layer occupancy status of the initial landing scheduling data. When the target layer is occupied, it calculates the comprehensive priority score of the returning UAV and performs scheduling processing according to the comprehensive priority score to obtain the final landing scheduling data. The data verification unit is used to generate a charging layer list for this round based on the final landing scheduling data and perform a mutual exclusion verification operation to obtain anti-interference charging control data. The data synchronization unit is used to periodically poll the anti-interference charging control data and perform data synchronization updates to obtain charging polling synchronization data.

9. A computer device, characterized in that, The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the UAV nest charging control method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the UAV nest charging control method as described in any one of claims 1 to 7.

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