CN113885554B - Distributed round-up control method and system for unmanned aerial vehicle swarm - Google Patents
Distributed round-up control method and system for unmanned aerial vehicle swarm Download PDFInfo
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Abstract
本发明涉及无人机技术领域，具体涉及一种无人机集群的分布式围捕控制方法及系统，所述方法包括：群体中的无人机进行目标检测，获取该无人机与每个目标的距离、以及对每个目标进行围捕的无人机的数量，以确定该无人机的围捕目标；将对该无人机的围捕目标进行围捕的无人机作为无人机群，所述无人机根据该无人机与群体中其他无人机之间的距离、该无人机与每个目标的距离、该无人机与障碍物之间的距离、该无人机与场地边界之间的距离、该无人机与围捕目标之间的距离、以及该无人机群的期望包围圈半径确定该无人机的控制速度，并按照该控制速度飞行，以对围捕目标进行围捕，本发明能够自主、安全性高的对目标进行分布式围捕。
The present invention relates to the technical field of unmanned aerial vehicles, in particular to a method and system for distributed round-up control of UAV clusters. The method includes: UAVs in the group perform target detection, obtain the distance between the UAV and each target, and the number of UAVs that round up each target, so as to determine the round-up target of the UAV; use the UAV that rounds up the UAV's round-up target as a UAV group, and the UAV is based on the distance between the UAV and other UAVs in the group, the distance between the UAV and each target, the distance between the UAV and obstacles, the distance between the UAV and the field boundary, and the distance between the UAV and the UAV. The distance between the rounded-up targets and the expected encirclement radius of the UAV group determine the control speed of the UAV, and fly according to the control speed to round up the rounded-up targets. The present invention can perform distributed round-up of the targets autonomously and with high security.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to a distributed capture control method and system for an unmanned aerial vehicle cluster.
Background
Unmanned aerial vehicle cluster flight becomes more and more a hot spot for research in various fields at present, such as police unmanned aerial vehicle cluster investigation, post-disaster rescue, light show and the like. The unmanned aerial vehicle has the characteristics of small size, high safety, low manufacturing cost and the like, and the advantages of the unmanned aerial vehicle for executing the tasks in an autonomous cluster flight are increasingly displayed. The unmanned aerial vehicle autonomous cluster trapping refers to that the unmanned aerial vehicle clusters fly in the air in a group state, and the group cooperation execution surrounds the task, so that the unmanned aerial vehicle autonomous cluster trapping is an important application of the unmanned aerial vehicle autonomous cluster flight execution task.
In the prior art, mostly, manual control unmanned aerial vehicles are adopted to complete flight tasks, namely, unmanned aerial vehicle clusters receive instructions of a ground workbench in real time, tasks are executed according to the instructions, and a central control node exists. The unmanned aerial vehicle clusters are used for capturing targets under the control of the central node, namely, the behaviors of the unmanned aerial vehicles are controlled by the ground workbench, and the unmanned aerial vehicles do not have the function of capturing the unmanned aerial vehicles independently.
Disclosure of Invention
The invention aims to provide a distributed trapping control method and system for an unmanned aerial vehicle cluster, which have an autonomous cluster trapping function, so as to solve one or more technical problems in the prior art and at least provide a beneficial selection or creation condition.
In order to achieve the above object, the present invention provides the following technical solutions:
a distributed enclosure control method for an unmanned aerial vehicle cluster, the method comprising the steps of:
step S100, target detection is carried out on unmanned aerial vehicles in a group, and the distance between the unmanned aerial vehicle and each target and the number of unmanned aerial vehicles for capturing each target are obtained;
step 200, the unmanned aerial vehicle determines a trapping target of the unmanned aerial vehicle according to the distance between the unmanned aerial vehicle and each target and the number of unmanned aerial vehicles trapping each target;
step S300, taking a plurality of unmanned aerial vehicles for capturing the capturing target of the unmanned aerial vehicle as an unmanned aerial vehicle group, and acquiring the distance between the unmanned aerial vehicle and other unmanned aerial vehicles in the group, the distance between the unmanned aerial vehicle and each target, the distance between the unmanned aerial vehicle and an obstacle, the distance between the unmanned aerial vehicle and the field boundary, the distance between the unmanned aerial vehicle and the capturing target and the expected radius of the surrounding ring of the unmanned aerial vehicle group;
step S400, the unmanned aerial vehicle determines the control speed of the unmanned aerial vehicle at the current moment according to the distance between the unmanned aerial vehicle and other unmanned aerial vehicles in the group, the distance between the unmanned aerial vehicle and each target, the distance between the unmanned aerial vehicle and the obstacle, the distance between the unmanned aerial vehicle and the field boundary, the distance between the unmanned aerial vehicle and the capturing target and the expected surrounding circle radius of the unmanned aerial vehicle group;
and S500, the unmanned aerial vehicle flies according to the control speed so as to trap the trapping target.
Further, the step S200 includes:
step S210, the unmanned aerial vehicle determines a first matrix according to the distance between the unmanned aerial vehicle and each target and the number of unmanned aerial vehicles for capturing each target, wherein the first matrix is used for representing the capturing weight of each target;
and S220, carrying out maximum value indexing on the first matrix, indexing out the maximum value of the trapping weight, and taking the target corresponding to the serial number of the maximum value as the trapping target of the unmanned aerial vehicle.
Further, the calculation formula of the first matrix is:
wherein seq is k The trapping weight of the kth target is (a, b) a weight matrix, r itark Distance N of ith unmanned aerial vehicle from kth target itark The number of unmanned aerial vehicles for capturing the kth target; k=1, 2,. -%, n; n is the total number of targets.
Further, the step S400 includes:
step S410, determining a first speed of the unmanned aerial vehicle at the current moment according to the distance between the unmanned aerial vehicle and other unmanned aerial vehicles in the unmanned aerial vehicle group and the distance between the unmanned aerial vehicle and each target;
step S420, the unmanned aerial vehicle determines a second speed of the unmanned aerial vehicle according to the distance between the unmanned aerial vehicle and the obstacle;
step S430, the unmanned aerial vehicle determines a third speed of the unmanned aerial vehicle at the current moment according to the distance between the unmanned aerial vehicle and the field boundary;
step S440, the unmanned aerial vehicle determines a fourth speed of the unmanned aerial vehicle at the current moment according to the distance between the unmanned aerial vehicle and the capturing target and the expected radius of the surrounding ring of the unmanned aerial vehicle group;
and step S450, determining the control speed of the unmanned aerial vehicle at the current moment according to the first speed, the second speed, the third speed and the fourth speed of the unmanned aerial vehicle in the unmanned aerial vehicle group.
Further, the step S410 includes:
step S411, determining a first rejection speed of the unmanned aerial vehicle at the current moment according to the distance between the unmanned aerial vehicle and other unmanned aerial vehicles in the unmanned aerial vehicle group by the unmanned aerial vehicle in the unmanned aerial vehicle group;
step S412, the unmanned aerial vehicle in the unmanned aerial vehicle group determines a second rejection speed of the unmanned aerial vehicle at the current moment according to the distance between the unmanned aerial vehicle and each target;
step S413, overlapping the first rejection speed and the second rejection speed of the unmanned aerial vehicle to obtain a first speed of the unmanned aerial vehicle at the current moment.
A computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the distributed enclosure control method of a drone cluster of any of the above claims.
A distributed enclosure control system for a cluster of unmanned aerial vehicles, the system comprising:
at least one processor;
at least one memory for storing at least one program;
the at least one program, when executed by the at least one processor, causes the at least one processor to implement the distributed enclosure control method of the drone cluster of any one of the above.
The beneficial effects of the invention are as follows: the invention discloses a distributed trapping control method and a distributed trapping control system for unmanned aerial vehicle clusters, which are used for the unmanned aerial vehicle to execute trapping tasks in a certain area range, and the method and the system realize the autonomous trapping of the unmanned aerial vehicle clusters, have no central control node, are used for the unmanned aerial vehicle to adaptively and automatically make decision and group trapping targets in real time, are convenient for the unmanned aerial vehicle to cooperatively execute the trapping tasks autonomously, can achieve the effect of trapping the clusters without manual control, and are simple and convenient; the unmanned aerial vehicles can automatically avoid obstacles in the flight process, the unmanned aerial vehicles can independently avoid collision, and the unmanned aerial vehicles can fly in the field, so that the safety is high.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a distributed capture control method for an unmanned aerial vehicle cluster in an embodiment of the invention;
FIG. 2 is a schematic diagram illustrating an effect of cluster trapping of a drone cluster in a venue according to an embodiment of the present invention;
FIG. 3 is a diagram of simulation experiment effects of distributed trapping of unmanned aerial vehicle clusters in one scene in an embodiment of the invention;
fig. 4 is a diagram of simulation experiment effect of distributed trapping of unmanned aerial vehicle groups under another scene in the embodiment of the invention;
fig. 5 is a diagram of simulation experiment effects of distributed trapping of unmanned aerial vehicle clusters in another scenario in an embodiment of the present invention.
Detailed Description
The conception, specific structure, and technical effects produced by the present application will be clearly and completely described below with reference to the embodiments and the drawings to fully understand the objects, aspects, and effects of the present application. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other.
Referring to fig. 1, fig. 1 shows a distributed enclosure control method for an unmanned aerial vehicle cluster according to an embodiment of the present application, where the method includes the following steps:
step S100, target detection is carried out on unmanned aerial vehicles in a group, and the distance between the unmanned aerial vehicle and each target and the number of unmanned aerial vehicles for capturing each target are obtained;
step 200, the unmanned aerial vehicle determines a trapping target of the unmanned aerial vehicle according to the distance between the unmanned aerial vehicle and each target and the number of unmanned aerial vehicles trapping each target;
step S300, taking a plurality of unmanned aerial vehicles for capturing the capturing target of the unmanned aerial vehicle as an unmanned aerial vehicle group, and acquiring the distance between the unmanned aerial vehicle and other unmanned aerial vehicles in the group, the distance between the unmanned aerial vehicle and each target, the distance between the unmanned aerial vehicle and an obstacle, the distance between the unmanned aerial vehicle and the field boundary, the distance between the unmanned aerial vehicle and the capturing target and the expected radius of the surrounding ring of the unmanned aerial vehicle group;
step S400, the unmanned aerial vehicle determines the control speed of the unmanned aerial vehicle at the current moment according to the distance between the unmanned aerial vehicle and other unmanned aerial vehicles in the group, the distance between the unmanned aerial vehicle and each target, the distance between the unmanned aerial vehicle and the obstacle, the distance between the unmanned aerial vehicle and the field boundary, the distance between the unmanned aerial vehicle and the capturing target and the expected surrounding circle radius of the unmanned aerial vehicle group;
and S500, the unmanned aerial vehicle flies according to the control speed so as to trap the trapping target.
In the embodiment provided by the invention, all unmanned aerial vehicles are contained in a group, wherein the unmanned aerial vehicle group is an unmanned aerial vehicle set for trapping the same trapping target, and it can be understood that the unmanned aerial vehicles in the group are divided into a plurality of unmanned aerial vehicle groups; specifically, after each unmanned aerial vehicle determines respective trapping targets, unmanned aerial vehicles trapping the same trapping targets form an unmanned aerial vehicle group, then unmanned aerial vehicles in the unmanned aerial vehicle group fly towards the trapping targets to trap, in the flying process, the unmanned aerial vehicles need to timely adjust the flying speed according to the distances between the unmanned aerial vehicles and the surrounding unmanned aerial vehicles, the targets, the barriers and the field boundaries, so that the trapping targets are trapped according to the expected surrounding circle radius of the unmanned aerial vehicle group on the premise of avoiding collision.
As a further improvement of the above embodiment, the step S200 includes:
step S210, the unmanned aerial vehicle determines a first matrix according to the distance between the unmanned aerial vehicle and each target and the number of unmanned aerial vehicles for capturing each target, wherein the first matrix is used for representing the capturing weight of each target;
the calculation formula of the first matrix is as follows:
wherein seq is k The trapping weight of the kth target is (a, b) a weight matrix, r itark Distance N of ith unmanned aerial vehicle from kth target itark The number of unmanned aerial vehicles for capturing the kth target; k=1, 2,. -%, n; n is the total number of targets.
It should be noted that, in some embodiments, the weight matrix (a, b) is obtained according to expert experience and actual operation conditions.
And S220, carrying out maximum value indexing on the first matrix, indexing out the maximum value of the trapping weight, and taking the target corresponding to the serial number of the maximum value as the trapping target of the unmanned aerial vehicle.
In this embodiment, an adaptive decision is made according to the surrounding condition of the target, and the surrounding target of each unmanned plane is determined in real time. And (5) searching the target sequence number at the maximum value, wherein the target sequence number is a target which the unmanned aerial vehicle group should preferentially select at present and is taken as a currently-captured object.
Referring to fig. 2, as a further improvement of the above embodiment, the step S400 includes:
step S410, determining a first speed of the unmanned aerial vehicle at the current moment according to the distance between the unmanned aerial vehicle and other unmanned aerial vehicles in the unmanned aerial vehicle group and the distance between the unmanned aerial vehicle and each target; the first speed is a speed generated by repulsive force of the unmanned aerial vehicle on the periphery and repulsive force of each target.
In one embodiment, the step S410 includes:
step S411, determining a first rejection speed of the unmanned aerial vehicle at the current moment according to the distance between the unmanned aerial vehicle and other unmanned aerial vehicles in the unmanned aerial vehicle group by the unmanned aerial vehicle in the unmanned aerial vehicle group;
the calculation formula of the first rejection speed of the unmanned aerial vehicle is as follows:
wherein,,for the first rejection speed of the ith drone,/->Is an adjustable parameter->The value range of (5) is [0.2,10.0 ]]In m 2 /s，r agentrep For a first distance threshold, r i R is the current position of the ith unmanned aerial vehicle j The current position of the jth unmanned plane; r is (r) ij R is the distance between the ith unmanned aerial vehicle and the jth unmanned aerial vehicle ij ＝|r i -r j |。
It can be appreciated that in this embodiment, the repulsive speed of the unmanned aerial vehicles is determined based on the repulsive force rule, that is, if the distance between two unmanned aerial vehicles in the population is smaller than the first distance threshold, the unmanned aerial vehicles will generate repulsive speeds in opposite directions, so that no collision occurs between the unmanned aerial vehicles.
Step S412, the unmanned aerial vehicle in the unmanned aerial vehicle group determines a second rejection speed of the unmanned aerial vehicle at the current moment according to the distance between the unmanned aerial vehicle and each target;
the calculation formula of the second rejection rate of the unmanned aerial vehicle is as follows:
wherein,,for the second rejection speed of the ith drone,/->Is an adjustable parameter->The value range of (5) is [0.2,10.0 ]]In m 2 /s，r targetrep For a second distance threshold, r target Is the current location of the target; r is (r) itarget Is the distance between the ith unmanned aerial vehicle and the target.
The repulsive force method is also applied between the unmanned aerial vehicle and the target. But is a unidirectional rejection between the drone and the target. After the unmanned aerial vehicle detects the target (namely, the distance between the unmanned aerial vehicle and the target is within a second distance threshold), the unmanned aerial vehicle can be subjected to the rejection speed of the target, and the unmanned aerial vehicle is prevented from colliding with the target.
Step 413, superposing the first rejection speed and the second rejection speed of the unmanned aerial vehicle to obtain a first speed of the unmanned aerial vehicle at the current moment;
wherein,,the first speed of the ith unmanned aerial vehicle at the current moment.
It should be noted that, regarding the ith unmanned aerial vehicle, the rejection speed influence generated by all unmanned aerial vehicles within the first distance threshold needs to be considered, and the rejection speed influence generated by all targets within the second distance threshold needs to be considered, so that the rejection speed of the unmanned aerial vehicle is obtained by adopting the above formula and is used as the first speed of the unmanned aerial vehicle at the current moment.
Step S420, the unmanned aerial vehicle determines a second speed of the unmanned aerial vehicle according to the distance between the unmanned aerial vehicle and the obstacle; the second speed is the speed of the unmanned plane for avoiding the obstacle;
the calculation formula of the second speed of the unmanned aerial vehicle at the current moment is as follows:
wherein,,the second speed of the ith unmanned aerial vehicle at the current moment is the speed of the ith unmanned aerial vehicle for avoiding touching the obstacle, v i The current speed of the ith unmanned aerial vehicle; v s A first virtual speed representing a first virtual agent, the first virtual agent being located at a point on an edge of an obstacle closest to the drone; wherein the first virtual speed v s The speed generated by the first virtual intelligent agent on the edge of the obstacle when the unmanned aerial vehicle is too close to the edge of the obstacle; when the unmanned aerial vehicle is about to collide with an obstacle, the unmanned aerial vehicle has the function of keeping the unmanned aerial vehicle away from the obstacle, and the first virtual intelligent body does not generate displacement under the action of the first virtual speed; first virtual speed v s Is perpendicular to the barrier edge line where the first virtual intelligent agent is located and points to the field, wherein the field refers to the flight area of unmanned aerial vehicles in the group, v is Speed vector v of ith unmanned aerial vehicle i First virtual velocity vector v with first virtual agent s Modulus of vector difference between v is ＝|v i -v s |；r is R is the distance between the ith unmanned aerial vehicle and the first virtual intelligent agent, namely the distance between the unmanned aerial vehicle and the nearest point on the obstacle to the unmanned aerial vehicle is ＝|r i -r s |；r obs And the third distance threshold value is the safety distance between the unmanned aerial vehicle and the obstacle. Calculating the speed of the unmanned plane away from the obstacle according to the formula>The direction is (v) i -v s )/v is ；C shill For adjustable coefficient, a shill 、p shill For adjustable parameter a shill In units of m/s 2 、p shill In 1/s, D (r, a, p) is a smooth speed decay function, here as a braking curve of the drone to its desired stopping point, at a gain p shill In larger cases the braking curve approximates a constant acceleration curve; c when the unmanned aerial vehicle keeps away the barrier shill The second speed size may be linearly adjusted; a, a shill Is the maximum acceleration of the drone at the second velocity component.
Step S430, the unmanned aerial vehicle determines a third speed of the unmanned aerial vehicle at the current moment according to the distance between the unmanned aerial vehicle and the field boundary; the third speed is a speed of the unmanned aerial vehicle away from the site boundary;
the calculation formula of the third speed of the unmanned aerial vehicle at the current moment is as follows:
wherein,,for the third speed of the ith unmanned aerial vehicle at the current moment, v i The current speed of the ith unmanned aerial vehicle; r is (r) wall Is the firstFour distance threshold, v w The second virtual speed of the second virtual intelligent agent is represented, and the second virtual intelligent agent is located at the position of the nearest point on the site boundary to the unmanned plane; wherein the second virtual speed v w The speed generated by the second virtual intelligent agent on the site boundary when the unmanned plane is too close to the site boundary; when the distance between the unmanned aerial vehicle and the site boundary is smaller than a fourth distance threshold, the unmanned aerial vehicle has the function of enabling the unmanned aerial vehicle to be far away from the site boundary, and the second virtual intelligent body does not generate displacement under the action of the second virtual speed; second virtual speed v w Is perpendicular to the boundary line of the site where the second virtual agent is located and is directed to the site, v iw Speed vector v of ith unmanned aerial vehicle i Second virtual velocity vector v with second virtual agent w Modulus of vector difference between v iw ＝|v i -v w |；r iw Is the distance between the ith unmanned aerial vehicle and the second virtual intelligent agent, namely the shortest distance between the ith unmanned aerial vehicle and the field boundary, r iw ＝|r i -r w I (I); when the unmanned aerial vehicles in the unmanned aerial vehicle group approach near field boundary, the third speed is adopted to limit the unmanned aerial vehicle to fly in the field boundary, the field can be set through the GPS on board the unmanned aerial vehicle, and the field boundary is the position boundary limited by the GPS; c'. shill For adjustable coefficient, a' shill 、p′ shill For adjustable parameters, a' shill In units of m/s 2 、p′ shill In 1/s, D '(r, a, p) is a smooth speed decay function, here as a braking curve of the drone to its desired stopping point, at a gain p' shill In larger cases the braking curve approximates a constant acceleration curve; c 'when the unmanned aerial vehicle is far away from the site boundary' shill The third speed may be linearly adjusted; a' shill Is the maximum acceleration of the drone at the third speed component.
Step S440, the unmanned aerial vehicle determines a fourth speed of the unmanned aerial vehicle at the current moment according to the distance between the unmanned aerial vehicle and the capturing target and the expected radius of the surrounding ring of the unmanned aerial vehicle group; the fourth speed is the speed of the unmanned aerial vehicle for capturing the target;
the calculation formula of the fourth speed of the unmanned aerial vehicle at the current moment is as follows:
wherein v is itarget The fourth speed of the ith unmanned aerial vehicle at the current moment, namely the speed item of the ith unmanned aerial vehicle for tracking and capturing the captured target, v f Tracking an initial velocity value of the captured target for the unmanned aerial vehicle, C t To adjust the linear gain of the drone towards the fourth speed component, r itarget R is the distance between the ith unmanned plane and the trapping object entrap A is the radius of a desired enclosure of the unmanned aerial vehicle group target 、p target In order to adjust the parameters of the device,the method comprises the steps of pointing the trapping target from the ith unmanned aerial vehicle to the direction of the trapping target relative to the ith unmanned aerial vehicle.
And step S450, determining the control speed of the unmanned aerial vehicle at the current moment according to the first speed, the second speed, the third speed and the fourth speed of the unmanned aerial vehicle in the unmanned aerial vehicle group.
The calculation formula of the control speed of the unmanned aerial vehicle at the current moment is as follows:
wherein,,indicating the theoretical speed of the ith drone, < >>Indicating the control speed, v, of the ith unmanned aerial vehicle at the current moment limit Representing a speed cut-off value for the drone.
In this embodiment, a speed cutoff value is introduced, if the calculated theoretical speed is greater than the speed cutoff value v of the unmanned plane flight under the condition that the direction of the speed is unchanged limit The magnitude of the control speed is set as a speed cut-off value, and the direction is still consistent with the theoretical speed.
After the unmanned aerial vehicle acquires the information of the trapping target, the trapping target is trapped. In the process of approaching the trapping target, the closer the unmanned aerial vehicle is to the trapping target, the smaller the speed is, and the speed of the unmanned aerial vehicle needs to be smoothly attenuated, so that the unmanned aerial vehicle meets the natural group motion law. In this embodiment, the control speed of the unmanned aerial vehicle at the current moment is obtained by superposing the speed components.
Referring to fig. 3 to 5, in one simulation experiment, targets were trapped by using a drone group, which walked by using a lewy flight algorithm in the field.
Referring to fig. 3, in one scenario, the drone may tightly trap obstacles in a narrow traffic space, and its trapping configuration may be adaptively adjusted with the environment.
Referring to fig. 4, in a nine-grid scene, the unmanned aerial vehicle can flexibly change directions in an environment full of obstacles, so that the obstacles are avoided, and a good trapping effect is realized.
Referring to fig. 5 in combination, it can be seen that:
1. the unmanned aerial vehicle self-adaptive grouping is used for capturing the targets, the unmanned aerial vehicle capturing each target is not too much or too little, and when two targets are close, the unmanned aerial vehicle group can independently make a decision according to the current information to orderly form new groupings.
2. The unmanned aerial vehicle and the target can not collide with each other, and the unmanned aerial vehicle can not touch the obstacle.
3. The trapping form of the unmanned aerial vehicle can be adaptively adjusted along with the environment.
4. The unmanned plane forms a tight and uniform surrounding ring on the target in a flying state similar to a natural population.
Compared with the prior art, the embodiment provided by the invention has the following advantages:
according to the invention, unmanned aerial vehicle autonomous cluster trapping is realized, a central control node does not exist, and when a plurality of targets are encountered, unmanned aerial vehicles self-adaptively decide to trap corresponding targets, so that unmanned aerial vehicle cluster cooperation autonomous execution of trapping tasks is facilitated, the cluster trapping effect can be achieved without manual control, and the method is simple and convenient;
unmanned aerial vehicles avoid the barrier automatically in the flight process, and the unmanned aerial vehicles are prevented from colliding independently, namely, independent interaction exists among unmanned aerial vehicle individuals, so that the safety is high.
Corresponding to the method of fig. 1, the embodiment of the present invention further provides a computer readable storage medium, where a distributed capture control program of the unmanned aerial vehicle cluster is stored on the computer readable storage medium, where the steps of the distributed capture control method of the unmanned aerial vehicle cluster according to any one of the embodiments are implemented when the distributed capture control program of the unmanned aerial vehicle cluster is executed by a processor.
Corresponding to the method of fig. 1, the embodiment of the invention further provides a distributed capture control system of the unmanned aerial vehicle cluster, where the system includes:
at least one processor;
at least one memory for storing at least one program;
when the at least one program is executed by the at least one processor, the at least one processor is caused to implement the distributed capture control method of the unmanned aerial vehicle cluster according to any one of the above embodiments.
The content in the method embodiment is applicable to the system embodiment, the functions specifically realized by the system embodiment are the same as those of the method embodiment, and the achieved beneficial effects are the same as those of the method embodiment.
The Processor may be a Central-Processing Unit (CPU), other general-purpose Processor, digital-Signal-Processor (DSP), application-Specific-Integrated-Circuit (ASIC), field-Programmable-Gate array (FPGA), or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. The general processor may be a microprocessor or the processor may be any conventional processor, etc., which is a control center of the distributed capture control system of the unmanned aerial vehicle cluster, and connects various parts of the operational devices of the distributed capture control system of the entire unmanned aerial vehicle cluster by various interfaces and lines.
The memory may be used to store the computer program and/or module, and the processor may implement various functions of the distributed capture control system of the drone cluster by running or executing the computer program and/or module stored in the memory, and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart-Media-Card (SMC), secure-digital (SD) Card, flash Card (Flash-Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
Although the description of the present application has been described in considerable detail and with particularity with respect to several illustrated embodiments, it is not intended to be limited to any such detail or embodiments or any particular embodiment, but is to be construed as providing broad interpretation of such claims by reference to the appended claims, taking into account the prior art to which such claims are entitled to effectively encompass the intended scope of this application. Furthermore, the foregoing description of the embodiments contemplated by the inventors has been presented for the purpose of providing a useful description, and yet insubstantial changes to the invention that are not presently contemplated may represent equivalents of the invention.
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| CN114859904B (en) * | 2022-04-24 | 2023-04-07 | 汕头大学 | Cluster trapping method, executing device and system based on E-GRN |
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