CN116449865A - Cluster task decomposition method and system for clustered unmanned aerial vehicle based on state awareness - Google Patents
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Abstract
The invention discloses a clustered unmanned aerial vehicle cluster task decomposition method and system based on state perception, wherein the system comprises an application task issuing module, a clustered state perception module, a clustered task decomposition module and a decomposed task issuing module; the application task issuing module is used for receiving the application task by the ground control power station, preferentially selecting a matched unmanned aerial vehicle cluster for executing the application task, and sending the application task to the cluster head unmanned aerial vehicle of the matched unmanned aerial vehicle cluster; the cluster state sensing module is used for acquiring running state information of a cluster matched with the unmanned aerial vehicle by the cluster head unmanned aerial vehicle; the cluster task decomposition module is used for decomposing the application task according to the running state of the matched unmanned aerial vehicle cluster by the cluster head unmanned aerial vehicle; the decomposing task issuing module is used for sending the decomposed task to each unmanned aerial vehicle in the matched unmanned aerial vehicle cluster; the method is a control method based on the system; the invention has the advantages of good environmental adaptability and high success rate of task execution.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to a clustered unmanned aerial vehicle cluster task decomposition method and system based on state perception.
Background
Through the task planning in advance, a plurality of heterogeneous unmanned aerial vehicles can form an unmanned aerial vehicle cluster, communication and coordination are carried out among the unmanned aerial vehicles through an unmanned aerial vehicle network, various given tasks are completed in a cooperative mode, including area sensing, target tracking, disaster assessment, relay communication and the like, and the clustered unmanned aerial vehicle cluster is generally provided with a cluster head unmanned aerial vehicle, so that actions of the unmanned aerial vehicles are coordinated better, and task completion efficiency is improved; however, the tasks to be completed by the unmanned aerial vehicle clusters often change dynamically, the environment in which the tasks are executed is also changed continuously, and in particular, factors such as dynamic electromagnetic interference can cause the air link on which the unmanned aerial vehicle network depends to be interrupted, so that part of unmanned aerial vehicles cannot participate in a given task.
At present, the industry has developed some work in the aspect of optimization scheduling related to unmanned aerial vehicle clusters, for example, the application of the invention with the application number of 201811436625.7 is a data sharing-oriented multi-unmanned aerial vehicle collaborative map construction method, and the data sharing-oriented multi-unmanned aerial vehicle collaborative map construction method is provided to solve the problems of long time consumption and slow return of an optimized map in a map fusion process; the Chinese patent application No. 202110828150.1 discloses a multi-unmanned aerial vehicle distributed control system, a cooperative control method, a medium and an unmanned aerial vehicle formation, and designs the multi-unmanned aerial vehicle distributed control system and the cooperative control method so as to improve the task execution efficiency of the multi-unmanned aerial vehicle system; the Chinese patent application No. 202111151028.1 authorizes a digital twinning-based cluster collaborative search virtual-real combination verification method to improve the simulation reliability; the Chinese patent application No. 202111346648.0 grants "a heterogeneous task-oriented unmanned aerial vehicle cluster collaborative target selection method" to improve the efficiency of the unmanned aerial vehicle cluster system for simultaneously completing a plurality of tasks; the Chinese patent application No. 202210065422.1 grants a digital twinning-based unmanned aerial vehicle cluster track optimization and task unloading method to reduce the energy consumption of the whole system; the Chinese patent application No. 202210146501.5 grants an unmanned aerial vehicle cluster collaborative reconnaissance coverage distributed autonomous optimization method to obtain virtual benefits to drive autonomous decisions of unmanned aerial vehicle actions, so that the stability and flexibility of the unmanned aerial vehicle cluster are improved.
However, none of the existing solutions focuses on the problem of task decomposition in the event of a link outage in the network part of the drone, nor how the ground control station selects the appropriate cluster from a plurality of available drone clusters to perform a given application task.
Therefore, how to provide a clustered unmanned aerial vehicle cluster task decomposition method and system based on state perception, which efficiently utilizes available unmanned aerial vehicle cluster resources in a dynamic environment to complete tasks dynamically issued by a ground control station is a problem to be solved by those skilled in the art.
Disclosure of Invention
In view of the above, the present invention provides a clustered unmanned aerial vehicle cluster task decomposition method and system based on state awareness, so as to solve the problems mentioned in the background art.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a clustered unmanned aerial vehicle cluster task decomposition system based on state perception comprises an application task issuing module, a clustered state perception module, a clustered task decomposition module and a decomposition task issuing module;
the application task issuing module is used for receiving the application task by the ground control power station, preferentially selecting a matched unmanned aerial vehicle cluster for executing the application task, and sending the application task to the cluster head unmanned aerial vehicle of the matched unmanned aerial vehicle cluster;
the cluster state sensing module is used for acquiring running state information of a cluster matched with the unmanned aerial vehicle by the cluster head unmanned aerial vehicle;
the cluster task decomposition module is used for decomposing the application task according to the running state of the matched unmanned aerial vehicle cluster by the cluster head unmanned aerial vehicle;
and the decomposed task issuing module is used for sending the decomposed task to each unmanned aerial vehicle in the matched unmanned aerial vehicle cluster.
Preferably, the application task issuing module comprises an application task input unit, an execution cluster selection unit and a task data transmission unit,
the ground control station is used for receiving the application task input;
the execution cluster selection unit is used for the ground control station to preferentially select unmanned aerial vehicle clusters for executing the application tasks based on the capability matching degree according to the received attribute of the application tasks;
the task data transmission unit is used for transmitting the application task execution instruction and data to the cluster head unmanned aerial vehicle matched with the unmanned aerial vehicle cluster through the ground air link by the ground control station.
Preferably, the attributes of the application task include a task target area and task capability requirements.
Preferably, the execution cluster selection unit comprises a capability matching degree calculation subunit, a task target area matching subunit and a cluster matching subunit;
the capability matching degree calculating subunit is used for calculating the capability matching degree of each unmanned aerial vehicle cluster and the application task;
the task target area matching subunit is used for calculating the matching degree of each unmanned aerial vehicle cluster and the task target area of the application task;
the cluster matching subunit is used for selecting the unmanned aerial vehicle cluster with the maximum capability matching degree as a potential unmanned aerial vehicle cluster for executing the application task according to the capability matching degree vector; if a plurality of potential unmanned aerial vehicle clusters exist, selecting the unmanned aerial vehicle cluster with the largest target area matching degree according to the target area matching degree vector as the potential unmanned aerial vehicle cluster, and if the plurality of potential unmanned aerial vehicle clusters exist, randomly selecting 1 matching unmanned aerial vehicle clusters for executing application tasks.
Preferably, the cluster state sensing module comprises an operation information collecting unit and a cluster state converging unit;
the running information collection unit is used for collecting running state information of each unmanned aerial vehicle in the matched unmanned aerial vehicle cluster by the cluster head unmanned aerial vehicle;
and the cluster state aggregation unit is used for forming an available unmanned aerial vehicle list and a corresponding available resource list according to the running state information of each unmanned aerial vehicle.
Preferably, the running state information is information related to execution of application tasks by each unmanned aerial vehicle matched with the unmanned aerial vehicle cluster, and the running state information comprises position information, load information and bandwidth information.
Preferably, the cluster task decomposition module comprises a resource-aware task decomposition unit, an execution unit allocation unit and a deployment update calculation unit;
the resource perception task decomposition unit is used for dividing the application task into different execution units according to the available resource list and the application task by the cluster head unmanned aerial vehicle;
the execution unit distribution unit is used for distributing the execution unit to unmanned aerial vehicles in the available unmanned aerial vehicle list according to the minimum execution time or the minimum execution energy consumption or other principles by the cluster head unmanned aerial vehicle;
the deployment updating calculation unit is used for calculating a new deployment position of each unmanned aerial vehicle according to the distribution result of the execution unit.
Preferably, the decomposition task issuing module comprises a dependency relation calculating unit and an allocation instruction transmitting unit;
the dependency relation calculating unit is used for calculating the data dependency relation among the unmanned aerial vehicles in the cluster according to the distribution result of the executing unit by the unmanned aerial vehicle in the cluster;
the allocation instruction transmission unit is used for the cluster head unmanned aerial vehicle to transmit the application task data, the allocation result of the execution unit, the data dependency relationship and the new deployment position of the unmanned aerial vehicle to all the unmanned aerial vehicles in the cluster of the available unmanned aerial vehicle list.
A clustering unmanned aerial vehicle cluster task decomposition method based on state perception comprises the following steps:
s1, receiving an application task, and preferentially selecting a matched unmanned aerial vehicle cluster for executing the application task based on the capability matching degree according to the attribute of the received application task;
s2, sending the application task to a cluster head unmanned aerial vehicle matched with the unmanned aerial vehicle cluster;
s3, the cluster head unmanned aerial vehicle acquires running state information of a matched unmanned aerial vehicle cluster;
s4, the cluster head unmanned aerial vehicle decomposes the application task according to the running state of the matched unmanned aerial vehicle cluster;
s5, sending the decomposed tasks to all unmanned aerial vehicles in the matched unmanned aerial vehicle cluster.
Compared with the prior art, the invention discloses a clustered unmanned aerial vehicle cluster task decomposition method and system based on state perception, wherein a ground control station can select a proper cluster from a plurality of available unmanned aerial vehicle clusters to execute a given application task; the unmanned aerial vehicle cluster operation state sensing is dynamically carried out, so that the unmanned aerial vehicle cluster can be better adapted to the dynamically-changed operation environment; through state sensing, task decomposition can be performed only based on the existing available resources, task execution failure caused by factors such as link interruption is avoided, and task execution success rate is remarkably improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a clustered unmanned aerial vehicle cluster task decomposition system provided by the invention;
FIG. 2 is a schematic diagram of an application task issuing module according to the present invention;
fig. 3 is a schematic diagram of a typical network scenario in which a ground control station controls N unmanned aerial vehicle clusters according to the present invention;
FIG. 4 is a diagram illustrating an application task G according to an embodiment of the present invention 1 Schematic of (2);
FIG. 5 is a schematic diagram of an execution cluster selection unit according to the present invention;
FIG. 6 is a schematic flow chart of a capability matching degree calculation subunit provided by the invention;
FIG. 7 is a schematic flow chart of a task target area matching subunit provided by the present invention;
FIG. 8 is a schematic diagram of a cluster state aware module according to the present invention;
FIG. 9 is a schematic diagram of a list of available unmanned aerial vehicles according to an embodiment of the present invention;
FIG. 10 is a schematic diagram of a cluster task decomposition module structure provided by the present invention;
FIG. 11 is a diagram illustrating an application task G according to an embodiment of the present invention 1 A schematic diagram of the execution unit division result;
fig. 12 is a schematic diagram of an exploded task issuing module according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment of the invention discloses a clustered unmanned aerial vehicle cluster task decomposition system based on state perception, as shown in figure 1, comprising an application task issuing module, a clustered state perception module, a clustered task decomposition module and a decomposed task issuing module;
the application task issuing module is used for receiving the application task by the ground control power station, preferentially selecting a matched unmanned aerial vehicle cluster for executing the application task, and sending the application task to the cluster head unmanned aerial vehicle of the matched unmanned aerial vehicle cluster;
the cluster state sensing module is used for acquiring running state information of a cluster matched with the unmanned aerial vehicle by the cluster head unmanned aerial vehicle;
the cluster task decomposition module is used for decomposing the application task according to the running state of the matched unmanned aerial vehicle cluster by the cluster head unmanned aerial vehicle;
and the decomposed task issuing module is used for sending the decomposed task to each unmanned aerial vehicle in the matched unmanned aerial vehicle cluster.
In order to further implement the above technical solution, as shown in fig. 2, the application task assigning module includes an application task input unit, an execution cluster selection unit and a task data transmission unit,
the ground control station is used for receiving application task input from a user through man-machine interaction;
the ground control station can simultaneously control at least one unmanned aerial vehicle cluster, at least one ground-air link exists between the ground control station and each unmanned aerial vehicle cluster, and is used for transmitting control instructions and data of application tasks, as shown in a typical network scene in fig. 3, wherein the ground control station simultaneously controls N unmanned aerial vehicle clusters through the ground-air link, and N is more than or equal to 1;
the application tasks comprise various types, such as target searching, communication relay, region investigation and the like;
each application task is represented in the form of a directed acyclic graph, which contains a plurality of interrelated sub-tasks, FIG. 4, an application task G 1 Comprising 6 subtasks, i.e. v 1 -v 6 Subtask v 1 Corresponding image perception, v 2 Corresponding image analysis, v 3 Corresponding to the feature perception of the ground object, v 5 Corresponding feature recognition, v 4 Mapping corresponding to target position, v 6 Constructing and fusing corresponding maps;
the execution cluster selection unit is used for the ground control station to preferentially select unmanned aerial vehicle clusters for executing the application tasks based on the capability matching degree according to the received attribute of the application tasks;
the task data transmission unit is used for transmitting the application task execution instruction and data to the cluster head unmanned aerial vehicle matched with the unmanned aerial vehicle cluster through the ground air link by the ground control station.
In order to further implement the above technical solution, the attributes of the application task include a task target area and task capability requirements.
The task target area is a geographical area where the application task is executed, for example, for a given investigation task, a given investigation geographical area is generally required;
the task capability requirement is the capability required by executing the application task, for example, the capability of image sensing and analysis, electromagnetic signal interception and analysis, ground feature sensing and identification, map construction and fusion and the like are generally required by executing the investigation task, so that M capability requirements are required by the application task;
task capabilities are typically associated with one or more subtasks in an application task.
In order to further implement the above technical solution, as shown in fig. 5, the execution cluster selection unit includes a capability matching degree calculation subunit, a task target area matching subunit, and a cluster matching subunit;
the capability matching degree calculating subunit is configured to calculate a capability matching degree between each unmanned aerial vehicle cluster and an application task, where the capability matching degree of the kth unmanned aerial vehicle cluster is denoted as f k Capability matching is a certain capability required by an unmanned aerial vehicle, and when the application task requires p-term capabilities and an ith unmanned aerial vehicle (i is less than or equal to N) has q-term capabilities therein (q is less than or equal to p), the capability matching degree is recorded as q, namely f i =q; the capability matching degree vector of all N unmanned aerial vehicle clusters is denoted as f= [ F 1 ,f 2 ,…,f N ]As in fig. 6;
a task target area matching subunit, configured to calculate a matching degree between each unmanned aerial vehicle cluster and a task target area of an application task, where the matching degree of the target area of the kth unmanned aerial vehicle cluster is denoted as a k Calculating the area of an overlapping area of the coverage area of the current unmanned aerial vehicle cluster and the target area of the application task, and taking the calculation result as the matching degree of the target area of the current unmanned aerial vehicle cluster, a k ＝S{A k ∪A t }/S{A k And }, where ∈denotes intersection, S {.cndot } represents the area of the fetch region, target area matching degree vectors of all N unmanned aerial vehicle clusters are expressed as A= [ a ] 1 ,a 2 ,…,a N ]As in fig. 7;
the cluster matching subunit is used for selecting the unmanned aerial vehicle cluster with the maximum capability matching degree as a potential unmanned aerial vehicle cluster for executing the application task according to the capability matching degree vector; if a plurality of potential unmanned aerial vehicle clusters exist, selecting the unmanned aerial vehicle cluster with the largest target area matching degree according to the target area matching degree vector as the potential unmanned aerial vehicle cluster, and if the plurality of potential unmanned aerial vehicle clusters exist, randomly selecting 1 matching unmanned aerial vehicle clusters for executing application tasks.
In order to further implement the above technical solution, the cluster state sensing module includes an operation information collecting unit and a cluster state converging unit, as shown in fig. 8;
the running information collection unit is used for collecting running state information of each unmanned aerial vehicle in the matched unmanned aerial vehicle cluster by the cluster head unmanned aerial vehicle;
and the cluster state aggregation unit is used for forming an available unmanned aerial vehicle list and a corresponding available resource list according to the running state information of each unmanned aerial vehicle.
In order to further implement the technical scheme, the running state information is information related to execution of application tasks by each unmanned aerial vehicle matched with the unmanned aerial vehicle cluster, and comprises position information, load information and bandwidth information;
the position information is the current position of the unmanned plane;
the load information is information of various application tasks operated by the unmanned aerial vehicle;
the bandwidth information is transmission bandwidth information between the unmanned aerial vehicle and other unmanned aerial vehicles in the cluster.
The available unmanned aerial vehicle list is an unmanned aerial vehicle set which successfully transmits the running state information to the cluster head unmanned aerial vehicle; the available resource list comprises the resources available on each unmanned plane such as perception, calculation, transmission and the like;
the unmanned aerial vehicle in the cluster which is out of contact with the unmanned aerial vehicle of the cluster head due to the factors of equipment failure, electromagnetic interference, propagation environment and the like will not be contained in the unmanned aerial vehicle set, as shown in fig. 9, the unmanned aerial vehicle cluster 1 contains 5 unmanned aerial vehicles, namely U 1 、U 2 、U 3 、U 4 、U 5 ，U 1 Unmanned aerial vehicle U capable of transmitting operation information to cluster head due to air-air link interruption 5 ，U 2 Due to itselfFailure does not transmit operation information to cluster head unmanned aerial vehicle U 5 Therefore when the cluster becomes a matching unmanned aerial vehicle cluster, the cluster head unmanned aerial vehicle U 5 The list of available drones screened will contain only U 3 、U 4 And U 5 A total of 3 unmanned aerial vehicles.
In order to further implement the above technical solution, the cluster task decomposition module includes a resource-aware task decomposition unit, an execution unit allocation unit, and a deployment update calculation unit, as shown in fig. 10;
the resource perception task decomposition unit is used for dividing the application task into different execution units according to the available resource list and the application task by the cluster head unmanned aerial vehicle;
the execution unit comprises at least 1 subtask of application tasks;
as in FIG. 11, task G is applied 1 Is divided into 3 execution units, the execution unit 1 contains v 1 And v 2 The two subtasks, execution unit 2, contain v 3 And v 5 Two subtasks and corresponding subtask v of execution unit 3 4 And v 6 ；
The execution unit allocation unit is used for allocating the execution unit to unmanned aerial vehicles in the available unmanned aerial vehicle list by using a greedy algorithm, a genetic algorithm and other scheduling methods according to the minimum execution time or the minimum execution energy consumption or other principles;
the minimum execution time principle is that after an execution unit is distributed to unmanned aerial vehicles in the available unmanned aerial vehicle list, the minimum execution time of an application task can be obtained;
the minimum execution energy consumption principle is that after an execution unit is distributed to unmanned aerial vehicles in the available unmanned aerial vehicle list, the minimum application task execution energy consumption can be obtained;
the deployment updating calculation unit is used for calculating a new deployment position of each unmanned aerial vehicle according to the distribution result of the execution unit.
In order to further implement the above technical solution, the decomposition task issuing module includes a dependency relation calculating unit and an allocation instruction transmitting unit, as shown in fig. 12;
the dependency relation calculating unit is used for calculating the data dependency relation among the unmanned aerial vehicles in the cluster according to the distribution result of the executing unit by the unmanned aerial vehicle in the cluster;
the allocation instruction transmission unit is used for the cluster head unmanned aerial vehicle to transmit the application task data, the allocation result of the execution unit, the data dependency relationship and the new deployment position of the unmanned aerial vehicle to all the unmanned aerial vehicles in the cluster of the available unmanned aerial vehicle list.
A clustering unmanned aerial vehicle cluster task decomposition method based on state perception comprises the following steps:
s1, receiving an application task, and preferentially selecting a matched unmanned aerial vehicle cluster for executing the application task based on the capability matching degree according to the attribute of the received application task;
s2, sending the application task to a cluster head unmanned aerial vehicle matched with the unmanned aerial vehicle cluster;
s3, the cluster head unmanned aerial vehicle acquires running state information of a matched unmanned aerial vehicle cluster;
s4, the cluster head unmanned aerial vehicle decomposes the application task according to the running state of the matched unmanned aerial vehicle cluster;
s5, sending the decomposed tasks to all unmanned aerial vehicles in the matched unmanned aerial vehicle cluster.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. The clustered unmanned aerial vehicle cluster task decomposition system based on state perception is characterized by comprising an application task issuing module, a clustered state perception module, a clustered task decomposition module and a decomposition task issuing module;
the application task issuing module is used for receiving the application task by the ground control power station, preferentially selecting a matched unmanned aerial vehicle cluster for executing the application task, and sending the application task to the cluster head unmanned aerial vehicle of the matched unmanned aerial vehicle cluster;
the cluster state sensing module is used for acquiring running state information of a cluster of the matched unmanned aerial vehicle, and an available unmanned aerial vehicle list and a corresponding available resource list by the cluster head unmanned aerial vehicle;
the cluster task decomposition module is used for decomposing the application task according to the running state of the matched unmanned aerial vehicle cluster by the cluster head unmanned aerial vehicle;
and the decomposed task issuing module is used for sending the decomposed task to each unmanned aerial vehicle in the matched unmanned aerial vehicle cluster.
2. The clustered unmanned aerial vehicle cluster task decomposition system based on state awareness according to claim 1, wherein the application task issuing module comprises an application task input unit, an execution cluster selection unit and a task data transmission unit,
the ground control station is used for receiving the application task input;
the execution cluster selection unit is used for the ground control station to preferentially select unmanned aerial vehicle clusters for executing the application tasks based on the capability matching degree according to the received attribute of the application tasks;
and the task data transmission unit is used for transmitting the application task execution instruction and data to the cluster head unmanned aerial vehicle matched with the unmanned aerial vehicle cluster by the ground control station.
3. The clustered unmanned aerial vehicle cluster task decomposition system based on state awareness of claim 2, wherein the attributes of the application task include task target area and task capability requirements.
4. A clustered unmanned aerial vehicle cluster task decomposition system based on state awareness according to claim 3, wherein the execution cluster selection unit comprises a capability matching degree calculation subunit, a task target area matching subunit and a cluster matching subunit;
the capability matching degree calculating subunit is used for calculating the capability matching degree of each unmanned aerial vehicle cluster and the application task;
the task target area matching subunit is used for calculating the matching degree of each unmanned aerial vehicle cluster and the task target area of the application task;
the cluster matching subunit is used for selecting the unmanned aerial vehicle cluster with the maximum capability matching degree as a potential unmanned aerial vehicle cluster for executing the application task according to the capability matching degree vector; if a plurality of potential unmanned aerial vehicle clusters exist, selecting the unmanned aerial vehicle cluster with the largest target area matching degree according to the target area matching degree vector as the potential unmanned aerial vehicle cluster, and if the plurality of potential unmanned aerial vehicle clusters exist, randomly selecting 1 matching unmanned aerial vehicle clusters for executing application tasks.
5. The clustered unmanned aerial vehicle cluster task decomposition system based on state awareness according to claim 1, wherein the cluster state awareness module comprises an operation information collection unit and a cluster state aggregation unit;
the running information collection unit is used for collecting running state information of each unmanned aerial vehicle in the matched unmanned aerial vehicle cluster by the cluster head unmanned aerial vehicle;
and the cluster state aggregation unit is used for forming an available unmanned aerial vehicle list and a corresponding available resource list according to the running state information of each unmanned aerial vehicle.
6. The clustered unmanned aerial vehicle cluster task decomposition system based on state awareness of claim 5, wherein the running state information is information associated with executing application tasks by each unmanned aerial vehicle matching the unmanned aerial vehicle cluster, and includes location information, load information and bandwidth information.
7. The clustered unmanned aerial vehicle cluster task decomposition system based on state awareness according to claim 1, wherein the cluster task decomposition module comprises a resource aware task decomposition unit, an execution unit allocation unit and a deployment update calculation unit;
the resource perception task decomposition unit is used for dividing the application task into different execution units according to the available resource list and the application task by the cluster head unmanned aerial vehicle;
the execution unit distribution unit is used for distributing the execution unit to unmanned aerial vehicles in the available unmanned aerial vehicle list according to the minimum execution time or the minimum execution energy consumption or other principles by the cluster head unmanned aerial vehicle;
the deployment updating calculation unit is used for calculating a new deployment position of each unmanned aerial vehicle according to the distribution result of the execution unit.
8. The clustered unmanned aerial vehicle cluster task decomposition system based on state awareness according to claim 1, wherein the decomposition task issuing module comprises a dependency relation calculating unit and an allocation instruction transmission unit;
the dependency relation calculating unit is used for calculating the data dependency relation among the unmanned aerial vehicles in the cluster according to the distribution result of the executing unit by the unmanned aerial vehicle in the cluster;
the allocation instruction transmission unit is used for the cluster head unmanned aerial vehicle to transmit the application task data, the allocation result of the execution unit, the data dependency relationship and the new deployment position of the unmanned aerial vehicle to all the unmanned aerial vehicles in the cluster of the available unmanned aerial vehicle list.
9. A clustered unmanned aerial vehicle cluster task decomposition method based on state perception, based on the clustered unmanned aerial vehicle cluster task decomposition system based on state perception as claimed in any one of claims 1-8, characterized by comprising the following steps:
s1, receiving an application task, and preferentially selecting a matched unmanned aerial vehicle cluster for executing the application task based on the capability matching degree according to the attribute of the received application task;
s2, sending the application task to a cluster head unmanned aerial vehicle matched with the unmanned aerial vehicle cluster;
s3, the cluster head unmanned aerial vehicle acquires running state information of a matched unmanned aerial vehicle cluster;
s4, the cluster head unmanned aerial vehicle decomposes the application task according to the running state of the matched unmanned aerial vehicle cluster;
s5, sending the decomposed tasks to all unmanned aerial vehicles in the matched unmanned aerial vehicle cluster.
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