Unmanned aerial vehicle nest charging control method and device and related medium

Abstract

The invention discloses an unmanned aerial vehicle nest charging control method and device and a related medium, and the method comprises the steps: dividing a plurality of layers in nest layer configuration data into at least two mutually exclusive charging groups, respectively collecting the battery electric quantity information of an in-air unmanned aerial vehicle and an in-nest unmanned aerial vehicle, and updating the state of the unmanned aerial vehicle. Performing integration to obtain initial landing scheduling data; performing horizon occupancy state checking on the initial landing scheduling data to obtain final landing scheduling data; generating a charging layer list of the current round and executing mutual exclusion verification operation to obtain anti-interference charging control data; and performing periodic polling on the anti-interference charging control data to obtain charging polling synchronization data. According to the invention, the anti-interference charging control data is generated through the calculated final landing scheduling data, and periodic polling is performed on the anti-interference charging control data to obtain the charging polling synchronization data, so that coupling interference caused by simultaneous charging of adjacent layers in the nest of the unmanned aerial vehicle can be effectively avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicles, and in particular to a method and device for controlling charging of a nest for unmanned aerial vehicles, and related media. BACKGROUND

[0002] With the increasing scale of performances by clusters of unmanned aerial vehicles, vertically stacked nests are used for centralized parking and automatic charging of multiple unmanned aerial vehicles, and often use nest side wall transmitting coils and unmanned aerial vehicle side wall receiving coils to cooperate in wireless energy transmission. Due to the dense arrangement of multiple layers of unmanned aerial vehicles, electromagnetic coupling interference is easily generated in adjacent layers of coils during charging. When the upper and lower adjacent layers are simultaneously in a charging state, an alternating magnetic field induces an unintended electrical signal in the adjacent receiving coils and conducts to the rectification path, thereby causing abnormal voltage in the rectification path and the risk of device heating, resulting in unstable charging. The current methods of increasing the layer spacing or adding shielding materials are also difficult to solve the current problem of unstable charging. SUMMARY

[0003] Embodiments of the present application provide a method and device for controlling charging of a nest for unmanned aerial vehicles, and related media, to solve the technical problem of electromagnetic coupling interference caused by simultaneous wireless charging of adjacent layers of a stacked nest in the prior art, leading to abnormal rectification path and unstable charging.

[0004] In a first aspect, embodiments of the present application provide a method for controlling charging of a nest for unmanned aerial vehicles, comprising: obtaining nest layer configuration data and dividing a plurality of layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data; collecting battery capacity information of an empty unmanned aerial vehicle and an in-nest unmanned aerial vehicle according to the layered charging strategy data and updating the state of the unmanned aerial vehicles to obtain initial landing scheduling data; checking the layer occupation state of the initial landing scheduling data, calculating the comprehensive priority score of a return unmanned aerial vehicle when a target layer is occupied, performing scheduling processing according to the comprehensive priority score to obtain final landing scheduling data; generating a charging layer list for this round based on the final landing scheduling data and performing mutual exclusion verification to obtain anti-interference charging control data; periodically polling the anti-interference charging control data and performing data synchronization updating to obtain charging polling synchronization data.

[0005] In a second aspect, embodiments of the present application provide a device for controlling charging of a nest for unmanned aerial vehicles, comprising: a data acquisition unit configured to obtain nest layer configuration data and divide a plurality of layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data; a data updating unit configured to collect battery power information of the unmanned aerial vehicles in flight and the unmanned aerial vehicles in nest according to the hierarchical charging strategy data and update the state of the unmanned aerial vehicles, and integrate the initial landing scheduling data; a data scheduling unit configured to check the occupancy state of the layers in the initial landing scheduling data, calculate a comprehensive priority score of the unmanned aerial vehicles returning to the nest when the target layer is occupied, perform scheduling processing according to the comprehensive priority score, and obtain the final landing scheduling data; a data checking unit configured to generate a charging layer list of the current round based on the final landing scheduling data, perform mutual exclusion checking operation, and obtain the anti-interference charging control data; a data synchronization unit configured to periodically poll the anti-interference charging control data, perform data synchronization update, and obtain the charging polling synchronization data.

[0006] In a third aspect, an embodiment of the present application provides a computer device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the unmanned aerial vehicle nest charging control method of the first aspect when executing the computer program.

[0007] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executable on a processor to implement the unmanned aerial vehicle nest charging control method of the first aspect.

[0008] The embodiment of the present application provides an unmanned aerial vehicle nest charging control method, which comprises obtaining nest layer configuration data, dividing a plurality of layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain hierarchical charging strategy data, collecting battery power information of the unmanned aerial vehicles in flight and the unmanned aerial vehicles in nest according to the hierarchical charging strategy data and updating the state of the unmanned aerial vehicles, integrating the initial landing scheduling data, checking the occupancy state of the layers in the initial landing scheduling data, calculating a comprehensive priority score of the unmanned aerial vehicles returning to the nest when the target layer is occupied, performing scheduling processing according to the comprehensive priority score, obtaining the final landing scheduling data, generating a charging layer list of the current round based on the final landing scheduling data, performing mutual exclusion checking operation, and obtaining the anti-interference charging control data, periodically polling the anti-interference charging control data, performing data synchronization update, and obtaining the charging polling synchronization data. The anti-interference charging control data is generated based on the final landing scheduling data obtained by calculation, and the anti-interference charging control data is periodically polled to obtain the charging polling synchronization data, so that the coupling interference caused by simultaneous charging of adjacent layers in the unmanned aerial vehicle nest can be effectively avoided.

[0009] The unmanned aerial vehicle nest charging control device, the computer device and the storage medium also have the beneficial effects described above. BRIEF DESCRIPTION OF DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0011] Figure 1 A flowchart of an unmanned aerial vehicle nest charging control method provided by the embodiment of the present application is shown. Figure 2 A schematic block diagram of an unmanned aerial vehicle nest charging control device provided by the embodiment of the present application is shown. DETAILED DESCRIPTION

[0012] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0013] It should be understood that when used in the specification and the appended claims, the terms "comprise" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0014] It should also be understood that the terms used in the present application specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, unless otherwise clearly indicated by the context, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0015] It should be further understood that the term "and / or" used in the present application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations thereof, and includes these combinations.

[0016] Please see the following Figure 1 , Figure 1 A flowchart of an unmanned aerial vehicle nest charging control method provided by the embodiment of the present application is shown, which specifically includes steps S101-S105.

[0017] S101, acquire nest layer configuration data, and divide a plurality of layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data; S102, respectively collect battery power information of the unmanned aerial vehicle and the nest unmanned aerial vehicle according to the layered charging strategy data, and update the unmanned aerial vehicle state to obtain initial landing scheduling data; S103, perform layer occupation state checking on the initial landing scheduling data, calculate a comprehensive priority score of a return unmanned aerial vehicle when a target layer is occupied, perform scheduling processing according to the comprehensive priority score to obtain final landing scheduling data; S104, generate a charging layer list based on the final landing scheduling data and perform mutual exclusion checking to obtain anti-interference charging control data; S105, periodically poll the anti-interference charging control data, and perform data synchronization update to obtain charging polling synchronization data.

[0018] In step S101, the nest layer configuration data is acquired, the layer numbers and available states of each layer are parsed, and a plurality of layers are divided into at least two mutually exclusive charging groups, for example, grouped and managed according to odd layers and even layers; only one group of charging is activated at any time, and when the group is switched, the stop charging and shutdown processing of the previous group are completed first, and then the current active charging group is updated after the safety delay ends, to obtain layered charging strategy data.

[0019] In an embodiment, the step S101 comprises: The layer numbers in the nest layer configuration data are parsed to group the odd layers and the even layers to obtain charging state identification data; The charging state identification data is compared with a layer start request to determine the current charging group according to the target layer odd-even group to obtain checking result data; When the checking data triggers switching, a stop charging instruction is sent, and the coil power supply and rectification path are turned off, the current charging group is updated after a safety delay, and switching control data is obtained; The switching control data is used to configure hardware interlocking, coil loop series interlocking relays in the odd group and the even group are used to make only one path conductive at any time, and mutual locking configuration data is obtained; Abnormal monitoring processing is performed on the mutual locking configuration data to obtain layered charging strategy data.

[0020] In the embodiment, machine nest layer configuration data can be acquired in advance, and the machine nest layer configuration data at least includes total number of layers, layer number of each layer, and available state of each layer, and the like. The embodiment takes a five-layer vertically stacked machine nest as an example, analyzes the layer number of the machine nest layer configuration data, and divides a plurality of layers into at least two mutually exclusive charging groups according to the parity of the layer number, wherein the odd group includes the first layer, the third layer, and the fifth layer, and the even group includes the second layer and the fourth layer. Only one charging group is allowed to be in a wireless charging open state at any time, and the upper layer and the lower layer of the layer being charged are in a non-charging state, so as to avoid simultaneous charging of adjacent layers under the condition of multi-layer dense arrangement. After grouping the layer number, charging state identification data is maintained to represent the state of the currently activated charging group. Specifically, a global variable current_charging_group is set to indicate the charging group in the active state, and the value of the global variable current_charging_group includes ODD, EVEN, and IDLE. ODD represents that the odd group is currently activated, EVEN represents that the even group is currently activated, and IDLE represents that no layer is in the charging state. The current_charging_group has an exclusive feature, and is only allowed to be in one valid value at any time. The complete shutdown of the previous charging group is completed before the charging group switching is performed, so that the charging state identification data is consistent with the actual charging state of the machine nest.

[0021] When the layer start request is received, the charging state identification data is compared with the layer start request, the current charging group is determined according to the parity group of the target layer, and the verification result data is output. When the scheduling module requests to start wireless charging of the third layer, it is determined that the third layer belongs to the odd group, and the current_charging_group is read. If the current_charging_group is EVEN, the verification result data of refusing to start immediately is output, and the layer start request is put into the waiting queue or the charging group switching is triggered. If the current_charging_group is ODD or IDLE, the verification result data of allowing to start charging of the odd group is output. Correspondingly, when the target layer belongs to the even group, the verification result data of allowing to start is only output when the current_charging_group is not ODD, so as to ensure that the odd group and the even group are not started simultaneously at the logical level.

[0022] When the check result data triggers the charging group switching, a switching control flow is executed and switching control data is generated. That is, a stop charging instruction is sent to all levels of the current active charging group, and each local control unit closes the transmitting coil power supply and disconnects the UAV rectification path after receiving the stop charging instruction, so that the corresponding level enters a non-charging state; then a safety delay is started, and the typical value of the safety delay is 300-500 ms, which is used to wait for the decay of the magnetic field and the release of residual energy in the circuit; after the safety delay ends, the value of current_charging_group is updated, for example, from ODD to EVEN, and a start instruction is sent to the levels of the newly activated charging group, so that the corresponding levels enter a chargeable state. The safety delay can be configured, and it can also be detected by a current sensor or a magnetic field sensor to detect the decay state, and then the update of current_charging_group and the activation of the new group are executed after the detection result meets the zeroing condition, so as to improve the safety and consistency of the switching process.

[0023] After generating the switching control data, the switching control data is further used to configure hardware interlocking and obtain interlocking configuration data, so that the odd group and the even group are mutually exclusive at the hardware execution level. A hardware interlocking relay is provided in the power supply driving circuit, so that the transmitting coil power supply loop of the odd group and the transmitting coil power supply loop of the even group share one double-pole relay, which can only connect one power supply loop in physical structure, so that only one power supply loop is connected at any time. When the switching control data is output, the interlocking relay is driven to switch the contact position, so that the coil loop corresponding to current_charging_group obtains the power supply condition, and the coil loop of the other group is in a disconnected state, thereby providing mutual exclusion guarantee at the hardware level in addition to software control. After completing the interlocking configuration, the interlocking configuration data is monitored for abnormalities, and layered charging strategy data is output accordingly. The current sensor continuously monitors the transmitting coil current output state of the odd group and the even group; when it is monitored that the transmitting coils of the two groups exist current output at the same time, emergency power-off is triggered, and fault logs are reported, and all UAVs are placed in a charging disabled state; the charging disabled state is maintained until the manual reset or self-check is passed. Through the cooperative processing of the above grouping, comparison and checking, switching control, hardware interlocking and abnormality monitoring, layered charging strategy data is output, which can be called in subsequent steps.

[0024] In step S102, the ground station collects battery capacity information of the aerial drone and the nest drone respectively under the management framework of the hierarchical charging strategy data, and updates the unmanned aerial vehicle state according to a unified standard; wherein the aerial drone samples voltage, current, temperature, residual capacity and battery state of charge percentage by the on-board battery management unit, and periodically reports to the ground station by the flight control; the nest drone reads the battery state of charge percentage by the local interface or the short distance communication mode, or sends the simplified heartbeat information by the unmanned aerial vehicle maintenance low power consumption report mode; the ground station writes the above multi-source data into the global unmanned aerial vehicle state table and updates the record, so as to obtain the initial landing scheduling data.

[0025] In an embodiment, the step S102 comprises: extracting the aerial drone identifier based on the hierarchical charging strategy data to obtain the power collection object data; calling the on-board battery management unit to sample the power according to the power collection object data to obtain the battery capacity information; packet encapsulating the battery capacity information according to the flight control period, and setting the report code rate to obtain the battery state packet data; sending the battery state packet data to the ground station through the wireless data transmission module to obtain the ground station receiving data; performing power analysis on the ground station receiving data, and updating the unmanned aerial vehicle state based on the power analysis result to obtain the initial landing scheduling data.

[0026] In the embodiment, based on the obtained layered charging strategy data, the unmanned aerial vehicles inside and outside the nest are subjected to state screening, the unmanned aerial vehicles in the air in flight state and needing to continuously report battery state are extracted as in-air unmanned aerial vehicle identifiers, and collection task parameters are allocated for each in-air unmanned aerial vehicle identifier, the collection task parameters at least including unmanned aerial vehicle number, sampling period, reporting code rate and message type identifier, thereby obtaining power collection object data. The power collection object data can be used as input of ground station polling scheduling and flight control reporting configuration, so that each in-air unmanned aerial vehicle outputs battery power information under the same collection caliber. The power collection object data is used to call the on-board battery management unit BMS to perform power sampling. Specifically, each in-air unmanned aerial vehicle is configured with an intelligent battery, the intelligent battery is integrated with a battery management system BMS, the BMS reads battery monomer cell voltage, total voltage and current, temperature, residual capacity mAh and state of charge SOC State of Charge according to the sampling period, the state of charge SOC is in percentage %. The BMS encapsulates the above sampling results as battery power information, and attaches sampling time stamp and unmanned aerial vehicle number, so as to perform consistency check and state update on the ground station side subsequently. After obtaining the battery power information, the unmanned aerial vehicle flight control encapsulates the battery power information into a message according to the flight control period, and sets the reporting code rate to obtain battery state message data. The reporting code rate can be set to 1-5 Hz, the flight control packs the battery power information into a BATTERY_STATUS message or a custom message of MAVLink protocol, the battery state message data includes unmanned aerial vehicle number, time stamp, SOC, total voltage, current, temperature and residual capacity mAh, and can be periodically output according to the reporting code rate, so as to meet the real-time maintenance requirement of the ground station on the in-air unmanned aerial vehicle battery state.

[0027] Further, the battery status message data is sent to the ground station through the wireless data transmission module to obtain ground station received data. The wireless data transmission module can use a 900 MHz or 2.4 GHz wireless data transmission module, or a 4G / 5G communication module; during the sending process, the flight control sends the battery status message data frame by frame according to the reporting code rate, the ground station buffers and reorganizes the message at the receiving end, and collects the corresponding ground station received data according to the unmanned aerial vehicle number, so as to continuously update the battery status record of the same unmanned aerial vehicle dimension. Finally, the ground station analyzes the power of the ground station received data, and updates the unmanned aerial vehicle state based on the power analysis result to obtain initial landing scheduling data. The ground station analyzes the BATTERY_STATUS or custom message protocol, extracts the SOC, total voltage, current, temperature, remaining capacity mAh, and timestamp, and writes the analysis result into the corresponding record in the unmanned aerial vehicle state table; the ground station updates the unmanned aerial vehicle state to the current power state according to the latest timestamp, and outputs the initial landing scheduling data for scheduling, which at least includes the empty unmanned aerial vehicle identifier, the latest SOC percentage, the power sampling timestamp, and the task label associated with the hierarchical charging strategy data, for subsequent steps of unified processing of return landing and layer allocation.

[0028] In an embodiment, the step S102 further comprises: The hierarchical charging strategy data is identified in the nest to determine the in-nest unmanned aerial vehicle identifier, and the in-nest collection task data is obtained; According to the in-nest collection task data, an interface is called to enable the battery management system to connect to the nest control unit through a contact interface or near field communication, and the query power data is obtained; The query power data is uploaded to the central controller and synchronized to the ground station to obtain in-nest reporting data; According to the in-nest reporting data, a heartbeat power is sent to obtain heartbeat power data; The heartbeat power data is written into a specific state table according to the timestamp source weight to obtain initial landing scheduling data.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] In one embodiment, step S103 includes: 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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 for subsequent optimization of the layer allocation strategy and parameter calibration. The final output includes the final landing scheduling data containing the target layer result and the lock status.

[0038] 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.

[0039] In one embodiment, step S104 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.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] In one embodiment, step S105 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 odd and even group charging requirements of the landing request parsing data are statistically analyzed, 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.

[0046] 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.

[0047] 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.

[0048] 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.

[0049] 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.

[0050] 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.

[0051] 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.

[0052] 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.

[0053] 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: 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. 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. 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. 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; 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.

[0054] 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.

[0055] In one embodiment, the data acquisition unit 201 is specifically used for: 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 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.

[0056] In one embodiment, the data update unit 202 is specifically used for: 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.

[0057] In one embodiment, the data update unit 202 is further specifically used for: 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.

[0058] In one embodiment, the data scheduling unit 203 is specifically used for: 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.

[0059] In one embodiment, the data verification unit 204 is specifically used for: 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.

[0060] In one embodiment, the data synchronization unit 205 is specifically used for: 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 odd and even group charging requirements of the landing request parsing data are statistically analyzed, 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.

[0061] 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.

[0062] 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.

[0063] 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.

[0064] 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.

[0065] 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, The method comprises the following steps: acquiring nest layer configuration data, and dividing a plurality of layers in the nest layer configuration data into at least two mutually exclusive charging groups to obtain layered charging strategy data; collecting battery capacity information of the unmanned aerial vehicle in flight and the unmanned aerial vehicle in nest according to the layered charging strategy data, updating the state of the unmanned aerial vehicle, and integrating to obtain initial landing scheduling data; checking the layer occupation state of the initial landing scheduling data, calculating the comprehensive priority score of the return unmanned aerial vehicle when the target layer is occupied, performing scheduling processing according to the comprehensive priority score, and obtaining final landing scheduling data; generating a charging layer list based on the final landing scheduling data, performing mutual exclusion verification, and obtaining anti-interference charging control data; periodically polling the anti-interference charging control data, and updating the data synchronously to obtain charging polling synchronization data. 2.The drone nest charging control method of claim 1, wherein, The method comprises the following steps: analyzing the layer number of the nest layer configuration data to group the odd-numbered groups and the even-numbered groups, and obtaining charging state identification data; comparing the charging state identification data with the layer start request, determining the current charging group according to the target layer odd-even group, and obtaining verification result data; when the verification data triggers switching, sending a stop charging instruction and turning off the coil power supply and rectification path, updating the current charging group after a safety delay, and obtaining switching control data; configuring hardware interlocking by using the switching control data to connect the coil loop of the odd-numbered group and the even-numbered group in series through an interlocking relay, so that only one path is turned on at any moment, and obtaining interlocking configuration data; performing abnormal monitoring processing on the interlocking configuration data to obtain layered charging strategy data. 3.The drone nest charging control method of claim 1, wherein, The method comprises the following steps: extracting the unmanned aerial vehicle in flight based on the layered charging strategy data to obtain power collection object data; calling the on-board battery management unit to sample the battery capacity according to the power collection object data to obtain battery capacity information; packet encapsulating the battery capacity information according to the flight control period, setting the reporting code rate, and obtaining battery state packet data; sending the battery state packet data to the ground station through the wireless data transmission module to obtain ground station receiving data; performing power analysis on the ground station receiving data, and updating the state of the unmanned aerial vehicle based on the power analysis result to obtain initial landing scheduling data. 4.The drone nest charging control method of claim 1, wherein, The method further comprises the following steps: performing in-nest identification on the layered charging strategy data to determine the identification of the unmanned aerial vehicle in nest, and obtaining in-nest collection task data; calling the interface according to the in-nest collection task data, so that the battery management system connects the nest control unit through the contact interface or near field communication to obtain query power data; Upload the query power data to the central controller and synchronize to the ground station to obtain the nest reporting data; According to the nest reporting data, the heartbeat power is sent, and the heartbeat power data is obtained; The heartbeat power data is written into a specific state table according to the timestamp source weight, and the initial landing scheduling data is obtained. 5.The drone nest charging control method of claim 1, wherein, The initial landing scheduling data is checked for layer occupation state, and when the target layer is occupied, the comprehensive priority score of the return unmanned aerial vehicle is calculated, and the scheduling processing is performed according to the comprehensive priority score, and the final landing scheduling data is obtained, including: According to the initial landing scheduling data, the power percentage, task type, and return remaining time are extracted respectively, and the comprehensive priority score is weighted correspondingly, and the evaluation model data is obtained; Using the evaluation model data, the nest layer state is read, and the idle layer is searched according to the odd or even group and checked for occupation. If there is no idle, the dynamic adjustment trigger data is output, and the matching result data is obtained; The matching result data is dynamically adjusted according to the preset adjustment strategy, and the adjustment scheduling data is obtained. Based on the adjustment scheduling data, the target layer is preoccupied and globally locked before distribution, and a preset aging factor is introduced to improve the comprehensive priority score according to the waiting time, and the final landing scheduling data is obtained. 6.The drone nest charging control method of claim 1, wherein, The final landing scheduling data is used to generate the current charging layer list and perform mutual exclusion verification operation, and the anti-interference charging control data is obtained, including: The final landing scheduling data is parsed, and the current charging layer list is generated according to the odd-even grouping and emergency priority, and the layer list verification data is obtained; According to the layer list verification data, mutual exclusion verification is performed to verify the transmission coil and charging state of the previous layer and the next layer, and the charging permission verification data is obtained; The charging permission verification data is used to issue a rectification enable signal, so that the local control unit closes the rectification switch to connect the receiving coil and the battery, and controls the gate to be disconnected with a low resistance field effect transistor, and the rectification path state data is obtained; According to the rectification path state data, delay stabilization processing is performed, and the energy transmission state data is obtained; The energy transmission state data is reported and the adjacent layer and rectification current are monitored. If the adjacent layer is charged or the current is abnormal, the coil is turned off and the rectification switch is disconnected, and the anti-interference charging control data is obtained. 7.The drone nest charging control method of claim 1, wherein, The anti-interference charging control data is periodically polled, and data synchronization update is performed, and the charging polling synchronization data is obtained, including: The anti-interference charging control data is polled to collect layer occupation data, battery state of charge data, and rectification closed state data, and the machine nest state snapshot data is obtained by integration; The machine nest state snapshot data is received and the landing instruction is parsed to generate a landing request queue and associate the target layer and the occupation state, and the landing request analysis data is obtained; The odd-even group charging demand of the landing request analysis data is counted, and the emergency return attribution group within a preset time is predicted to output the charging group switching decision data; The charging group switching decision data is stopped and the rectification is turned off, and after a delay of a preset time, the charging group is updated and the target group is activated, and the charging polling synchronization data is obtained.

8. A drone nest charging control device, characterized in that, including: The data acquisition unit is configured to acquire nest layer configuration data, divide a plurality of layers in the nest layer configuration data into at least two mutually exclusive charging groups, and obtain layered charging strategy data. The data updating unit is configured to collect battery power information of the unmanned aerial vehicle and the nest unmanned aerial vehicle according to the layered charging strategy data, update the state of the unmanned aerial vehicle, and integrate to obtain initial landing scheduling data. The data scheduling unit is configured to check a layer occupation state of the initial landing scheduling data, calculate a comprehensive priority score of a return unmanned aerial vehicle when a target layer is occupied, perform scheduling processing according to the comprehensive priority score, and obtain final landing scheduling data. The data verification unit is configured to generate a charging layer list of this round based on the final landing scheduling data, perform a mutual exclusion verification operation, and obtain anti-interference charging control data. The data synchronization unit is configured to periodically poll the anti-interference charging control data, perform data synchronization updating, and obtain charging polling synchronization data.

9. A computer device, comprising: The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the unmanned aerial vehicle nest charging control method according to 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, and the computer program is executed by the processor to implement the unmanned aerial vehicle nest charging control method according to any one of claims 1 to 7.

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