A method and device for cooperative management of unmanned aerial vehicles

Abstract

The application discloses a kind of unmanned aerial vehicle cooperative management method and device, belong to unmanned aerial vehicle control field, the method is: first unmanned aerial vehicle sends join application to master unmanned aerial vehicle, master unmanned aerial vehicle determines whether to allow first unmanned aerial vehicle to join airspace by calculating the pheromone concentration corresponding to its airspace;When first unmanned aerial vehicle joins airspace, according to its first flight route scheme planned in advance, it sends airspace cell use application to layer control unmanned aerial vehicle, and layer control unmanned aerial vehicle determines whether to allow first unmanned aerial vehicle to use airspace cell resource according to the airspace cell occupation plan maintained by it;When first unmanned aerial vehicle joins airspace, according to its own equipment information, priority is calculated, and priority is returned to master unmanned aerial vehicle, when meeting first preset condition, master unmanned aerial vehicle redistributes the role of each second unmanned aerial vehicle according to the priority of each second unmanned aerial vehicle in its airspace.Therefore, by implementing the present application, the problem of poor real-time dynamic response capability of unmanned aerial vehicle group can be solved.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) control, and more particularly to a method and apparatus for collaborative management of UAVs. Background Technology

[0002] In the field of land consolidation and ecological restoration, drone swarms are often deployed to accomplish tasks such as pre-consolidation surveying and planning, dynamic monitoring of the construction process, precise implementation of restoration projects, and long-term monitoring of post-consolidation effectiveness. Therefore, a drone swarm management method is needed to achieve intelligent and digital transformation in the field of land consolidation and ecological restoration.

[0003] Existing solutions typically rely on a single ground control center to schedule the entire drone swarm. As the number of drones increases, the master control node needs to process a large amount of status information simultaneously, resulting in excessive communication bandwidth consumption and command transmission delays. This leads to swarm response lag and even control collapse due to single-point failure. It cannot adapt to dynamically changing multi-drone scenarios, and when facing drone swarms that are dynamically adjusted in real time, it is easy to cause airspace congestion because it cannot respond to the actual drone swarm traffic fluctuations in real time.

[0004] Therefore, improving the real-time dynamic response capability of drone swarms is a technical problem that needs to be solved. Summary of the Invention

[0005] This application provides a method and apparatus for collaborative management of unmanned aerial vehicles (UAVs), which can solve the problem of poor real-time dynamic response capability of UAV swarms in the prior art.

[0006] This application provides a drone collaborative management method in some embodiments, applied to a master-controlled drone, wherein the master-controlled drone manages a corresponding airspace, and the drone collaborative management method includes: When a first UAV receives a request to join the airspace and the pheromone concentration of the airspace meets a first preset condition, the request to join is approved, so that the first UAV sends an airspace cell usage request to the layered control UAV that manages each sub-airspace in the airspace; wherein, the pheromone concentration is calculated based on the member information list of the airspace maintained by the master control UAV; When any UAV joins or leaves the airspace, the member information list is updated and broadcast to each second UAV in the airspace; When the second preset condition is met, the roles of each of the second drones are reassigned according to the member information list, and a corresponding role change instruction is issued to the corresponding second drone; wherein, the roles include: master drone and layer control drone.

[0007] Compared to existing technologies, the above embodiments have the following beneficial effects: By introducing pheromone concentration calculation at the master control drone end, the congestion status of the airspace can be dynamically assessed in real time based on the member information list, thereby controlling the addition of drones from a macroscopic perspective through the master control drone. Simultaneously, by managing sub-airspaces within the airspace from a microscopic perspective based on layered control drones, hierarchical management of the drone swarm is achieved, improving drone scheduling efficiency and alleviating the communication pressure caused by a single control node. When a drone joins or leaves the airspace, the master control drone updates and broadcasts member information in real time to maintain a consistent group status, ensuring rapid switching of subsequent master control drones. Furthermore, when the system detects airspace changes that meet preset conditions, it can automatically reassign roles based on member priorities, achieving self-organized role switching when the master or layered control drones fail, significantly improving the robustness and continuous collaboration capabilities in the drone swarm management process.

[0008] Furthermore, the pheromone concentration is calculated based on the member information list of the airspace maintained by the master-controlled UAV, including: The member information list records the speed and directional consistency density of each of the second UAVs; After normalizing the speed of each of the second UAVs, we obtain speed normalized data; The pheromone concentration is obtained by assessing the congestion level of the area based on the speed normalization data and the directional consistency density of each of the second UAVs.

[0009] Compared to existing technologies, the above embodiments have the following beneficial effects: By introducing two types of indicators—speed normalization data and directional consistency density—when calculating pheromone concentration at the master control UAV end, the congestion level and coordination consistency of the UAV swarm can be reflected in real time at different flight stages. This allows the master control UAV to dynamically determine whether to approve a joining application based on real-time mobility and density characteristics, rather than just a fixed threshold, thus avoiding communication delays and security risks caused by local airspace congestion or conflicting movement directions. Furthermore, speed normalization can shield the impact of performance differences between different UAV models on the overall assessment, and the introduction of directional consistency density enhances the judgment of swarm behavior coordination, making pheromone concentration a comprehensive indicator reflecting airspace load and coordination level.

[0010] Further, the step of reassigning the roles of each of the second drones according to the member information list includes: The member information list records the priority of each of the second drones; the priority is calculated by the second drone based on its own equipment information. Select the second UAV with the highest priority in the airspace as the new master UAV; For each sub-airspace, the second UAV with the highest priority in the sub-airspace is selected as the new layer-controlled UAV in the corresponding sub-airspace.

[0011] Compared to existing technologies, the above embodiments have the following advantages: By setting priorities for each second UAV in calculations, the computational load on the master UAV is reduced, thus freeing up the majority of computational resources for communication control. Simultaneously, by maintaining the priorities of each second UAV in real time through a member information list and automatically redistributing master and layer control roles based on priorities, self-organizing management of the UAV swarm is achieved. Furthermore, it ensures that if the master or layer control node fails, the highest-priority UAV can automatically take over control without external intervention, guaranteeing the continuity and robustness of system operation.

[0012] Furthermore, the drone collaborative management method further includes: sending a first heartbeat signal to each of the second drones in real time, so that when a second drone fails to receive the first heartbeat signal within a first preset time, each of the second drones will recommend itself to become a new master drone.

[0013] Compared with the prior art, the above embodiments have the following beneficial effects: by enabling the master drone to periodically send a first heartbeat signal, and allowing the second drone to recommend itself as the new master node when it has not received a heartbeat signal for a long time, each second drone can promptly judge the working status of the master drone, and quickly trigger the transfer of master control when the master drone fails or communication is interrupted, thus avoiding the drone swarm from entering a state of disconnection or loss of control, improving the self-recovery capability and mission continuity of the drone swarm under emergencies, and enhancing the fault tolerance and dynamic stability of the system.

[0014] Another embodiment of this application provides a UAV collaborative management method, applied to a layered UAV, wherein the layered UAV manages a sub-airspace, and the UAV collaborative management method includes: When a request for airspace cell usage from any second UAV within the corresponding airspace of the sub-airspace is received, the request is responded to according to the sub-airspace resource occupancy information list maintained by the layered UAV; wherein, the sub-airspace resource occupancy information list records the airspace cell occupancy plan within the sub-airspace; the airspace cell usage request includes a first route plan; If the first route plan conflicts with the airspace cell occupancy plan, then according to the first route plan and each of the airspace cell occupancy plans, several second route plans are generated and returned to the second UAV. If the first route plan does not conflict with the airspace cell occupancy plan, then the airspace cell usage application is approved; When any UAV joins or leaves the sub-airspace, the airspace cell occupancy plan is updated and broadcast to each second UAV within the sub-airspace.

[0015] Compared to existing technologies, the above embodiments have the following advantages: By maintaining a sub-airspace resource occupancy information list through layered control UAVs, and when a layered control UAV receives a usage request, it can dynamically determine the conflict situation based on the existing occupancy plan, and generate multiple alternative route schemes to return to the requester when conflicts exist, thereby achieving flexible path negotiation and local optimization. Compared to traditional centralized scheduling, this application, through a hierarchical management structure of master control UAVs and layered control UAVs, can effectively reduce the computational and communication pressure on the master control UAV, while improving airspace resource utilization. In addition, the broadcast update mechanism within the sub-airspace can ensure that all UAVs share the latest resource status in real time, reducing the probability of flight conflicts and redundant planning.

[0016] Another embodiment of this application provides a drone collaborative management method applied to a first drone, the drone collaborative management method comprising: When the first heartbeat signal sent by the master drone is detected, a join request is sent to the master drone so that the master drone can determine whether to approve the join request based on the pheromone concentration in the airspace where the master drone is located. If an approval response is received from the master control drone, an airspace cell usage application is sent to the corresponding layer control drone according to the preset first route plan; When a layered control UAV returns several second route plans, the optimal second route plan is determined from each of the second route plans, and the airspace cell usage application is resent to the corresponding layered control UAV according to the optimal second route plan.

[0017] Compared to existing technologies, the above embodiments have the following beneficial effects: By monitoring the heartbeat signal of the master drone, the drones can automatically sense the presence of the master drone before joining the airspace. The master drone then calculates the pheromone concentration in the airspace in real time to determine the timing for each first drone to join the airspace, thereby achieving macro-control at the master control layer. Once a first drone joins the airspace and becomes a second drone, it sends an airspace usage request to the layer-control drone. The layer-control drone can then determine if there are any navigation conflicts and obtain the optimal alternative route, effectively coordinating the macro-schedule of the master control layer with the management capabilities between the layer-control layers, significantly improving the autonomy and collaboration of the cluster operation.

[0018] Furthermore, upon receiving the approval response from the master drone, the process also includes: The master drone calculates and returns its own priority based on its own equipment information, so that the master drone can reassign the roles of each second drone according to the priority of all second drones in the airspace. The system continuously monitors the first heartbeat signal sent by the master drone, and if it does not receive the first heartbeat signal for a first preset time, it recommends itself to become the new master drone.

[0019] Compared to existing technologies, the above embodiments have the following beneficial effects: By feeding back its own priority information and continuously monitoring heartbeat signals after the first UAV joins the airspace, each second UAV in the airspace possesses both proactive reporting and passive monitoring functions. This not only assists the master UAV in optimizing role allocation in real time but also allows it to automatically take over control in abnormal situations. Through priority feedback, the master UAV can dynamically adjust the responsibilities of each node globally to ensure optimal group structure. Through heartbeat monitoring and timeout self-recommendation mechanisms, the system has rapid recovery and role redundancy functions, enabling the overall network to maintain stable collaboration and continuous task execution even in the face of communication interruptions, insufficient energy, or equipment failures.

[0020] Another embodiment of this application provides a drone collaborative management device, applied to a master-controlled drone, the master-controlled drone corresponding to and managing an airspace, the drone collaborative management device including: a first approval module, a first broadcast module and a role allocation module; The first approval module is configured to approve the application when it receives an application from a first UAV to join the airspace and the pheromone concentration of the airspace meets a first preset condition, so that the first UAV sends an application for airspace cell use to the layered control UAV that manages each sub-airspace in the airspace; wherein the pheromone concentration is calculated based on the member information list of the airspace maintained by the master control UAV. The first broadcast module is used to update and broadcast the member information list to each second drone in the airspace when any drone joins or leaves the airspace; The role allocation module is used to reallocate the roles of each of the second drones according to the member information list when the second preset condition is met, and to issue corresponding role change instructions to the corresponding second drones; wherein, the roles include: master drone and layer control drone.

[0021] Another embodiment of this application provides a drone collaborative management device for layered drones, wherein the layered drones manage a sub-airspace, and the drone collaborative management device includes: a second approval module, a first execution module, a second execution module, and a second broadcast module; The second approval module is used to respond to the airspace cell usage application based on the sub-airspace resource occupancy information list maintained by the layered UAV when it receives an application from any second UAV within the airspace corresponding to the sub-airspace to use the airspace cell in the sub-airspace; wherein the sub-airspace resource occupancy information list records the airspace cell occupancy plan within the sub-airspace; the airspace cell usage application includes a first route plan; The first execution module is configured to generate and return several second route plans to the second UAV based on the first route plan and each of the airspace cell occupancy plans if the first route plan conflicts with the airspace cell occupancy plan. The second execution module is configured to approve the airspace cell usage application if the first route plan does not conflict with the airspace cell occupancy plan; The second broadcast module is used to update and broadcast the airspace cell occupancy plan to each second UAV in the sub-airspace when any UAV joins or leaves the sub-airspace.

[0022] Another embodiment of this application also provides a drone collaborative management device, applied to a first drone, the drone collaborative management device including: a first application sending module, a second application sending module and a third application sending module; The first application sending module is used to send a join application to the master drone when it hears the first heartbeat signal sent by the master drone, so that the master drone can determine whether to approve the join application based on the pheromone concentration in the airspace where the master drone is located. The second application sending module is used to send an airspace cell usage application to the corresponding layer-controlled drone according to the preset first route plan if it receives an approval response from the master control drone. The third application sending module is used to determine the optimal second route plan from each of the second route plans when it receives several second route plans returned by the layered control UAV, and resend the airspace cell use application to the corresponding layered control UAV according to the optimal second route plan. Attached Figure Description

[0023] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating a drone collaborative management method applied to a master-controlled drone, provided in some embodiments of this application. Figure 2 This is a flowchart illustrating a drone collaborative management method applied to a layered control drone, provided in some embodiments of this application. Figure 3 This is a flowchart illustrating a drone collaborative management method applied to a first drone, provided in some embodiments of this application. Figure 4 This is a timing diagram illustrating a drone collaborative management method provided in some embodiments of this application; Figure 5 This is a schematic diagram of the structure of a drone collaborative management device applied to a master-controlled drone, provided in some embodiments of this application; Figure 6 This is a schematic diagram of the structure of a drone collaborative management device applied to a layered control drone provided in some embodiments of this application; Figure 7 This is a schematic diagram of the structure of a drone collaborative management device applied to a first drone, provided in some embodiments of this application. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0027] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0028] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0029] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0030] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0031] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; 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; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0032] Existing solutions typically rely on a single ground control center to schedule the entire drone swarm. As the number of drones increases, the master control node needs to process a large amount of status information simultaneously, resulting in excessive communication bandwidth consumption and command transmission delays. This leads to swarm response lag and even control collapse due to single-point failure. It cannot adapt to dynamically changing multi-drone scenarios, and when facing drone swarms that are dynamically adjusted in real time, it is easy to cause airspace congestion because it cannot respond to the actual drone swarm traffic fluctuations in real time.

[0033] Please refer to Figure 1 To address the problem of poor real-time dynamic response capability of drone swarms in existing technologies, this application provides a drone collaborative management method applied to a master-controlled drone, which manages a corresponding airspace. The drone collaborative management method includes steps S101 to S103, specifically: S101: When a first UAV is received to join the airspace and the pheromone concentration of the airspace meets a first preset condition, the joining application is approved, so that the first UAV sends an airspace cell usage application to the layered control UAV that manages each sub-airspace in the airspace; wherein, the pheromone concentration is calculated based on the member information list of the airspace maintained by the master control UAV.

[0034] Preferably, in some embodiments of this application, the airspace cell is the smallest spatial unit representing the division of the airspace managed by the master drone. Each airspace cell has a unique code, which includes at least the sub-airspace where the airspace cell is located and its own airspace cell number. It can be understood that the master drone is the organization controller (OC) in the drone swarm, the overall manager of each sub-airspace, responsible for macro-level traffic control, member information management, and synchronization of the entire airspace. The layer-controlled drone is the layer manager (LM) in the drone swarm, the scheduler of airspace cell resources in its sub-airspace, responsible for monitoring and controlling the resource allocation and conflict resolution of airspace cells. The first drone is an external drone waiting to join the drone swarm. When the first drone joins the airspace of the master drone, it becomes the second drone in the airspace. Therefore, the first drone can be regarded as a regular drone (UAV). By receiving instructions from the OC or LM, and upon joining the airspace, the first drone can accurately take over as the OC or LM at any time.

[0035] Furthermore, in some embodiments of this application, the pheromone concentration is calculated based on the member information list of the airspace maintained by the master-controlled UAV, including: The member information list records the speed and directional consistency density of each of the second UAVs; After normalizing the speed of each of the second UAVs, we obtain speed normalized data; The pheromone concentration is obtained by assessing the congestion level of the area based on the speed normalization data and the directional consistency density of each of the second UAVs.

[0036] Preferably, in some embodiments of this application, the formula for calculating the pheromone concentration is as follows: in, For the airspace in time The concentration of pheromones at that time; This represents the total number of the second type of drones within the airspace; This is the speed weighting coefficient; For the second drone The current speed; The maximum permissible speed within the airspace; This refers to the directional density weighting coefficient; For the second drone The directional consistency density, this value is calculated by the second UAV. The value is obtained by comparing the heading with the average heading of surrounding drones; the greater the difference, the smaller the value.

[0037] Preferably, in some embodiments of this application, approving the application when a first UAV's request to join the airspace is received and the pheromone concentration of the airspace meets a first preset condition includes: if the currently calculated pheromone concentration is less than or equal to a preset minimum threshold. If the calculated pheromone concentration is greater than the minimum threshold, then the first drone is allowed to join and pass freely; And less than or equal to the preset maximum threshold The first drone is allowed to join, but at the same time, airspace with lower surrounding pheromone concentrations will be recommended to the first drone; if the currently calculated pheromone concentration is greater than the maximum threshold... Then, no drones are allowed to participate. It can be set to 5. It can be set to 15.

[0038] This application introduces two types of indicators—speed normalization data and directional consistency density—when calculating pheromone concentration at the master-controlled UAV. This allows for real-time reflection of the congestion level and coordination consistency of the UAV swarm at different flight phases. The master-controlled UAV, when approving a UAV joining application, not only relies on a fixed threshold but also makes a dynamic judgment based on real-time mobility and density characteristics, thus avoiding communication delays and security risks caused by localized airspace congestion or conflicting flight directions. Furthermore, speed normalization can mask the impact of performance differences between different UAV models on the overall assessment, while the introduction of directional consistency density enhances the judgment of swarm behavior coordination, making pheromone concentration a comprehensive indicator reflecting airspace load and coordination levels.

[0039] S102: When any UAV joins or leaves the airspace, update and broadcast the member information list to each second UAV in the airspace.

[0040] Preferably, in some embodiments of this application, the member information list records the role, sub-airspace, drone ID, and estimated departure time of each second drone within the airspace corresponding to the master drone. It is understood that the member information list only includes the basic attributes of the second drones, requiring relatively few communication resources.

[0041] Preferably, in some embodiments of this application, whenever any UAV joins or leaves the airspace, the pheromone concentration in the airspace needs to be recalculated and broadcast to each second UAV to ensure data synchronization and prevent data loss when the master UAV switches over.

[0042] S103: When the second preset condition is met, the roles of each of the second drones are reassigned according to the member information list, and a corresponding role change instruction is issued to the corresponding second drone; wherein, the roles include: master drone and layer control drone.

[0043] Preferably, in some embodiments of this application, the second preset conditions include: the master drone detects that its own battery is too low, there is a second drone detecting that the heartbeat of the master drone has timed out, and when a new master drone is not re-determined or any other master drone actively initiates a reselection after a second preset time has elapsed.

[0044] Furthermore, in some embodiments of this application, the step of reassigning the roles of each of the second drones according to the member information list includes: The member information list records the priority of each of the second drones; the priority is calculated by the second drone based on its own equipment information. Select the second UAV with the highest priority in the airspace as the new master UAV; For each sub-airspace, the second UAV with the highest priority in the sub-airspace is selected as the new layer-controlled UAV in the corresponding sub-airspace.

[0045] Preferably, in some embodiments of this application, the device information includes: remaining power, full charge, onboard computing power (which can be determined by comprehensive indicators such as CPU clock speed and available memory), communication signal strength, task priority, and required stay time in the airspace.

[0046] Preferably, in some embodiments of this application, the formula for calculating the priority is as follows: in, For the second drone Priority; , , , as well as These are weighting coefficients, and preferences can be adjusted according to the actual application scenario; For the second drone The remaining battery power; This represents the drone's full charge level. For the second drone Onboard computing power; This represents the largest onboard computing power among all second-generation drones. For the second drone The strength of the communication signal; This serves as a reference value for communication signal strength. For the second drone Task priority; For the second drone The length of stay; The maximum time threshold allowed for a drone to act as a master or layered drone.

[0047] This application reduces the computational load on the master drone by assigning priorities to each second drone, thus freeing up the majority of computational resources for communication control. Simultaneously, the priorities of each second drone are maintained in real-time through a member information list, and the master and layer control roles are automatically reassigned based on these priorities. This achieves self-organizing management of the drone swarm and ensures that if the master or layer control node fails, the highest-priority drone can automatically take over control without external intervention, guaranteeing system continuity and robustness.

[0048] Furthermore, in some embodiments of this application, the drone collaborative management method further includes: sending a first heartbeat signal to each of the second drones in real time, so that when a second drone fails to receive the first heartbeat signal within a first preset time, each of the second drones will self-recommend to become a new master drone.

[0049] Preferably, in some embodiments of this application, the step of making each of the second drones recommend itself as the new master drone when there is a second drone that has not received the first heartbeat signal within a first preset time includes: the second drone determines the new master drone in the current airspace based on the second drone with the highest priority in its synchronously received member information list.

[0050] This application enables the master drone to periodically send a first heartbeat signal and allows the second drone to recommend itself as the new master node when it has not received a heartbeat signal for a long time. This allows each second drone to judge the working status of the master drone in a timely manner and quickly trigger the transfer of master control when the master drone fails or communication is interrupted. This prevents the drone swarm from entering a state of disconnection or loss of control, improves the self-recovery capability and mission continuity of the drone swarm under emergencies, and enhances the fault tolerance and dynamic stability of the system.

[0051] In summary, the UAV collaborative management method for master-controlled UAVs provided in this application has the following advantages compared to existing technologies: By introducing pheromone concentration calculation at the master-controlled UAV end, the congestion status of the airspace can be dynamically assessed in real time based on the member information list, thereby controlling the addition of UAVs from a macroscopic perspective through the master-controlled UAV. Simultaneously, by managing sub-airspaces within the airspace from a microscopic perspective based on layered control UAVs, hierarchical management of the UAV swarm is achieved, improving UAV scheduling efficiency and alleviating the communication pressure caused by a single control node. When a UAV joins or leaves the airspace, the master-controlled UAV updates and broadcasts member information in real time to maintain a consistent group status, ensuring rapid switching of subsequent master-controlled UAVs. Furthermore, when the system detects airspace changes that meet preset conditions, it can automatically reassign roles based on member priorities, achieving self-organized role switching when the master-controlled or layered control UAVs fail, significantly improving the robustness and continuous collaborative capability of the UAV swarm management process.

[0052] refer to Figure 2 This application provides a method for collaborative management of unmanned aerial vehicles (UAVs), applied to layered UAVs, wherein the layered UAVs manage a sub-airspace. The UAV collaborative management method includes steps S201 to S204, specifically: S201: When an application for airspace cell use of the sub-airspace is received from any second UAV within the corresponding airspace of the sub-airspace, the application for airspace cell use is responded to according to the sub-airspace resource occupancy information list maintained by the layer-controlled UAV; wherein, the sub-airspace resource occupancy information list records the airspace cell occupancy plan within the sub-airspace; the application for airspace cell use includes a first route plan.

[0053] Preferably, in some embodiments of this application, the airspace cell occupancy plan includes: a time window in which airspace cells are occupied in the future.

[0054] S202: If the first route plan conflicts with the airspace cell occupancy plan, then generate and return several second route plans to the second UAV according to the first route plan and each of the airspace cell occupancy plans.

[0055] Preferably, in some embodiments of this application, the conflict between the first route plan and the airspace cell occupancy plan is specifically that the occupancy time of each airspace cell in the first route overlaps with the time window in which the airspace cell will be occupied in the future.

[0056] Preferably, in some embodiments of this application, the step of generating and returning several second route plans based on the first route plan and each of the airspace cell occupancy plans includes: modifying the time, speed, horizontal or vertical route in the first route plan, wherein the vertical route modification requires communication with layer-controlled UAVs in other sub-airspaces to obtain the airspace cell occupancy plans of those other sub-airspaces. The specific process of generating the second route plans can be implemented using any scheduling and planning algorithm, and this application does not impose specific limitations on this process.

[0057] Preferably, in some embodiments of this application, after several second route plans are returned to the second UAV, the system waits for a new airspace cell usage request from the second UAV. If the route plan in the new airspace cell usage request is one of the second route plans, the airspace cell usage request is directly approved; if it is still the original preset first route plan, the airspace cell usage request is directly rejected. If no new airspace cell usage request is received from the second UAV after a third preset time, it means that the second UAV has rejected all second route plans, and the airspace cell usage request initially sent by the second UAV is directly rejected.

[0058] S203: If the first route plan does not conflict with the airspace cell occupancy plan, then the airspace cell usage application is approved.

[0059] S204: When any UAV joins or leaves the sub-airspace, update and broadcast the airspace cell occupancy plan to each second UAV in the sub-airspace.

[0060] In summary, the UAV collaborative management method for layered-control UAVs provided in this application has the following advantages compared to existing technologies: By maintaining a sub-airspace resource occupancy information list through layered-control UAVs, and upon receiving a usage request, the layered-control UAVs can dynamically determine conflict situations based on existing occupancy plans, and generate multiple alternative flight path schemes to return to the requester when conflicts exist, thereby achieving flexible path negotiation and local optimization. Compared to traditional centralized scheduling, this application, through a hierarchical management structure of master control UAVs and layered-control UAVs, can effectively reduce the computational and communication pressure on the master control UAV while improving airspace resource utilization. Furthermore, the broadcast update mechanism within the sub-airspace ensures that all UAVs share the latest resource status in real time, reducing the probability of flight conflicts and redundant planning.

[0061] refer to Figure 3 This application provides a method for collaborative management of unmanned aerial vehicles (UAVs), applied to a first UAV. The method includes steps S301 to S303, specifically: S301: When the first heartbeat signal sent by the master drone is detected, a join request is sent to the master drone so that the master drone can determine whether to approve the join request based on the pheromone concentration in the airspace where the master drone is located.

[0062] S302: If an approval response is received from the master control drone, an airspace cell usage application is sent to the corresponding layer control drone according to the preset first route plan.

[0063] Furthermore, in some embodiments of this application, after receiving the approval response returned by the master drone, the method further includes: The master drone calculates and returns its own priority based on its own equipment information, so that the master drone can reassign the roles of each second drone according to the priority of all second drones in the airspace. The system continuously monitors the first heartbeat signal sent by the master drone, and if it does not receive the first heartbeat signal for a first preset time, it recommends itself to become the new master drone.

[0064] This application enables each secondary UAV in the airspace to possess both proactive reporting and passive monitoring capabilities by feeding back its own priority information and continuously monitoring heartbeat signals after the first UAV joins the airspace. This allows it to assist the master UAV in optimizing role allocation in real time and automatically take over control in abnormal situations. Through priority feedback, the master UAV can dynamically adjust the responsibilities of each node globally to ensure optimal group structure. Through heartbeat monitoring and timeout self-recommendation mechanisms, the system has rapid recovery and role redundancy functions, enabling the overall network to maintain stable collaboration and continuous task execution even in the face of communication interruptions, insufficient energy, or equipment failures.

[0065] S303: When receiving several second route plans returned by the layered control UAV, the optimal second route plan is determined from each of the second route plans, and the airspace cell use application is resent to the corresponding layered control UAV according to the optimal second route plan.

[0066] Preferably, in some embodiments of this application, determining the optimal second route option from each second route option includes: performing a multi-dimensional cost evaluation on each second route option, including time cost: the delay that the option will cause; energy cost: the energy consumption increased by rerouting, climbing / descending; feasibility: whether the performance of the UAV supports the option; rule compliance: the altitude restrictions of the target airspace; mission constraints: whether the latest arrival time of the mission is met, etc.

[0067] In summary, the UAV collaborative management method for a first UAV provided in this application has the following advantages compared to existing technologies: By maintaining a sub-airspace resource occupancy information list through layered control UAVs, and when a layered control UAV receives a usage request, it can dynamically determine the conflict situation based on the existing occupancy plan, and generate multiple alternative route schemes to return to the requester when conflicts exist, thereby achieving flexible path negotiation and local optimization. Compared to traditional centralized scheduling, this application, through a hierarchical management structure of master control UAVs and layered control UAVs, can effectively reduce the computational and communication pressure on the master control UAV while improving airspace resource utilization. Furthermore, the broadcast update mechanism within the sub-airspace ensures that all UAVs share the latest resource status in real time, reducing the probability of flight conflicts and redundant planning.

[0068] To more clearly explain the collaborative management process of drones with different roles within a drone swarm, please refer to the following... Figure 4 The timing diagram of the drone collaborative management method shown is used for further explanation.

[0069] Before joining an airspace, the first drone sends a joining request to the master drone. Upon receiving the request, the master drone checks the pheromone concentration in the airspace. If the concentration is normal, it approves the first drone's joining and updates and broadcasts the currently maintained member information list to the second drone (which can be understood as all drones in the current airspace). If the pheromone concentration is too high, the master drone rejects the first drone's joining request and suggests it detour. After joining the airspace, the first drone determines the next sub-airspace it needs to go to based on its preset first flight path and sends an airspace cell usage request to the layer-controlled drones in that sub-airspace. When the layer-controlled drone receives the airspace... After a cell usage application is submitted, the first UAV queries the sub-airspace resource occupancy information list according to the first route plan to determine whether the first route plan conflicts with the existing airspace cell occupancy plan. If there is no conflict, the airspace cell usage application of the first UAV is approved. After the first UAV flies according to its approved route plan, it feeds back the used airspace cells to the layer control UAV in real time, so that the layer control UAV updates the sub-airspace resource occupancy information list in a timely manner. If there is a conflict, the application is rejected and several suggested second route plans are returned for the first UAV to make a decision. When the first UAV finishes flying and leaves the airspace, it sends an exit notification to the master control UAV. At this time, the master control UAV updates and broadcasts the member information list to each second UAV.

[0070] like Figure 5 As shown, based on the above method embodiments, an embodiment of this application provides a drone collaborative management device applied to a master drone, wherein the master drone manages an airspace, and the drone collaborative management device includes: a first approval module 401, a first broadcast module 402, and a role allocation module 403.

[0071] Further, in some embodiments of this application, the first approval module 401 is used to approve the application when it receives an application from a first UAV to join the airspace and the pheromone concentration of the airspace meets a first preset condition, so that the first UAV sends an application for airspace cell use to the layered control UAVs that manage each sub-airspace in the airspace; wherein, the pheromone concentration is calculated based on the member information list of the airspace maintained by the master control UAV; the first broadcast module 402 is used to update and broadcast the member information list to each second UAV in the airspace when any UAV joins or leaves the airspace; the role allocation module 403 is used to reallocate the roles of each second UAV according to the member information list when the second preset condition is met, and issue a corresponding role change instruction to the corresponding second UAV; wherein, the roles include: master control UAV and layered control UAV.

[0072] Furthermore, in some embodiments of this application, the pheromone concentration is calculated based on the member information list of the airspace maintained by the master-controlled UAV, including: wherein the member information list records the speed and directional consistency density of each second UAV; after normalizing the speed of each second UAV, speed normalized data is obtained; the congestion level of the area is assessed based on the speed normalized data of each second UAV and the directional consistency density to obtain the pheromone concentration.

[0073] Further, in some embodiments of this application, the role allocation module 403 includes: a first selection unit and a second selection unit; the role allocation module 403 is used to reallocate the roles of each of the second drones according to the member information list, including: wherein the member information list records the priority of each of the second drones; wherein the priority is calculated by the second drone based on its own equipment information; the first selection unit is used to select the second drone with the highest priority in the airspace as the new master drone; the second selection unit is used to select the second drone with the highest priority in each sub-airspace as the new master drone in the corresponding sub-airspace.

[0074] Furthermore, in some embodiments of this application, the drone collaborative management device further includes: a heartbeat signal sending module: the heartbeat signal sending module is used to send a first heartbeat signal to each of the second drones in real time, so that when a second drone fails to receive the first heartbeat signal within a first preset time, each of the second drones will recommend itself to become a new master drone.

[0075] In summary, the UAV collaborative management device for master-controlled UAVs provided in this application has the following advantages compared to existing technologies: By introducing pheromone concentration calculation at the master-controlled UAV end, the congestion status of the airspace can be dynamically assessed in real time based on the member information list, thereby controlling the addition of UAVs from a macroscopic perspective through the master-controlled UAV. Simultaneously, by managing sub-airspaces within the airspace from a microscopic perspective based on layered control UAVs, hierarchical management of the UAV swarm is achieved, improving UAV scheduling efficiency and alleviating the communication pressure caused by a single control node. When a UAV joins or leaves the airspace, the master-controlled UAV updates and broadcasts member information in real time to maintain a consistent group status, ensuring rapid switching of subsequent master-controlled UAVs. Furthermore, when the system detects airspace changes that meet preset conditions, it can automatically reassign roles based on member priorities, achieving self-organized role switching when the master-controlled or layered control UAVs fail, significantly improving the robustness and continuous collaborative capability of the UAV swarm management process.

[0076] like Figure 6 As shown, based on the above method embodiments, an embodiment of this application provides a UAV collaborative management device, applied to a layered UAV, wherein the layered UAV manages a sub-airspace, and the UAV collaborative management device includes: a second approval module 501, a first execution module 502, a second execution module 503, and a second broadcast module 504.

[0077] Further, in some embodiments of this application, the second approval module 501 is used to respond to the airspace cell usage application based on the sub-airspace resource occupancy information list maintained by the layered UAV when receiving an airspace cell usage application from any second UAV within the airspace corresponding to the sub-airspace; wherein, the sub-airspace resource occupancy information list records the airspace cell occupancy plan within the sub-airspace; the airspace cell usage application includes a first route plan; the first execution module 502 is used to generate and return several second route plans to the second UAV based on the first route plan and each airspace cell occupancy plan if the first route plan conflicts with the airspace cell occupancy plan; the second execution module 503 is used to approve the airspace cell usage application if the first route plan does not conflict with the airspace cell occupancy plan; the second broadcast module 504 is used to update and broadcast the airspace cell occupancy plan to each second UAV within the sub-airspace when any UAV joins or leaves the sub-airspace.

[0078] In summary, the UAV collaborative management device for layered control UAVs provided in this application has the following advantages compared to existing technologies: By maintaining a sub-airspace resource occupancy information list through layered control UAVs, and when a layered control UAV receives a usage request, it can dynamically determine the conflict situation based on the existing occupancy plan, and generate multiple alternative route schemes to return to the requester when conflicts exist, thereby achieving flexible path negotiation and local optimization. Compared to traditional centralized scheduling, this application, through a hierarchical management structure of master control UAVs and layered control UAVs, can effectively reduce the computational and communication pressure on the master control UAV while improving airspace resource utilization. Furthermore, the broadcast update mechanism within the sub-airspace ensures that all UAVs share the latest resource status in real time, reducing the probability of flight conflicts and redundant planning.

[0079] like Figure 7 As shown, based on the above method embodiments, one embodiment of this application provides a drone collaborative management device applied to a first drone. The drone collaborative management device includes: a first application sending module 601, a second application sending module 602, and a third application sending module 603.

[0080] Further, in some embodiments of this application, the first application sending module 601 is used to send a join application to the master control drone when it hears the first heartbeat signal sent by the master control drone, so that the master control drone can determine whether to approve the join application based on the pheromone concentration in the airspace where the master control drone is located; the second application sending module 602 is used to send an airspace cell use application to the corresponding layer control drone according to a preset first route plan if it receives an approval response from the master control drone; the third application sending module 603 is used to determine the optimal second route plan from each of the second route plans when it receives a plurality of second route plans returned by the layer control drone, and resend the airspace cell use application to the corresponding layer control drone according to the optimal second route plan.

[0081] Furthermore, in some embodiments of this application, after receiving the approval response returned by the master drone, the method further includes: calculating and returning its own priority to the master drone based on its own device information, so that the master drone can reassign the roles of each second drone according to the priority of all second drones in the airspace; continuously monitoring the first heartbeat signal sent by the master drone, and recommending itself to become the new master drone when the first heartbeat signal is not received for a first preset time.

[0082] In summary, the UAV collaborative management device for a first UAV provided in this application embodiment has the following advantages compared to the prior art: It maintains a sub-airspace resource occupancy information list through layered control UAVs, and when a layered control UAV receives a usage request, it can dynamically determine the conflict situation based on the existing occupancy plan, and generate multiple alternative route schemes to return to the requester when conflicts exist, thereby achieving flexible path negotiation and local optimization. Compared to traditional centralized scheduling, this application, through a hierarchical management structure of master control UAVs and layered control UAVs, can effectively reduce the computational and communication pressure on the master control UAV while improving airspace resource utilization. Furthermore, the broadcast update mechanism within the sub-airspace ensures that all UAVs share the latest resource status in real time, reducing the probability of flight conflicts and redundant planning.

[0083] It is understood that the above-described device embodiments correspond to the method embodiments of this application, and can implement the UAV collaborative management method provided by any of the above-described method embodiments of this application.

[0084] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided in this application, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0085] Based on the above embodiments of the drone collaborative management method, another embodiment of this application provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the drone collaborative management method of any embodiment of this application.

[0086] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete this application. The one or more module units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0087] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0088] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0089] Based on the above-described method embodiments, another embodiment of this application provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the UAV collaborative management method described in any of the above-described method embodiments of this application.

[0090] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

Claims

1. A method for collaborative management of unmanned aerial vehicles (UAVs), characterized in that, Applied to a master-controlled unmanned aerial vehicle (UAV) that manages a corresponding airspace, the UAV collaborative management method includes: When a first UAV receives a request to join the airspace and the pheromone concentration of the airspace meets a first preset condition, the request to join is approved, so that the first UAV sends an airspace cell usage request to the layered control UAV that manages each sub-airspace in the airspace; wherein, the pheromone concentration is calculated based on the member information list of the airspace maintained by the master control UAV; When any UAV joins or leaves the airspace, the member information list is updated and broadcast to each second UAV in the airspace; When the second preset condition is met, the roles of each of the second drones are reassigned according to the member information list, and a corresponding role change instruction is issued to the corresponding second drone; wherein, the roles include: master drone and layer control drone; The pheromone concentration is calculated based on the member information list of the airspace maintained by the master-controlled UAV, including: The member information list records the speed and directional consistency density of each of the second UAVs; After normalizing the speed of each of the second UAVs, we obtain speed normalized data; The congestion level of the airspace is assessed based on the normalized speed data and the directional consistency density of each of the second UAVs, and the pheromone concentration is obtained. The specific formula for calculating the pheromone concentration is as follows: in, For the airspace in time The concentration of pheromones at that time; This represents the total number of the second type of drones within the airspace; This is the speed weighting coefficient; For the second drone The current speed; The maximum permissible speed within the airspace; This refers to the directional density weighting coefficient; For the second drone The directional consistency density, this value is calculated by the second UAV. The value is obtained by comparing the heading with the average heading of surrounding drones; the greater the difference, the smaller the value.

2. The drone collaborative management method as described in claim 1, characterized in that, The roles of each of the second drones are reassigned according to the member information list. include: The member information list records the priority of each of the second drones; the priority is calculated by the second drone based on its own equipment information. Select the second UAV with the highest priority in the airspace as the new master UAV; For each sub-airspace, the second UAV with the highest priority in the sub-airspace is selected as the new layer-controlled UAV in the corresponding sub-airspace.

3. The drone collaborative management method as described in claim 1, characterized in that, The drone collaborative management method further includes: sending a first heartbeat signal to each of the second drones in real time, so that when a second drone fails to receive the first heartbeat signal within a first preset time, each of the second drones will recommend itself to become a new master drone.

4. A drone collaborative management device, characterized in that, Applied to a master-controlled drone, the master-controlled drone manages a corresponding airspace, and the drone collaborative management device includes: a first approval module, a first broadcast module, and a role assignment module; The first approval module is configured to approve the application when it receives an application from a first UAV to join the airspace and the pheromone concentration of the airspace meets a first preset condition, so that the first UAV sends an application for airspace cell use to the layered control UAV that manages each sub-airspace in the airspace; wherein the pheromone concentration is calculated based on the member information list of the airspace maintained by the master control UAV. The first broadcast module is used to update and broadcast the member information list to each second drone in the airspace when any drone joins or leaves the airspace; The role allocation module is used to reassign roles to each of the second drones according to the member information list when the second preset condition is met, and to issue corresponding role change instructions to the corresponding second drones; wherein, the roles include: master drone and layer control drone; The pheromone concentration is calculated based on the member information list of the airspace maintained by the master-controlled UAV, including: The member information list records the speed and directional consistency density of each of the second UAVs; After normalizing the speed of each of the second UAVs, we obtain speed normalized data; The congestion level of the airspace is assessed based on the normalized speed data and the directional consistency density of each of the second UAVs, and the pheromone concentration is obtained. The specific formula for calculating the pheromone concentration is as follows: in, For the airspace in time The concentration of pheromones at that time; This represents the total number of the second type of drones within the airspace; This is the speed weighting coefficient; For the second drone The current speed; The maximum permissible speed within the airspace; This refers to the directional density weighting coefficient; For the second drone The directional consistency density, this value is calculated by the second UAV. The value is obtained by comparing the heading with the average heading of surrounding drones; the greater the difference, the smaller the value.

Images