A multi-model high-isomerism large unmanned aerial vehicle cluster command and control system and method

Abstract

The application belongs to the technical field of unmanned aerial vehicle control, and discloses a multi-model high-heterogeneous large unmanned aerial vehicle cluster command control system and method, the multi-model high-heterogeneous large unmanned aerial vehicle cluster command control system comprises: an unmanned aerial vehicle cluster control authority management module, which is used for completing unmanned aerial vehicle cluster control authority management; a plurality of aircraft pilot systems, which are respectively used for completing general flight control of each model unmanned aerial vehicle; a plurality of aircraft maintenance officer systems, which are respectively used for completing preset model unmanned aerial vehicle special working state monitoring, and are responsible for maintenance disposal when preset emergency situations occur. The application realizes general flight operation and reduces the ability requirement of flight operation personnel.

Description

Technical Field

[0001] This application belongs to the field of unmanned aerial vehicle (UAV) control technology, and in particular relates to a command and control system and method for a large-scale UAV swarm with multiple models and highly heterogeneous structures. Background Technology

[0002] As a high-end intelligent and complex aircraft, the command and control of a single large UAV is generally completed by a flight operator, a payload operator and a link operator located at the ground control station. The flight operator is responsible for controlling the flight of the UAV, monitoring the working status of the UAV and handling various emergencies. The payload operator is responsible for controlling the various payloads carried by the UAV. The link operator is responsible for controlling the wireless communication between the UAV and the ground control station.

[0003] Different types of drones generally differ significantly in terms of mission, functional indicators, system composition, and value. The design concepts and approaches of different design teams also differ significantly, resulting in the ground control stations of various drone models generally being dedicated.

[0004] With the rapid development of the large-scale drone industry in recent years, the number and models of drones purchased by the same user are growing rapidly. It has become the norm for multiple drones of different types to perform tasks in coordination. Based on considerations such as reducing procurement costs, reducing the skill and quantity requirements of operators, and facilitating support, the universal command and control of different drone models, as well as the swarm control of multiple drones, have become urgent needs.

[0005] There are generally two common practices for command and control: one is to design different UAV models based on a single standard interface, such as NATO's STANAG 4586; the other is to use the same command and control hardware for different UAV models, loading different software to achieve a single command and control system to control different UAVs. Both approaches are effective in reducing procurement costs and meeting support requirements, but they require operators to be proficient in operating different UAV models. Due to the powerful functions, high economic value, high mission value, high safety requirements, and complex systems of large UAVs, and the limitations of single-unit intelligent practicality, the operation of large UAVs is still relatively complex. Therefore, these two methods significantly increase the skill requirements for operators. Furthermore, because the system structures of different UAV models vary greatly, it is difficult to standardize various emergency response procedures, which can easily lead to confusion, misoperation, or delays.

[0006] In addition, with the rapid growth in the number of drones, the demand for operators will increase year-on-year for a considerable period of time due to the limitations of drone swarm intelligence and single-machine intelligence. To obtain a sufficient number of operators, it is necessary to reduce the capability requirements.

[0007] Therefore, there is an urgent need for a general-purpose UAV swarm command and control system and method that can achieve command and control of different models and reduce the overall skill requirements of operators through swarm control. Summary of the Invention

[0008] The purpose of this application is to overcome the problems of the prior art by disclosing a command and control system and method for a large-scale UAV swarm with multiple models and high heterogeneity. This application achieves universality in flight operations and reduces the skill requirements of flight operators.

[0009] On the one hand, the objective of this application is achieved through the following technical solution: A command and control system for a large-scale, multi-model, highly heterogeneous unmanned aerial vehicle (UAV) swarm, comprising: The drone swarm control permission management module is used to manage the control permissions of drone swarms. Several aircraft pilot systems are used to perform common flight control for various types of UAVs; Several aircraft maintenance systems are used to monitor the working status of pre-defined UAV models and to handle maintenance and emergency situations.

[0010] On the other hand, this application also discloses: A command and control method for a large, multi-model, highly heterogeneous UAV swarm, employing the aforementioned command and control system, wherein the method includes: Flight operators are divided into two categories: aircraft pilots and aircraft maintenance personnel. Aircraft pilots use the aircraft pilot system to perform general flight control of the UAV and coordinate operations with collaborating partners. Aircraft maintenance personnel monitor the dedicated operating status of the drones using the aircraft maintenance personnel system and are responsible for handling pre-set emergency situations.

[0011] According to a preferred embodiment, each drone performing a complex task is equipped with an aircraft pilot responsible for the flight operation of the drone in normal conditions. The pilot views the aircraft list through the configured pilot system, and after selecting a drone, sends a takeover request message to the drone cluster control authority management module through the pilot system to request control over the corresponding drone. The drone swarm control permission management module assigns permissions to the pilot of the drone based on the predefined permission allocation results and the working status of the corresponding drone. The allocation results are sent to the aircraft maintenance system of the corresponding model through allocation messages. The aircraft maintenance system registers and displays the permissions for centralized monitoring by the aircraft maintenance personnel.

[0012] According to a preferred embodiment, if the drone cluster control permission management module does not find the pre-assigned permission result of the corresponding aircraft pilot, it forwards the request message to the aircraft maintenance system of the same model, and the aircraft maintenance personnel manually confirm the takeover request.

[0013] According to a preferred embodiment, the pilot completes the automated control of the UAV based on the pilot system, and the pilot system monitors the flight status and the surrounding environment, and performs flight interventions according to mission requirements, including route and waypoint switching.

[0014] According to a preferred embodiment, after the aircraft pilot completes the mission, he operates the UAV to the designated location and sets it to automatic flight. He then sends a message to the UAV swarm control authority management module to return control authority through the aircraft pilot system. The UAV swarm control authority management module forwards the message to the maintenance personnel system of the corresponding aircraft model, where the maintenance personnel confirm the recovery authority.

[0015] According to a preferred embodiment, after the aircraft maintenance operator confirms that the drone's access has been reclaimed, control is transferred to the take-off and landing station, which is then responsible for the drone's landing and recovery.

[0016] According to a preferred embodiment, the aircraft maintenance system monitors the aircraft status based on the UAV's onboard management computer or command and control center, issues alarm prompts, and sends the alarm results to the aircraft pilot system for display.

[0017] According to a preferred embodiment, when the drone issues a preset level alarm, or when other situations occur that the pilot deems abnormal, The aircraft pilot sends an assistance request message automatically or manually to the maintenance system of the aircraft model through the aircraft pilot system. The aircraft maintenance personnel switch the maintenance system to the corresponding UAV maintenance screen, send a command to the UAV cluster control authority management module to revoke control authority of the UAV, and then take action.

[0018] According to a preferred embodiment, when an aircraft maintenance operator discovers that a drone has encountered a situation requiring immediate action, the aircraft maintenance operator system will proactively reclaim control authority.

[0019] The aforementioned main solution and its various further alternative solutions can be freely combined to form multiple solutions, all of which are solutions that can be adopted and are claimed in this application. Those skilled in the art, after understanding the solution of this application, will realize that there are many combinations based on the prior art and common general knowledge, all of which are technical solutions to be protected in this application, and will not be exhaustively listed here.

[0020] The beneficial effects of this application are: 1. When controlling drones in a swarm, the overall skill requirements for flight operators are significantly reduced.

[0021] Limited by the practical application bottlenecks of single-machine intelligence and swarm intelligence, each UAV still generally requires a flight operator when performing relatively complex tasks. Due to the complex structure of large UAV systems, the requirements for flight operators remain relatively high. This invention separates the use and maintenance of UAVs. The user (referred to as the pilot) only needs to focus on operation and does not need to be concerned with the specific system structure and emergency response strategies of the UAV, thus significantly reducing the skill requirements. The maintainer (referred to as the maintenance operator) is responsible for ensuring the normal operation of the aircraft and handling emergencies. Since the number of aircraft experiencing emergencies is small for mature aircraft, only a small number of each type of UAV needs to be configured in the swarm. The maintenance operator needs to be thoroughly familiar with the specific system structure and emergency response strategies of the UAVs, and the task content and requirements are consistent with those of the original flight operator.

[0022] Assuming the number of drones is N, and the capability requirement coefficient for a single drone pilot is α. 飞机驾驶员 Since each drone is equipped with one pilot, the number of drones is also N. Additionally, assume the capability requirement coefficient for a single drone maintenance worker is α. 飞机维护员 If the quantity configuration is L, then the total cluster operation capacity requirement E of this invention is... 本发明 =N*α 飞机驾驶员 +L*α 飞机维护员 Original cluster operation capacity requirement E 原 =N*α 原飞行操作员 , where α 原飞行操作员 =α 飞机维护员 Then E 本发明 / E 原 = (N*α) 飞机驾驶员 +L*α 飞机维护员 ) / N*α 原飞行操作员 = (N*α) 飞机驾驶员 +L*α 原飞机操作员 ) / N*α 原飞行操作员 =α 飞机驾驶员 / α 原飞机操作员 + L / N, where α 飞机驾驶员 / α 原飞机操作员 It is a fixed value, estimated to be no greater than 0.3 based on the aforementioned capability allocation and practical operational experience. The physical meaning of L / N is the ratio of flight maintenance personnel to drones, which is related to the aircraft's maturity. Assuming that one in five drones requires emergency handling during a mission, i.e., L / N = 0.2, then E... 本发明 / E 原 ≤0.5. It can be seen that this invention significantly reduces the overall skill requirements for flight operators when controlling drones in a swarm.

[0023] 2. It enables universal command and control for different types of UAVs, which not only does not increase the skill requirements for flight operators, but also significantly reduces the overall skill requirements for flight operators.

[0024] The aircraft pilot of this invention does not need to be concerned with the specific system configuration and emergency response strategy of the UAV. As can be seen from the functional allocation of this application, it can be responsible for the use of different models of UAVs. The aircraft maintenance personnel are assigned a small number of UAVs according to the UAV model and are only responsible for their respective UAV models.

[0025] Assume there are M types of drones, and for simplicity, assume there are N drones of each type, with a single pilot's skill requirement for each type of drone being α. 飞机驾驶员 Considering the differences in performance and dynamic response among various types of drones, and assuming a 20% increase in capability requirement for each additional model, with one pilot assigned to each drone, the number of pilots in swarm control is M*N. Additionally, assume a capability requirement coefficient of α for each individual drone maintenance operator. 飞机维护员 For simplicity, it is assumed that the capability requirement coefficient for each type of UAV flight maintenance personnel is the same, the number of maintenance personnel for each type of UAV is configured as L, and the total number is M*L. Then, the total cluster operation capability requirement E of this invention is... 本发明 =M*N*(α 飞机驾驶员 +α 飞机驾驶员 *20%*(M-1))+M*L*α 飞机维护员 Original cluster operation capacity requirement E 原 =M*N*(α 原飞行操作员 *M), where α 原飞行操作员 =α 飞机维护员 Then E 本发明 / E 原 =(M*N*(α 飞机驾驶员 +α 飞机驾驶员 *20%*(M-1))+M*L*α 飞机维护员 ) / (M*N*(α) 原飞行操作员 *M)) =α 飞机驾驶员 / (α 原飞机操作员 *M)+0.2*(α) 飞机驾驶员 / α 原飞机操作员 )*((M-1) / M)+ L / (M*N), assuming as mentioned above, take α 飞机驾驶员 / α 原飞机操作员 If the value is not greater than 0.3, and L / N is 0.2, then E 本发明 / E 原≤ 0.5 / M + 0.06*(M-1) / M ≤ 0.5 / M + 0.06. As can be seen from this formula, since M≥2, the overall reduction in the skill requirements of flight operators is particularly significant when operating multiple types of UAVs in a swarm.

[0026] 3. Achieve universal command and control for different UAV models at a relatively low cost, with minimal modifications to the existing command and control systems of each model. The existing flight operation software and hardware for each model can be reused by aircraft maintenance personnel, with only the addition of a centralized monitoring screen for the working status of each UAV and an interface with the UAV swarm control and access management module. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the control principle structure of the multi-model, highly heterogeneous large-scale UAV cluster command and control system of this application. Detailed Implementation

[0028] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0029] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0030] In the description of this application, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this application is in use. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. In addition, the terms "first," "second," and "third," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0031] In the description of this application, it should also be noted that, unless otherwise expressly specified and limited, the terms "set up," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0032] Furthermore, it should be noted that unless otherwise specified in this application, the specific structures, connections, positions, power sources, etc. involved are all things that a person skilled in the art can know without creative effort based on the prior art.

[0033] Example 1 refer to Figure 1 As shown in the figure, a command and control system for a large-scale, multi-model, highly heterogeneous UAV swarm is illustrated. The command and control system for a large-scale, multi-model, highly heterogeneous UAV swarm includes: a UAV swarm control authority management module, several aircraft pilot systems, and several aircraft maintenance personnel systems.

[0034] Among them, the UAV cluster control authority management module is used to manage the control authority of the UAV cluster; each aircraft pilot system is used to complete the general flight control of each UAV; and several aircraft maintenance personnel systems are used to complete the monitoring of the working status of the UAVs of the preset models and to be responsible for maintenance and handling in the event of preset emergency situations.

[0035] This application, from a system architecture perspective, divides the traditional UAV flight operator into two roles: aircraft pilot and aircraft maintenance personnel. This reduces the overall skill requirements for flight operators in swarm command and control of large UAVs. Aircraft pilots are only responsible for flying and configuring the pilot system; they are not concerned with the specific system configuration of the UAV or the corresponding emergency response procedures. Each UAV performing a mission is assigned one aircraft pilot. Aircraft maintenance personnel are assigned the maintenance system to ensure the normal operation of all UAV systems and to handle emergencies. They are assigned in small numbers based on the number of UAVs.

[0036] Example 2 refer to Figure 1 As shown in the figure, based on Embodiment 1, this embodiment discloses a command and control method for a large-scale UAV swarm with multiple models and high heterogeneity. The command and control system described in the embodiment is adopted. The command and control method for a large-scale UAV swarm with multiple models and high heterogeneity includes: dividing flight operators into two categories, including: aircraft pilots and aircraft maintenance personnel.

[0037] Aircraft pilots use the aircraft pilot system to perform general flight control of the UAV and coordinate operations with collaborating partners. Aircraft maintenance personnel monitor the dedicated operating status of the drones using the aircraft maintenance personnel system and are responsible for handling pre-set emergency situations.

[0038] Preferably, each drone performing the mission is equipped with an aircraft pilot responsible for the normal flight operation of the drone. The drone swarm performing the mission is equipped with different aircraft maintenance personnel according to the model, and the number depends on the size of the swarm, generally 1 to 2 people per model.

[0039] Large-scale drone swarm command and control systems are typically deployed in drone command and control centers, which are responsible for the coordinated execution of multiple types and multiple drones except for the take-off and landing section. The take-off and landing section is the responsibility of take-off and landing stations deployed near airport runways, which launch or recover each drone in sequence.

[0040] The user command department breaks down the task to the UAV command and control center and the take-off and landing station. After the take-off and landing station launches the UAV, it sequentially transfers control authority to the UAV command and control center. The aircraft maintenance personnel at the command and control center confirm the operational status of the transferred UAV through the configured maintenance personnel system, set it to automatic flight, and wait for the pilot to request to take over control authority.

[0041] Preferably, the aircraft pilot views the aircraft list through the configured aircraft pilot system, and after selecting a drone, sends a takeover request message to the drone cluster control authority management module through the aircraft pilot system to apply for takeover control authority of the corresponding drone. The drone cluster control authority management module assigns authority to the aircraft pilot according to the predefined authority allocation results and the working status of the corresponding drone, and sends the allocation result to the aircraft maintenance system of the corresponding aircraft type through an allocation message. The aircraft maintenance system registers and displays the information for centralized monitoring by the aircraft maintenance personnel.

[0042] Furthermore, if the drone cluster control permission management module does not find the pre-assigned permission result for the corresponding aircraft pilot, it will forward the request message to the aircraft maintenance system of this model, and the aircraft maintenance personnel will manually confirm the takeover request.

[0043] Preferably, the pilot performs automated control of the UAV based on the pilot system, which monitors the flight status and surrounding environment, and intervenes in the flight according to mission requirements. Intervention methods include switching flight paths and waypoints. The flight status includes speed, attitude, altitude, position, and heading, while the surrounding environment includes wind and temperature.

[0044] Preferably, after the pilot completes the mission, he or she will operate the UAV to the designated location and set it to automatic flight. He or she will send a message to the UAV swarm control authority management module to return control authority through the pilot's system. The UAV swarm control authority management module will then forward the message to the maintenance personnel system of the corresponding model of aircraft, where the maintenance personnel will confirm the recovery authority.

[0045] Furthermore, after the aircraft maintenance personnel confirm that the drone's control has been recovered, they transfer control to the take-off and landing station, which is then responsible for the drone's landing and recovery.

[0046] Preferably, the aircraft maintenance system monitors the aircraft status based on the UAV's onboard management computer or command and control center, issues alarms, and sends the alarm results to the aircraft pilot system for display.

[0047] Furthermore, when the drone issues a preset level alarm, or when other situations arise that the pilot deems abnormal, The aircraft pilot sends an assistance request message automatically or manually to the maintenance system of the aircraft model through the aircraft pilot system. The aircraft maintenance personnel switch the maintenance system to the corresponding UAV maintenance screen, send a command to the UAV cluster control authority management module to revoke control authority of the UAV, and then take action.

[0048] Furthermore, when an aircraft maintenance operator discovers that a drone is in a situation requiring immediate action, the system will automatically reclaim control of the drone.

[0049] The following technical effects have been achieved through this application: 1. When controlling drones in a swarm, the overall skill requirements for flight operators are significantly reduced.

[0050] Limited by the practical application bottlenecks of single-machine intelligence and swarm intelligence, each UAV still requires a flight operator when performing relatively complex tasks. Due to the complex structure of large UAV systems, the requirements for flight operators remain relatively high. This invention separates the use and maintenance of UAVs. The user (referred to as the pilot) only needs to focus on operation and does not need to be concerned with the specific system structure or emergency response strategies of the UAV, thus significantly reducing the skill requirements. The maintainer (referred to as the maintenance operator) is responsible for ensuring the normal operation of the aircraft and handling emergencies. Since the number of aircraft experiencing emergencies is small for mature aircraft, only a small number of each type of UAV needs to be configured in the swarm. The maintenance operator needs to be thoroughly familiar with the specific system structure and emergency response strategies of the UAVs, and the task content and requirements are consistent with those of the original flight operator.

[0051] Assuming the number of drones is N, and the capability requirement coefficient for a single drone pilot is α. 飞机驾驶员Since each drone is equipped with one pilot, the number of drones is also N. Additionally, assume the capability requirement coefficient for a single drone maintenance worker is α. 飞机维护员 If the quantity configuration is L, then the total cluster operation capacity requirement E of this invention is... 本发明 =N*α 飞机驾驶员 +L*α 飞机维护员 Original cluster operation capacity requirement E 原 =N*α 原飞行操作员 , where α 原飞行操作员 =α 飞机维护员 Then E 本发明 / E 原 = (N*α) 飞机驾驶员 +L*α 飞机维护员 ) / N*α 原飞行操作员 = (N*α) 飞机驾驶员 +L*α 原飞机操作员 ) / N*α 原飞行操作员 =α 飞机驾驶员 / α 原飞机操作员 + L / N, where α 飞机驾驶员 / α 原飞机操作员 It is a fixed value, estimated to be no greater than 0.3 based on the aforementioned capability allocation and practical operational experience. The physical meaning of L / N is the ratio of flight maintenance personnel to drones, which is related to the aircraft's maturity. Assuming that one in five drones requires emergency handling during a mission, i.e., L / N = 0.2, then E... 本发明 / E 原 ≤0.5. It can be seen that this invention significantly reduces the overall skill requirements for flight operators when controlling drones in a swarm.

[0052] 2. It enables universal command and control for different types of UAVs, which not only does not increase the skill requirements for flight operators, but also significantly reduces the overall skill requirements for flight operators.

[0053] The aircraft pilot of this invention does not need to be concerned with the specific system configuration and emergency response strategy of the UAV. As can be seen from the functional allocation of this application, it can be responsible for the use of different models of UAVs. The aircraft maintenance personnel are assigned a small number of UAVs according to the UAV model and are only responsible for their respective UAV models.

[0054] Assume there are M types of drones, and for simplicity, assume there are N drones of each type, with a single pilot's skill requirement for each type of drone being α. 飞机驾驶员 Considering the differences in performance and dynamic response among various types of drones, and assuming a 20% increase in capability requirement for each additional model, with one pilot assigned to each drone, the number of pilots in swarm control is M*N. Additionally, assume a capability requirement coefficient of α for each individual drone maintenance operator. 飞机维护员For simplicity, it is assumed that the capability requirement coefficient for each type of UAV flight maintenance personnel is the same, the number of maintenance personnel for each type of UAV is configured as L, and the total number is M*L. Then, the total cluster operation capability requirement E of this invention is... 本发明 =M*N*(α 飞机驾驶员 +α 飞机驾驶员 *20%*(M-1))+M*L*α 飞机维护员 Original cluster operation capacity requirement E 原 =M*N*(α 原飞行操作员 *M), where α 原飞行操作员 =α 飞机维护员 Then E 本发明 / E 原 =(M*N*(α 飞机驾驶员 +α 飞机驾驶员 *20%*(M-1))+M*L*α 飞机维护员 ) / (M*N*(α) 原飞行操作员 *M)) =α 飞机驾驶员 / (α 原飞机操作员 *M)+0.2*(α) 飞机驾驶员 / α 原飞机操作员 )*((M-1) / M)+ L / (M*N), assuming as mentioned above, take α 飞机驾驶员 / α 原飞机操作员 If the value is not greater than 0.3, and L / N is 0.2, then E 本发明 / E 原 ≤ 0.5 / M + 0.06*(M-1) / M ≤ 0.5 / M + 0.06. As can be seen from this formula, since M≥2, the overall reduction in the skill requirements of flight operators is particularly significant when operating multiple types of UAVs in a swarm.

[0055] 3. Achieve universal command and control for different UAV models at a relatively low cost, with minimal modifications to the existing command and control systems of each model. The existing flight operation software and hardware for each model can be reused by aircraft maintenance personnel, with only the addition of a centralized monitoring screen for the working status of each UAV and an interface with the UAV swarm control and access management module.

[0056] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A command and control system for a large-scale, multi-model, highly heterogeneous unmanned aerial vehicle (UAV) swarm, characterized in that: The multi-model, highly heterogeneous large-scale UAV swarm command and control system includes: The drone swarm control permission management module is used to manage the control permissions of drone swarms. Several aircraft pilot systems are used to perform common flight control for various types of UAVs; Several aircraft maintenance systems are used to monitor the working status of pre-defined UAV models and to handle maintenance and emergency situations.

2. A command and control method for a large-scale, multi-model, highly heterogeneous unmanned aerial vehicle (UAV) swarm, characterized in that: The command and control system described in claim 1, wherein the command and control method for a multi-model, highly heterogeneous large UAV swarm comprises: Flight operators are divided into two categories: aircraft pilots and aircraft maintenance personnel. Aircraft pilots use the aircraft pilot system to perform general flight control of the UAV and coordinate operations with collaborating partners. Aircraft maintenance personnel monitor the dedicated operating status of the drones using the aircraft maintenance personnel system and are responsible for handling pre-set emergency situations.

3. The command and control method for a large-scale, multi-model, highly heterogeneous UAV swarm as described in claim 2, characterized in that, Each drone performing complex tasks is equipped with an aircraft pilot who is responsible for the drone's flight operations under normal conditions. Aircraft pilots view the aircraft list through the configured aircraft pilot system. After selecting a drone, they send a takeover request message to the drone cluster control authority management module through the aircraft pilot system to request control authority over the corresponding drone. The drone cluster control authority management module assigns authority to the aircraft pilot based on the predefined authority allocation results and the working status of the corresponding drone. The allocation result is then sent to the corresponding aircraft maintenance system via an allocation message. The aircraft maintenance system registers and displays the information for centralized monitoring by the aircraft maintenance personnel.

4. The command and control method for a large-scale, multi-model, highly heterogeneous UAV swarm as described in claim 3, characterized in that, If the drone cluster control permission management module does not find the pre-assigned permission result for the corresponding aircraft pilot, it will forward the request message to the aircraft maintenance system of this model, and the aircraft maintenance personnel will manually confirm the takeover request.

5. The command and control method for a large-scale, multi-model, highly heterogeneous UAV swarm as described in claim 3, characterized in that, The pilot uses the pilot system to perform generalized control of the UAV, and the pilot system monitors the flight status and surrounding environment. The pilot also intervenes in the flight according to mission requirements, including switching flight routes and waypoints.

6. The command and control method for a large-scale, multi-model, highly heterogeneous UAV swarm as described in claim 5, characterized in that, After the pilot completes the mission, he will move the drone to the designated location and put it into automatic flight. He will then send a message to the drone swarm control authority management module through the pilot's system to return control authority. The drone swarm control authority management module will forward the message to the maintenance personnel system of the corresponding model, and the maintenance personnel will confirm the recovery authority.

7. The command and control method for a large-scale, multi-model, highly heterogeneous UAV swarm as described in claim 6, characterized in that, After the aircraft maintenance personnel confirm that the drone has been successfully reclaimed, they will transfer control to the take-off and landing station, which will then be responsible for the drone's landing and recovery.

8. The command and control method for a large-scale, multi-model, highly heterogeneous UAV swarm as described in claim 2, characterized in that, The aircraft maintenance system monitors the aircraft status based on the UAV's onboard management computer or command and control center, issues alarms, and sends the alarm results to the aircraft pilot system for display.

9. The command and control method for a large-scale, multi-model, highly heterogeneous UAV swarm as described in claim 8, characterized in that, When a drone issues a preset level alarm, or when other situations occur that the pilot deems abnormal, the pilot will automatically or manually send an assistance request message to the maintenance system of the same model through the pilot system. The maintenance personnel will then switch the maintenance system to the corresponding drone maintenance screen, issue a command to the drone cluster control authority management module to revoke control of the drone, and then take appropriate action.

10. The command and control method for a large-scale, multi-model, highly heterogeneous UAV swarm as described in claim 8, characterized in that, When an aircraft maintenance operator discovers that a drone is in a situation requiring immediate action, the system will automatically revoke control of the drone.

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