Collaborative control method and device based on UAV cluster failure analysis

Abstract

The present invention discloses a collaborative control method and device based on failure analysis of unmanned aerial vehicle (UAV) clusters. The method comprises: determining a target UAV corresponding to each subtask according to execution area parameters corresponding to each divided subtask, and monitoring the task execution status of each target UAV; determining a first subtask to be adjusted from all subtasks for which the corresponding target UAV meets a task execution failure condition according to the task execution status of all target UAVs, and analyzing a task execution failure factor of the first subtask to be adjusted; and collaboratively controlling the UAV cluster according to the task execution failure factor. In this way, task execution failure analysis can be performed intelligently on the target UAVs of the subtasks, and then collaboratively controlling the UAV cluster according to the task execution failure factor, which is conducive to timely adjusting the task execution process, improving the control reliability and accuracy of the UAV cluster, and thus helping to improve the control stability of the UAV cluster.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicle (UAV) control technology, and in particular to a collaborative control method and device based on UAV cluster failure analysis. Background Art

[0002] Drone swarms, with their high flexibility, wide adaptability and controllable economy, have increasingly broad application potential and have received great attention at home and abroad.

[0003] Currently, drone swarms are often controlled by a single leader controlling multiple followers. However, a single leader in a drone swarm is susceptible to environmental interference, making its control over multiple followers less stable. This, in turn, impacts the swarm's mission execution, making it difficult to ensure mission execution timeliness. Therefore, it is crucial to provide a method that can improve the control stability of drone swarms. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a collaborative control method and device based on UAV cluster failure analysis, which is conducive to timely adjustment of the task execution process, improving the control reliability and accuracy of the UAV cluster, and thus helping to improve the control stability of the UAV cluster.

[0005] In order to solve the above technical problems, the first aspect of the present invention discloses a collaborative control method based on failure analysis of drone clusters, the method comprising:

[0006] Performing a task division operation on the target task to be performed by the drone cluster to obtain multiple subtasks, and determining an execution area parameter corresponding to each of the subtasks; the execution area parameter includes at least one of an execution area range parameter, an execution area type parameter, and an execution area object parameter;

[0007] For each of the subtasks, determining a target drone corresponding to the subtask from the drone cluster according to the execution area parameters corresponding to the subtask, and monitoring the target drone's execution of the task corresponding to the subtask;

[0008] According to the task execution status of the target UAVs corresponding to all the subtasks, a first subtask to be adjusted whose corresponding target UAV meets a preset task execution failure condition is determined from all the subtasks, and a task execution failure factor of the target UAV corresponding to the first subtask to be adjusted is analyzed;

[0009] The drone cluster is collaboratively controlled according to a task execution failure factor of the target drone corresponding to the first subtask to be adjusted.

[0010] As an optional embodiment, in the first aspect of the present invention, the collaborative control operation of the drone cluster based on the task execution failure factor of the target drone corresponding to the first subtask to be adjusted includes:

[0011] Determining a task execution weight value of the first to-be-adjusted subtask based on the task content of the target task and the task content of the first to-be-adjusted subtask, and judging whether the task execution weight value is greater than or equal to a preset weight threshold;

[0012] When it is determined that the task execution weight value is greater than or equal to the weight threshold, determining a second subtask to be adjusted from all the subtasks except the first subtask to be adjusted, the second subtask to be adjusted corresponding to the target drone meets the preset task execution condition;

[0013] When the task execution failure factor of the target UAV corresponding to the first subtask to be adjusted includes a communication failure factor, the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted is obtained, and based on the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted, a collaborative control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted; the communication failure parameter includes at least one of a communication failure time parameter, a communication failure position parameter, and a communication failure type parameter.

[0014] As an optional embodiment, in the first aspect of the present invention, performing a collaborative control operation on the target UAV corresponding to the second subtask to be adjusted for the first subtask to be adjusted based on the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted includes:

[0015] Determining device parameters of the target UAV corresponding to the second to-be-adjusted subtask; the device parameters include at least one of device function parameters, device communication type parameters, device communication range parameters, and historical task execution status;

[0016] Determining, based on the device parameters of the target UAV corresponding to the second subtask to be adjusted and the communication failure parameters of the target UAV corresponding to the first subtask to be adjusted, a first control parameter of the target UAV corresponding to the second subtask to be adjusted for the first subtask to be adjusted; the first control parameter includes at least one of a communication control parameter, a first task execution position parameter, and a first task execution function parameter;

[0017] According to the first control parameter of the target UAV corresponding to the second subtask to be adjusted for the first subtask to be adjusted, a coordinated control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted.

[0018] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0019] When the task execution failure factor of the target UAV corresponding to the first to-be-adjusted subtask includes a task execution obstacle failure factor, determining a task execution obstacle parameter and a task non-execution status of the target UAV corresponding to the first to-be-adjusted subtask; the task execution obstacle parameter includes a task execution obstacle type parameter and / or a task execution obstacle location parameter;

[0020] According to the task execution obstacle parameters of the target UAV corresponding to the first subtask to be adjusted and the non-execution status of the task, a collaborative control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted.

[0021] As an optional embodiment, in the first aspect of the present invention, the step of performing a collaborative control operation on the target drone corresponding to the second subtask to be adjusted and the target drone corresponding to the first subtask to be adjusted based on the task execution obstacle parameters of the target drone corresponding to the first subtask to be adjusted and the task non-execution status includes:

[0022] Determining, based on the task execution obstacle parameters of the target UAV corresponding to the first subtask to be adjusted, obstacle elimination control parameters for the target UAV corresponding to the second subtask to be adjusted with respect to the first subtask to be adjusted; the obstacle elimination control parameters include obstacle crossing flight path control parameters and / or obstacle elimination device function control parameters;

[0023] Determining, based on the unexecuted task of the target UAV corresponding to the first subtask to be adjusted, second control parameters for the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted for the first subtask to be adjusted; the second control parameters include a second task execution position parameter and / or a second task execution function parameter;

[0024] According to the obstacle elimination control parameters, the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted for the second control parameter of the first subtask to be adjusted, the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted are subjected to a collaborative control operation for the first subtask to be adjusted.

[0025] As an optional embodiment, in the first aspect of the present invention, determining the target drone corresponding to the subtask from the drone cluster based on the execution area parameter corresponding to the subtask includes:

[0026] Determining target device parameters for each drone in the drone cluster; the target device parameters include at least one of a device function parameter, a device communication type parameter, a device communication range parameter, a historical mission execution status, a camera viewing angle range parameter, and a flight range parameter;

[0027] Based on the target device parameters of all the drones and the execution area parameters corresponding to the subtask, the execution matching degree between each drone and the subtask is calculated, and the drone with the execution matching degree greater than or equal to the preset matching degree threshold is determined from all the drones as the target drone corresponding to the subtask.

[0028] As an optional embodiment, in the first aspect of the present invention, determining, from all the subtasks, the first to-be-adjusted subtask corresponding to the target drone that meets a preset task execution failure condition based on the task execution status of all the subtasks corresponding to the target drone, includes:

[0029] For each of the subtasks, predicting a target condition of the target drone corresponding to the subtask based on the task execution status of the target drone corresponding to the subtask; the target condition includes at least one of a communication change, a task execution quality, a task execution progress, a flight range change, and a camera viewing angle range change;

[0030] For each of the subtasks, the expected execution status of the subtask is determined, and based on the target status and the expected execution status, it is judged whether the target status matches the expected execution status. If not, the subtask is determined as the first subtask to be adjusted for the corresponding target drone to meet the preset task execution failure condition.

[0031] A second aspect of the present invention discloses a collaborative control device based on failure analysis of drone clusters, the device comprising:

[0032] A task division module is used to divide the target task to be performed by the drone cluster into multiple subtasks;

[0033] a determination module, configured to determine an execution area parameter corresponding to each of the subtasks; the execution area parameter including at least one of an execution area range parameter, an execution area type parameter, and an execution area object parameter; and for each subtask, determining a target drone corresponding to the subtask from the drone cluster based on the execution area parameter corresponding to the subtask;

[0034] A monitoring module, configured to monitor the target UAV's task execution status corresponding to the subtask;

[0035] The determining module is further configured to determine, from all the subtasks, a first to-be-adjusted subtask whose corresponding target drone meets a preset task execution failure condition based on task execution statuses of the target drones corresponding to all the subtasks, and analyze a task execution failure factor of the target drone corresponding to the first to-be-adjusted subtask;

[0036] The collaborative control module is used to perform collaborative control operations on the drone cluster according to the task execution failure factor of the target drone corresponding to the first subtask to be adjusted.

[0037] As an optional embodiment, in the second aspect of the present invention, the collaborative control module performs a collaborative control operation on the drone cluster according to the task execution failure factor of the target drone corresponding to the first subtask to be adjusted, specifically including:

[0038] Determining a task execution weight value of the first to-be-adjusted subtask based on the task content of the target task and the task content of the first to-be-adjusted subtask, and judging whether the task execution weight value is greater than or equal to a preset weight threshold;

[0039] When it is determined that the task execution weight value is greater than or equal to the weight threshold, determining a second subtask to be adjusted from all the subtasks except the first subtask to be adjusted, the second subtask to be adjusted corresponding to the target drone meets the preset task execution condition;

[0040] When the task execution failure factor of the target UAV corresponding to the first subtask to be adjusted includes a communication failure factor, the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted is obtained, and based on the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted, a collaborative control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted; the communication failure parameter includes at least one of a communication failure time parameter, a communication failure position parameter, and a communication failure type parameter.

[0041] As an optional embodiment, in the second aspect of the present invention, the collaborative control module performs a collaborative control operation on the target UAV corresponding to the second subtask to be adjusted for the first subtask to be adjusted based on the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted, specifically including:

[0042] Determining device parameters of the target UAV corresponding to the second to-be-adjusted subtask; the device parameters include at least one of device function parameters, device communication type parameters, device communication range parameters, and historical task execution status;

[0043] Determining, based on the device parameters of the target UAV corresponding to the second subtask to be adjusted and the communication failure parameters of the target UAV corresponding to the first subtask to be adjusted, a first control parameter of the target UAV corresponding to the second subtask to be adjusted for the first subtask to be adjusted; the first control parameter includes at least one of a communication control parameter, a first task execution position parameter, and a first task execution function parameter;

[0044] According to the first control parameter of the target UAV corresponding to the second subtask to be adjusted for the first subtask to be adjusted, a coordinated control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted.

[0045] As an optional embodiment, in the second aspect of the present invention, the collaborative control module performs a collaborative control operation on the drone cluster according to the task execution failure factor of the target drone corresponding to the first subtask to be adjusted, and specifically further includes:

[0046] When the task execution failure factor of the target UAV corresponding to the first to-be-adjusted subtask includes a task execution obstacle failure factor, determining a task execution obstacle parameter and a task non-execution status of the target UAV corresponding to the first to-be-adjusted subtask; the task execution obstacle parameter includes a task execution obstacle type parameter and / or a task execution obstacle location parameter;

[0047] According to the task execution obstacle parameters of the target UAV corresponding to the first subtask to be adjusted and the non-execution status of the task, a collaborative control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted.

[0048] As an optional embodiment, in the second aspect of the present invention, the collaborative control module performs a collaborative control operation on the target drone corresponding to the second subtask to be adjusted and the target drone corresponding to the first subtask to be adjusted based on the task execution obstacle parameters of the target drone corresponding to the first subtask to be adjusted and the non-execution status of the task, specifically including:

[0049] Determining, based on the task execution obstacle parameters of the target UAV corresponding to the first subtask to be adjusted, obstacle elimination control parameters for the target UAV corresponding to the second subtask to be adjusted with respect to the first subtask to be adjusted; the obstacle elimination control parameters include obstacle crossing flight path control parameters and / or obstacle elimination device function control parameters;

[0050] Determining, based on the unexecuted task of the target UAV corresponding to the first subtask to be adjusted, second control parameters for the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted for the first subtask to be adjusted; the second control parameters include a second task execution position parameter and / or a second task execution function parameter;

[0051] According to the obstacle elimination control parameters, the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted for the second control parameter of the first subtask to be adjusted, the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted are subjected to a collaborative control operation for the first subtask to be adjusted.

[0052] As an optional embodiment, in the second aspect of the present invention, the determination module determines the target drone corresponding to the subtask from the drone cluster according to the execution area parameter corresponding to the subtask, specifically including:

[0053] Determining target device parameters for each drone in the drone cluster; the target device parameters include at least one of a device function parameter, a device communication type parameter, a device communication range parameter, a historical mission execution status, a camera viewing angle range parameter, and a flight range parameter;

[0054] Based on the target device parameters of all the drones and the execution area parameters corresponding to the subtask, the execution matching degree between each drone and the subtask is calculated, and the drone with the execution matching degree greater than or equal to the preset matching degree threshold is determined from all the drones as the target drone corresponding to the subtask.

[0055] As an optional embodiment, in the second aspect of the present invention, the determination module determines, based on the task execution status of the target drones corresponding to all the subtasks, the first to-be-adjusted subtask whose corresponding target drone meets the preset task execution failure condition from all the subtasks, specifically including:

[0056] For each of the subtasks, predicting a target condition of the target drone corresponding to the subtask based on the task execution status of the target drone corresponding to the subtask; the target condition includes at least one of a communication change, a task execution quality, a task execution progress, a flight range change, and a camera viewing angle range change;

[0057] For each of the subtasks, the expected execution status of the subtask is determined, and based on the target status and the expected execution status, it is judged whether the target status matches the expected execution status. If not, the subtask is determined as the first subtask to be adjusted for the corresponding target drone to meet the preset task execution failure condition.

[0058] The third aspect of the present invention discloses another collaborative control device based on UAV cluster failure analysis, the device comprising:

[0059] a memory storing executable program code;

[0060] a processor coupled to the memory;

[0061] The processor calls the executable program code stored in the memory to execute the collaborative control method based on drone cluster failure analysis disclosed in the first aspect of the present invention.

[0062] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute the collaborative control method based on drone cluster failure analysis disclosed in the first aspect of the present invention.

[0063] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0064] In an embodiment of the present invention, based on the execution area parameters corresponding to each divided subtask, the target drone corresponding to each subtask is determined, and the task execution status of each target drone is monitored; based on the task execution status of all target drones, the first subtask to be adjusted that meets the task execution failure condition of the corresponding target drone is determined from all subtasks, and the task execution failure factor of the first subtask to be adjusted is analyzed; based on the task execution failure factor, the drone cluster is collaboratively controlled. In this way, the target drones of the subtasks can be intelligently analyzed for task execution failure, and then the drone cluster can be collaboratively controlled based on the task execution failure factor, which is conducive to timely adjustment of the task execution process, improving the control reliability and accuracy of the drone cluster, and thus helping to improve the control stability of the drone cluster. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0066] Figure 1This is a flow chart of a collaborative control method based on failure analysis of drone clusters disclosed in an embodiment of the present invention;

[0067] Figure 2 This is a flow chart of another collaborative control method based on failure analysis of drone clusters disclosed in an embodiment of the present invention;

[0068] Figure 3 1 is a schematic structural diagram of a collaborative control device based on UAV cluster failure analysis disclosed in an embodiment of the present invention;

[0069] Figure 4 This is a structural diagram of another collaborative control device based on UAV cluster failure analysis disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0070] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0071] The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different items, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or end comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed therein, or may optionally include other steps or elements inherent to such process, method, product, or end.

[0072] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0073] The present invention discloses a collaborative control method and device based on failure analysis of drone clusters, which is conducive to timely adjustment of the task execution process, improving the control reliability and accuracy of drone clusters, and thus helping to improve the control stability of drone clusters.

[0074] Example 1

[0075] See also Figure 1 , Figure 1 This is a flow chart of a collaborative control method based on failure analysis of drone clusters disclosed in an embodiment of the present invention. Figure 1 The described collaborative control method based on drone cluster failure analysis can be applied to the collaborative control of drone clusters in various scenarios, such as disaster relief scenarios, entertainment performance scenarios, etc., and the embodiments of the present invention do not limit this. Optionally, the method can be implemented by a drone collaborative control system, which can be integrated into a drone collaborative control device, or a local server or cloud server for processing the drone collaborative control process, and the embodiments of the present invention do not limit this. Figure 1 As shown, the collaborative control method based on UAV cluster failure analysis may include the following operations:

[0076] 101. Perform a task division operation on the target task to be performed by the drone cluster to obtain multiple subtasks, and determine the execution area parameters corresponding to each subtask.

[0077] In an embodiment of the present invention, optionally, the execution area parameters include at least one of an execution area range parameter, an execution area type parameter, and an execution area object parameter, wherein the execution area object parameter includes an execution area object size parameter, an execution area object position parameter, an execution area object type parameter, and the like.

[0078] 102. For each subtask, according to the execution area parameters corresponding to the subtask, determine the target drone corresponding to the subtask from the drone cluster, and monitor the task execution status of the target drone corresponding to the subtask.

[0079] In an embodiment of the present invention, the number of target drones may optionally be one or more. When there are multiple target drones, they may include at least one leader drone and at least one follower drone, or multiple drones with equal mission execution relationships. Furthermore, the mission execution status may optionally include mission execution progress, mission execution quality, mission execution obstacles, and the like.

[0080] 103. Based on the task execution status of the target UAVs corresponding to all subtasks, determine the first subtask to be adjusted from all subtasks whose corresponding target UAV meets the preset task execution failure condition, and analyze the task execution failure factor of the target UAV corresponding to the first subtask to be adjusted.

[0081] In the embodiment of the present invention, the task execution failure condition can be understood as the inability to communicate with the target UAV corresponding to the subtask, or the target UAV in the subtask encountering a poor communication signal, or the target UAV in the subtask encountering an obstacle and being unable to continue executing the corresponding task, etc. Optionally, the task execution failure factor includes a communication failure factor and / or a task execution obstacle failure factor (such as encountering a dangerous situation, being unable to fly over an obstacle, etc.).

[0082] 104. Perform a coordinated control operation on the UAV cluster based on the mission execution failure factor of the target UAV corresponding to the first subtask to be adjusted.

[0083] In an embodiment of the present invention, while collaboratively controlling the target drones corresponding to other subtasks that do not meet the preset task execution failure conditions, the target drone corresponding to the first subtask to be adjusted is controlled and adjusted to achieve collaborative control operations on the entire drone cluster.

[0084] It should be noted that, for complex cross-domain heterogeneous system information and collaborative control tasks, a distributed collaborative control framework with multiple leaders is designed and optimized. Leader failure is determined based on collaborative control errors, and the robustness of the control system is improved by updating the multi-leader (multi-leader UAV) control framework. Secondly, the stable data link of the multi-leader distributed network is used to realize local information exchange and complete the function of control information transmission. The system is quickly responded to based on the event-driven control strategy, and dynamic event trigger conditions are designed to reduce the system latency. Finally, the collaborative control problem of cross-domain heterogeneous systems in bounded interference information is studied. A distributed control algorithm based on network security is designed to reduce the impact of interference. At the same time, a detection mechanism for interfered nodes is designed based on node information and observation data. The collaborative control algorithm is optimized based on the detection mechanism to ensure the safety and reliability of system operation and realize high-precision collaborative operation of the swarm intelligence system.

[0085] It can be seen that the implementation of the embodiment of the present invention can intelligently perform task execution failure analysis on the target drone of the subtask, and then collaboratively control the drone cluster according to the task execution failure factor, which is conducive to timely adjustment of the task execution process, improving the control reliability and accuracy of the drone cluster, and thus helping to improve the control stability of the drone cluster.

[0086] In an optional embodiment, the step 104 of performing a coordinated control operation on the drone cluster according to the task execution failure factor of the target drone corresponding to the first subtask to be adjusted includes:

[0087] Determine a task execution weight value of the first subtask to be adjusted based on the task content of the target task and the task content of the first subtask to be adjusted, and determine whether the task execution weight value is greater than or equal to a preset weight threshold;

[0088] When it is determined that the task execution weight value is greater than or equal to the weight threshold, a second subtask to be adjusted is determined from all subtasks except the first subtask to be adjusted, and the corresponding target UAV meets the preset task execution condition;

[0089] When the task execution failure factor of the target UAV corresponding to the first subtask to be adjusted includes a communication failure factor, the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted is obtained, and based on the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted, a collaborative control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted.

[0090] In this optional embodiment, based on the communication failure parameters of the target UAV corresponding to the first subtask to be adjusted, and using some / all of the target UAVs corresponding to the determined second subtask to be adjusted, the first subtask to be adjusted that was originally difficult to complete is continued to be executed. Optionally, the communication failure parameters include at least one of a communication failure time parameter, a communication failure location parameter, and a communication failure type parameter. Further optionally, the task execution conditions include task execution process conditions (such as the need to complete 99% of the subtask process) and / or task execution quality conditions (such as the need for the subtask execution quality to reach good). Furthermore, when it is determined that the task execution weight value is less than the weight threshold, the target UAVs corresponding to other subtasks that do not meet the preset task execution failure conditions are collaboratively controlled to continue to complete other subtasks.

[0091] It can be seen that this optional embodiment can coordinate the target drone corresponding to the second sub-task to be adjusted that meets the preset task execution conditions when the task execution weight value of the first sub-task to be adjusted is greater than or equal to the preset weight threshold, and continue to execute the first sub-task to be adjusted based on the communication failure parameter of the first sub-task to be adjusted to achieve collaborative control operations on the drone cluster. This is conducive to improving the reliability and accuracy of the coordinated control of the drone cluster, so as to ensure the overall control stability of the drone cluster, and then to improve the execution reliability and accuracy of the target task, thereby helping to improve the timeliness of the execution of the target task.

[0092] In another optional embodiment, the above step of performing a coordinated control operation on the target UAV corresponding to the second subtask to be adjusted for the first subtask to be adjusted based on the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted includes:

[0093] Determine the equipment parameters of the target UAV corresponding to the second subtask to be adjusted;

[0094] Determining a first control parameter of the target UAV corresponding to the second task to be adjusted for the first task to be adjusted based on the device parameter of the target UAV corresponding to the second task to be adjusted and the communication failure parameter of the target UAV corresponding to the first task to be adjusted;

[0095] According to the first control parameter of the target UAV corresponding to the second subtask to be adjusted for the first subtask to be adjusted, the target UAV corresponding to the second subtask to be adjusted is subjected to a coordinated control operation for the first subtask to be adjusted.

[0096] In this optional embodiment, the device parameters optionally include at least one of a device function parameter, a device communication type parameter, a device communication range parameter, and a historical task execution status. Further optionally, the first control parameter includes at least one of a communication control parameter, a first task execution location parameter, and a first task execution function parameter. For example, if the first subtask to be adjusted cannot be executed because the distance between its target drone A and the target drone A in a certain location in the area is too far, resulting in poor signal reception, then the task location, function, etc. that the target drone B needs to perform in the first subtask to be adjusted can be determined based on the time, location, type, etc. of the communication failure, combined with the device parameters of the target drone B corresponding to the coordinated second subtask to be adjusted, thereby achieving coordinated control operations on the target drone B for the first subtask to be adjusted.

[0097] It can be seen that this optional embodiment can determine the first control parameters of the coordinated target drone corresponding to the second subtask to be adjusted for the first subtask to be adjusted based on the communication failure parameters of the target drone corresponding to the first subtask to be adjusted and the equipment parameters of the target drone corresponding to the second subtask to be adjusted, so as to perform collaborative control operations on the target drone corresponding to the second subtask to be adjusted for the first subtask to be adjusted. This is conducive to improving the reliability and accuracy of the collaborative control operations of the drones for the first subtask to be adjusted, and further conducive to improving the control stability of the drone cluster, which is conducive to the smooth progress of the overall process of the target task.

[0098] In yet another optional embodiment, the method further includes:

[0099] When the task execution failure factor of the target UAV corresponding to the first to-be-adjusted subtask includes a task execution obstacle failure factor, determining a task execution obstacle parameter and a task non-execution condition of the target UAV corresponding to the first to-be-adjusted subtask;

[0100] According to the task execution obstacle parameters and task non-execution status of the target UAV corresponding to the first subtask to be adjusted, a coordinated control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted.

[0101] In this optional embodiment, it can be understood that while the target drone corresponding to the second subtask is controlled to overcome obstacles based on the mission execution obstacle parameters of the target drone corresponding to the first subtask, the target drone corresponding to the second subtask and the target drone corresponding to the first subtask are collaboratively controlled based on the mission failure of the target drone corresponding to the first subtask, so as to continue to execute and complete the first subtask with the assistance of the target drone corresponding to the second subtask. Optionally, the mission execution obstacle parameters include a mission execution obstacle type parameter and / or a mission execution obstacle location parameter.

[0102] It can be seen that this optional embodiment can collaboratively control the target UAVs corresponding to the first subtask to be coordinated and the second subtask to be coordinated based on the task execution obstacle parameters and task non-execution status of the target UAV corresponding to the first subtask to be coordinated. In this way, the reliability and accuracy of the collaborative control of the target UAVs corresponding to the first subtask to be coordinated and the second subtask to be coordinated are improved, thereby improving the control stability of the overall target UAV, which is conducive to the smooth execution of the target task.

[0103] In yet another optional embodiment, the above steps of performing a coordinated control operation on the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted based on the task execution obstacle parameters and task non-execution status of the target UAV corresponding to the first subtask to be adjusted include:

[0104] Determining obstacle elimination control parameters for the target UAV corresponding to the second subtask to be adjusted with respect to the first subtask to be adjusted based on the task execution obstacle parameters of the target UAV corresponding to the first subtask to be adjusted;

[0105] Determining, based on the unexecuted status of the target drone corresponding to the first subtask to be adjusted, second control parameters of the target drone corresponding to the second subtask to be adjusted and the target drone corresponding to the first subtask to be adjusted for the first subtask to be adjusted;

[0106] According to the obstacle elimination control parameters, the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted for the second control parameter of the first subtask to be adjusted, the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted are subjected to collaborative control operations for the first subtask to be adjusted.

[0107] In this optional embodiment, the obstacle removal control parameters may include obstacle crossing flight path control parameters and / or obstacle removal equipment function control parameters (such as a sprinkler function, a lighting function, etc.). Further optionally, the second control parameters may include second task execution position parameters and / or second task execution function parameters. Furthermore, the obstacle removal control parameters for the target drone corresponding to the second subtask to be adjusted with respect to the first subtask to be adjusted may be determined based on the task execution obstacle parameters of the target drone corresponding to the first subtask to be adjusted, in combination with the equipment parameters of the target drone corresponding to the first subtask to be adjusted.

[0108] It can be seen that this optional embodiment can perform collaborative control of the target drones corresponding to the first subtask to be adjusted and the second subtask to be adjusted for the first subtask to be adjusted based on the obstacle elimination control parameters, the target drone corresponding to the second subtask to be adjusted, and the target drone corresponding to the first subtask to be adjusted for the first subtask to be adjusted. In this way, the reliability and accuracy of the collaborative control of drones for the first subtask to be adjusted can be improved, which is conducive to reducing the degree of impact of obstacles on the target drone during the execution of the task, thereby successfully completing the corresponding subtask that was originally difficult to continue.

[0109] Example 2

[0110] See also Figure 2 , Figure 2 This is a flow chart of another collaborative control method based on UAV cluster failure analysis disclosed in an embodiment of the present invention. Figure 2 The described collaborative control method based on drone cluster failure analysis can be applied to the collaborative control of drone clusters in various scenarios, such as disaster relief scenarios, entertainment performance scenarios, etc., and the embodiments of the present invention do not limit this. Optionally, the method can be implemented by a drone collaborative control system, which can be integrated into a drone collaborative control device, or a local server or cloud server for processing the drone collaborative control process, and the embodiments of the present invention do not limit this. Figure 2 As shown, the collaborative control method based on UAV cluster failure analysis may include the following operations:

[0111] 201. Perform a task division operation on the target task to be performed by the drone cluster to obtain multiple subtasks, and determine the execution area parameters corresponding to each subtask.

[0112] 202. For each subtask, determine the target device parameters of each drone in the drone cluster.

[0113] In an embodiment of the present invention, optionally, the target device parameters include at least one of device function parameters, device communication type parameters, device communication range parameters, historical task execution status, camera viewing angle range parameters, and flight range parameters.

[0114] 203. Calculate the execution matching degree between each UAV and the subtask based on the target device parameters of all UAVs and the execution area parameters corresponding to the subtask, and determine the UAV with an execution matching degree greater than or equal to a preset matching degree threshold from all UAVs as the target UAV corresponding to the subtask, and monitor the task execution status of the target UAV corresponding to the subtask.

[0115] In the embodiment of the present invention, optionally, the execution matching degree may be expressed in the form of a percentage or a natural number.

[0116] 204. Based on the task execution status of the target UAVs corresponding to all subtasks, determine the first subtask to be adjusted from all subtasks whose corresponding target UAV meets the preset task execution failure condition, and analyze the task execution failure factor of the target UAV corresponding to the first subtask to be adjusted.

[0117] 205. Perform a coordinated control operation on the UAV cluster according to the task execution failure factor of the target UAV corresponding to the first subtask to be adjusted.

[0118] In the embodiment of the present invention, for other descriptions of step 201, step 204 and step 205, please refer to the detailed description of step 101, step 103 and step 104 in embodiment 1, which will not be repeated in this embodiment of the present invention.

[0119] It can be seen that the implementation of the embodiment of the present invention can match the target drone corresponding to each subtask according to the target device parameters of each drone in the drone cluster, which is conducive to improving the reliability and accuracy of determining the target drone corresponding to the subtask, and further conducive to improving the feasibility of executing the subtask, thereby facilitating the overall smooth execution of the target task.

[0120] In an optional embodiment, in step 204, determining, from all subtasks, the first to-be-adjusted subtask corresponding to the target UAV that satisfies a preset task execution failure condition based on the task execution status of the target UAV corresponding to all subtasks includes:

[0121] For each subtask, predict the target status of the target UAV corresponding to the subtask based on the task execution status of the target UAV corresponding to the subtask;

[0122] For each subtask, the expected execution status of the subtask is determined, and based on the target status and the expected execution status, it is judged whether the target status matches the expected execution status. If not, the subtask is determined as the first pending subtask for the corresponding target UAV to meet the preset task execution failure condition.

[0123] In this optional embodiment, the target condition optionally includes at least one of a communication change, a mission execution quality, a mission execution progress, a flight range change, and a camera angle range change. Further optionally, the expected execution condition includes at least one of an expected communication change, an expected mission execution quality, an expected mission execution progress, an expected flight range change, and an expected camera angle range change.

[0124] It can be seen that this optional embodiment can intelligently determine whether the subtask meets the preset task execution failure condition based on the target situation of the target drone corresponding to the predicted subtask and the corresponding expected execution situation. This is conducive to timely determining the first subtask to be adjusted for task execution failure, and then conducive to timely adjusting the collaborative control operation of the drone cluster, thereby helping to improve the control stability of the drone cluster.

[0125] Example 3

[0126] See also Figure 3 , Figure 3 This is a schematic diagram of the structure of a collaborative control device based on UAV cluster failure analysis disclosed in an embodiment of the present invention. Figure 3 As shown, the collaborative control device based on UAV cluster failure analysis may include:

[0127] The task division module 301 is used to divide the target task to be performed by the UAV cluster into multiple subtasks;

[0128] Determination module 302 is used to determine the execution area parameters corresponding to each subtask; for each subtask, based on the execution area parameters corresponding to the subtask, determine the target drone corresponding to the subtask from the drone cluster;

[0129] Monitoring module 303, used to monitor the target UAV's task execution status corresponding to the subtask;

[0130] The determination module 302 is further configured to determine, from all subtasks, a first pending subtask whose corresponding target UAV meets a preset task execution failure condition based on task execution status of the target UAV corresponding to all subtasks, and analyze a task execution failure factor of the target UAV corresponding to the first pending subtask;

[0131] The collaborative control module 304 is configured to perform collaborative control operations on the UAV cluster according to the task execution failure factor of the target UAV corresponding to the first subtask to be adjusted.

[0132] In an embodiment of the present invention, the execution area parameter includes at least one of an execution area range parameter, an execution area type parameter, and an execution area object parameter.

[0133] It can be seen that implementation Figure 3 The described collaborative control device based on UAV cluster failure analysis can intelligently perform task execution failure analysis on the target UAV of the subtask, and then collaboratively control the UAV cluster according to the task execution failure factor, which is conducive to timely adjustment of the task execution process, improving the control reliability and accuracy of the UAV cluster, and thus helping to improve the control stability of the UAV cluster.

[0134] In an optional embodiment, the collaborative control module 304 performs the collaborative control operation on the drone cluster according to the task execution failure factor of the target drone corresponding to the first subtask to be adjusted, specifically including:

[0135] Determine a task execution weight value of the first subtask to be adjusted based on the task content of the target task and the task content of the first subtask to be adjusted, and determine whether the task execution weight value is greater than or equal to a preset weight threshold;

[0136] When it is determined that the task execution weight value is greater than or equal to the weight threshold, a second subtask to be adjusted is determined from all subtasks except the first subtask to be adjusted, and the corresponding target UAV meets the preset task execution condition;

[0137] When the task execution failure factor of the target UAV corresponding to the first subtask to be adjusted includes a communication failure factor, the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted is obtained, and based on the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted, a collaborative control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted.

[0138] In this optional embodiment, the communication failure parameter includes at least one of a communication failure time parameter, a communication failure location parameter, and a communication failure type parameter.

[0139] It can be seen that implementation Figure 3The described collaborative control device based on drone cluster failure analysis can coordinate the target drone corresponding to the second sub-task to be adjusted that meets the preset task execution conditions when the task execution weight value of the first sub-task to be adjusted is greater than or equal to the preset weight threshold, and continue to execute the first sub-task to be adjusted based on the communication failure parameter of the first sub-task to be adjusted to achieve collaborative control operations on the drone cluster. This is conducive to improving the reliability and accuracy of the coordinated control of the drone cluster, so as to ensure the overall control stability of the drone cluster, and further conducive to improving the execution reliability and accuracy of the target task, thereby helping to improve the timeliness of the execution of the target task.

[0140] In another optional embodiment, the collaborative control module 304 performs the collaborative control operation on the target UAV corresponding to the second subtask to be adjusted according to the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted, specifically including:

[0141] Determine the equipment parameters of the target UAV corresponding to the second subtask to be adjusted;

[0142] Determining a first control parameter of the target UAV corresponding to the second task to be adjusted for the first task to be adjusted based on the device parameter of the target UAV corresponding to the second task to be adjusted and the communication failure parameter of the target UAV corresponding to the first task to be adjusted;

[0143] According to the first control parameter of the target UAV corresponding to the second subtask to be adjusted for the first subtask to be adjusted, the target UAV corresponding to the second subtask to be adjusted is subjected to a coordinated control operation for the first subtask to be adjusted.

[0144] In this optional embodiment, the device parameters include at least one of device function parameters, device communication type parameters, device communication range parameters, and historical task execution status; the first control parameters include at least one of communication control parameters, first task execution location parameters, and first task execution function parameters.

[0145] It can be seen that implementation Figure 3 The described collaborative control device based on drone cluster failure analysis can determine the first control parameters of the coordinated target drone corresponding to the second sub-task to be adjusted for the first sub-task to be adjusted based on the communication failure parameters of the target drone corresponding to the first sub-task to be adjusted and the equipment parameters of the target drone corresponding to the second sub-task to be adjusted, thereby performing collaborative control operations on the target drone corresponding to the second sub-task to be adjusted for the first sub-task to be adjusted. This is conducive to improving the reliability and accuracy of the drone collaborative control operations for the first sub-task to be adjusted, and further conducive to improving the control stability of the drone cluster, thereby facilitating the smooth progress of the overall process of the target task.

[0146] In another optional embodiment, the collaborative control module 304 performs the collaborative control operation on the drone cluster according to the task execution failure factor of the target drone corresponding to the first subtask to be adjusted, and specifically includes:

[0147] When the task execution failure factor of the target UAV corresponding to the first to-be-adjusted subtask includes a task execution obstacle failure factor, determining a task execution obstacle parameter and a task non-execution condition of the target UAV corresponding to the first to-be-adjusted subtask;

[0148] According to the task execution obstacle parameters and task non-execution status of the target UAV corresponding to the first subtask to be adjusted, a coordinated control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted.

[0149] In this optional embodiment, the task execution obstacle parameter includes a task execution obstacle type parameter and / or a task execution obstacle location parameter.

[0150] It can be seen that implementation Figure 3 The described collaborative control device based on drone cluster failure analysis can collaboratively control the target drones corresponding to the first subtask to be coordinated and the second subtask to be coordinated according to the task execution obstacle parameters and task non-execution status of the target drone corresponding to the first subtask to be coordinated. In this way, the reliability and accuracy of the collaborative control of the target drones corresponding to the first subtask to be coordinated and the second subtask to be coordinated are improved, thereby improving the control stability of the overall target drone, which is conducive to the smooth execution of the target task.

[0151] In another optional embodiment, the collaborative control module 304 performs the collaborative control operation on the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted based on the task execution obstacle parameters and the task non-execution status of the target UAV corresponding to the first subtask to be adjusted, specifically including:

[0152] Determining obstacle elimination control parameters for the target UAV corresponding to the second subtask to be adjusted with respect to the first subtask to be adjusted based on the task execution obstacle parameters of the target UAV corresponding to the first subtask to be adjusted;

[0153] Determining, based on the unexecuted status of the target drone corresponding to the first subtask to be adjusted, second control parameters of the target drone corresponding to the second subtask to be adjusted and the target drone corresponding to the first subtask to be adjusted for the first subtask to be adjusted;

[0154] According to the obstacle elimination control parameters, the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted for the second control parameter of the first subtask to be adjusted, the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted are subjected to collaborative control operations for the first subtask to be adjusted.

[0155] In this optional embodiment, the obstacle elimination control parameters include obstacle crossing flight path control parameters and / or obstacle elimination equipment function control parameters; the second control parameters include second task execution position parameters and / or second task execution function parameters.

[0156] It can be seen that implementation Figure 3 The described collaborative control device based on drone cluster failure analysis can perform collaborative control of the target drones corresponding to the first subtask and the second subtask for the first subtask based on the obstacle elimination control parameters, the target drone corresponding to the second subtask and the target drone corresponding to the first subtask for the first subtask. In this way, the reliability and accuracy of the collaborative control of drones for the first subtask can be improved, which is conducive to reducing the degree of impact of obstacles on the target drone during the execution of the task, thereby successfully completing the corresponding subtask that was originally difficult to continue.

[0157] In another optional embodiment, the determination module 302 determines the target drone corresponding to the subtask from the drone cluster according to the execution area parameter corresponding to the subtask, specifically including:

[0158] Determine target device parameters for each drone in the drone swarm;

[0159] Based on the target device parameters of all drones and the execution area parameters corresponding to the subtask, the execution matching degree between each drone and the subtask is calculated, and the drone with an execution matching degree greater than or equal to the preset matching degree threshold is determined from all drones as the target drone corresponding to the subtask.

[0160] In this optional embodiment, the target device parameters include at least one of device function parameters, device communication type parameters, device communication range parameters, historical task execution status, camera viewing angle range parameters, and flight range parameters.

[0161] It can be seen that implementation Figure 3 The described collaborative control device based on drone cluster failure analysis can match the target drone corresponding to each subtask according to the target equipment parameters of each drone in the drone cluster, which is conducive to improving the reliability and accuracy of determining the target drone corresponding to the subtask, and then helping to improve the feasibility of executing the subtask, thereby facilitating the overall smooth execution of the target task.

[0162] In another optional embodiment, the determination module 302 determines, based on the task execution status of the target drones corresponding to all subtasks, the first to-be-adjusted subtask whose corresponding target drone meets the preset task execution failure condition from all subtasks, specifically including:

[0163] For each subtask, predict the target status of the target UAV corresponding to the subtask based on the task execution status of the target UAV corresponding to the subtask;

[0164] For each subtask, the expected execution status of the subtask is determined, and based on the target status and the expected execution status, it is judged whether the target status matches the expected execution status. If not, the subtask is determined as the first pending subtask for the corresponding target UAV to meet the preset task execution failure condition.

[0165] In this optional embodiment, the target situation includes at least one of a communication change situation, a task execution quality situation, a task execution progress situation, a flight range change situation, and a camera viewing angle range change situation.

[0166] It can be seen that implementation Figure 3 The described collaborative control device based on drone cluster failure analysis can intelligently determine whether a subtask meets the preset task execution failure condition based on the target situation of the target drone corresponding to the predicted subtask and the corresponding expected execution situation. This is conducive to timely determining the first subtask to be adjusted due to task execution failure, and then is conducive to timely adjusting the collaborative control operation of the drone cluster, thereby helping to improve the control stability of the drone cluster.

[0167] Example 4

[0168] See also Figure 4 , Figure 4 This is a structural diagram of another cooperative control device based on UAV cluster failure analysis disclosed in an embodiment of the present invention. Figure 4 As shown, the collaborative control device based on UAV cluster failure analysis may include:

[0169] A memory 401 storing executable program code;

[0170] a processor 402 coupled to the memory 401;

[0171] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the collaborative control method based on drone cluster failure analysis described in the first embodiment of the present invention or the second embodiment of the present invention.

[0172] Example 5

[0173] An embodiment of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute the steps of the collaborative control method based on drone cluster failure analysis described in Example 1 or Example 2 of the present invention.

[0174] Example 6

[0175] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the collaborative control method based on drone cluster failure analysis described in Example 1 or Example 2.

[0176] The device embodiments described above are merely illustrative, wherein the modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, i.e., they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Those skilled in the art can understand and implement the present invention without inventive effort.

[0177] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus the necessary general hardware platform, or of course, by means of hardware. Based on this understanding, the above technical solution, in essence, or the portion that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0178] Finally, it should be noted that the collaborative control method and device based on drone cluster failure analysis disclosed in the embodiment of the present invention is only a preferred embodiment of the present invention, which is only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, ordinary technicians in this field should understand that it is still possible to modify the technical solutions recorded in the aforementioned embodiments, or to make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A collaborative control method based on UAV cluster failure analysis, characterized in that: The method comprises: Performing a task division operation on the target task to be performed by the drone cluster to obtain multiple subtasks, and determining an execution area parameter corresponding to each of the subtasks; the execution area parameter includes at least one of an execution area range parameter, an execution area type parameter, and an execution area object parameter; For each of the subtasks, determining a target drone corresponding to the subtask from the drone cluster according to the execution area parameters corresponding to the subtask, and monitoring the target drone's execution of the task corresponding to the subtask; According to the task execution status of the target UAVs corresponding to all the subtasks, a first subtask to be adjusted whose corresponding target UAV meets a preset task execution failure condition is determined from all the subtasks, and a task execution failure factor of the target UAV corresponding to the first subtask to be adjusted is analyzed; Determining a task execution weight value of the first to-be-adjusted subtask based on the task content of the target task and the task content of the first to-be-adjusted subtask, and judging whether the task execution weight value is greater than or equal to a preset weight threshold; When it is determined that the task execution weight value is greater than or equal to the weight threshold, determining a second subtask to be adjusted from all the subtasks except the first subtask to be adjusted, the second subtask to be adjusted corresponding to the target drone meets the preset task execution condition; When the task execution failure factor of the target UAV corresponding to the first subtask to be adjusted includes a communication failure factor, the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted is obtained, and based on the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted, a collaborative control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted; the communication failure parameter includes at least one of a communication failure time parameter, a communication failure position parameter, and a communication failure type parameter.

2. The collaborative control method based on UAV cluster failure analysis according to claim 1 is characterized in that: The step of performing a coordinated control operation on the target UAV corresponding to the second subtask to be adjusted according to the communication failure parameter of the target UAV corresponding to the first subtask to be adjusted includes: Determining device parameters of the target UAV corresponding to the second to-be-adjusted subtask; the device parameters include at least one of device function parameters, device communication type parameters, device communication range parameters, and historical task execution status; Determining, based on the device parameters of the target UAV corresponding to the second subtask to be adjusted and the communication failure parameters of the target UAV corresponding to the first subtask to be adjusted, a first control parameter of the target UAV corresponding to the second subtask to be adjusted for the first subtask to be adjusted; the first control parameter includes at least one of a communication control parameter, a first task execution position parameter, and a first task execution function parameter; According to the first control parameter of the target UAV corresponding to the second subtask to be adjusted for the first subtask to be adjusted, a coordinated control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted.

3. The collaborative control method based on UAV cluster failure analysis according to claim 1 is characterized in that: The method further comprises: When the task execution failure factor of the target UAV corresponding to the first to-be-adjusted subtask includes a task execution obstacle failure factor, determining a task execution obstacle parameter and a task non-execution status of the target UAV corresponding to the first to-be-adjusted subtask; the task execution obstacle parameter includes a task execution obstacle type parameter and / or a task execution obstacle location parameter; According to the task execution obstacle parameters of the target UAV corresponding to the first subtask to be adjusted and the non-execution status of the task, a collaborative control operation for the first subtask to be adjusted is performed on the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted.

4. The collaborative control method based on UAV cluster failure analysis according to claim 3 is characterized in that: The step of performing a coordinated control operation on the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted according to the task execution obstacle parameter of the target UAV corresponding to the first subtask to be adjusted and the task non-execution status includes: Determining, based on the task execution obstacle parameters of the target UAV corresponding to the first subtask to be adjusted, obstacle elimination control parameters for the target UAV corresponding to the second subtask to be adjusted with respect to the first subtask to be adjusted; the obstacle elimination control parameters include obstacle crossing flight path control parameters and / or obstacle elimination device function control parameters; Determining, based on the unexecuted task of the target UAV corresponding to the first subtask to be adjusted, second control parameters for the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted for the first subtask to be adjusted; the second control parameters include a second task execution position parameter and / or a second task execution function parameter; According to the obstacle elimination control parameters, the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted for the second control parameter of the first subtask to be adjusted, the target UAV corresponding to the second subtask to be adjusted and the target UAV corresponding to the first subtask to be adjusted are subjected to a collaborative control operation for the first subtask to be adjusted.

5. The collaborative control method based on UAV cluster failure analysis according to any one of claims 1 to 4, characterized in that: The determining, from the drone cluster, a target drone corresponding to the subtask based on the execution area parameter corresponding to the subtask includes: Determining target device parameters for each drone in the drone cluster; the target device parameters include at least one of a device function parameter, a device communication type parameter, a device communication range parameter, a historical mission execution status, a camera viewing angle range parameter, and a flight range parameter; Based on the target device parameters of all the drones and the execution area parameters corresponding to the subtask, the execution matching degree between each drone and the subtask is calculated, and the drone with the execution matching degree greater than or equal to the preset matching degree threshold is determined from all the drones as the target drone corresponding to the subtask.

6. The collaborative control method based on UAV cluster failure analysis according to claim 5 is characterized in that: The step of determining, based on the task execution status of the target UAVs corresponding to all the subtasks, a first subtask to be adjusted whose corresponding target UAV meets a preset task execution failure condition from all the subtasks includes: For each of the subtasks, predicting a target condition of the target drone corresponding to the subtask based on the task execution status of the target drone corresponding to the subtask; the target condition includes at least one of a communication change, a task execution quality, a task execution progress, a flight range change, and a camera viewing angle range change; For each of the subtasks, the expected execution status of the subtask is determined, and based on the target status and the expected execution status, it is judged whether the target status matches the expected execution status. If not, the subtask is determined as the first subtask to be adjusted for the corresponding target drone to meet the preset task execution failure condition.

7. A collaborative control device based on UAV cluster failure analysis, characterized in that: The device is used to execute the collaborative control method based on UAV cluster failure analysis according to any one of claims 1 to 6, and the device includes: A task division module is used to divide the target task to be performed by the drone cluster into multiple subtasks; a determination module, configured to determine an execution area parameter corresponding to each of the subtasks; the execution area parameter including at least one of an execution area range parameter, an execution area type parameter, and an execution area object parameter; and for each subtask, determining a target drone corresponding to the subtask from the drone cluster based on the execution area parameter corresponding to the subtask; A monitoring module, configured to monitor the target UAV's task execution status corresponding to the subtask; The determining module is further configured to determine, from all the subtasks, a first to-be-adjusted subtask whose corresponding target drone meets a preset task execution failure condition based on task execution statuses of the target drones corresponding to all the subtasks, and analyze a task execution failure factor of the target drone corresponding to the first to-be-adjusted subtask; The collaborative control module is used to perform collaborative control operations on the drone cluster according to the task execution failure factor of the target drone corresponding to the first subtask to be adjusted.

8. A collaborative control device based on UAV cluster failure analysis, characterized in that: The device comprises: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the collaborative control method based on drone cluster failure analysis as described in any one of claims 1 to 6.

9. A computer storage medium, characterized in that The computer storage medium stores computer instructions, which, when called, are used to execute the collaborative control method based on drone cluster failure analysis as described in any one of claims 1 to 6.

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