Unmanned aerial vehicle deployment method, device, equipment, storage medium and product

Abstract

The invention discloses an unmanned aerial vehicle deployment method and device, equipment, a storage medium and a product, and relates to the technical field of communication, and the unmanned aerial vehicle deployment method comprises the steps: determining a target height when the coverage range is maximum; initializing the unmanned aerial vehicle, and receiving broadcast information of a neighbor unmanned aerial vehicle; determining a current moving strategy according to the broadcast information; and carrying out unmanned aerial vehicle deployment based on the movement strategy. The current movement strategy is determined according to the broadcast information of the neighbor unmanned aerial vehicle, and unmanned aerial vehicle deployment is performed based on the movement strategy. Compared with an existing mode that a specific unmanned aerial vehicle obtains all information of the whole network in advance and then carries out deployment, the method can reduce the cost and energy consumption of unmanned aerial vehicle deployment, and improves the deployment efficiency of the unmanned aerial vehicle.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to drone deployment methods, devices, equipment, storage media and products. Background Art

[0002] The deployment mechanism of drones in existing drone networks is usually centralized and executed by some specific drones. These drones need to obtain all the information of the entire network in advance in order to execute the deployment mechanism and obtain the global optimal deployment result. However, in actual scenarios, due to the limitation of communication range, individual drones are usually unable to obtain all the information of the entire network through single-hop routing. Therefore, how to improve the deployment efficiency of drones has become a technical problem that needs to be solved urgently. Summary of the invention

[0003] The main purpose of this application is to provide a drone deployment method, device, equipment, storage medium and product, aiming to solve the technical problem of low efficiency of existing drone deployment.

[0004] To achieve the above objectives, the present application proposes a drone deployment method, which includes:

[0005] Determine the target height at which coverage is maximum;

[0006] Initialize the drone and receive broadcast information from neighboring drones;

[0007] Determine a current mobility strategy according to the broadcast information;

[0008] The drones are deployed based on the mobility strategy.

[0009] Optionally, the step of determining the current mobility strategy according to the broadcast information includes:

[0010] Determine whether the current state is redundant according to the broadcast information;

[0011] If the current state is not redundant, determine whether the target mark is currently received;

[0012] A current movement strategy is determined according to whether the target mark is received.

[0013] Optionally, the step of determining the current movement strategy according to whether the target mark is received includes:

[0014] When receiving the target mark, determining that the current movement strategy is a diffusion movement strategy;

[0015] When the target mark is not received, it is determined that the current movement strategy is an enhanced movement strategy.

[0016] Optionally, the step of deploying drones based on the mobile strategy includes:

[0017] When the movement strategy is an enhanced movement strategy, calculating local Voronoi information;

[0018] Determining whether to search for a candidate position according to the local Voronoi information;

[0019] If so, the candidate position is determined based on the virtual Coulomb force and Voronoi partitioning;

[0020] The drone is deployed according to the candidate location.

[0021] Optionally, the step of deploying a drone according to the candidate location includes:

[0022] Determine the area of ​​the historical coverage area corresponding to the historical location;

[0023] Obtaining the candidate coverage area corresponding to the candidate position;

[0024] The drones are deployed according to the historical coverage area and the candidate coverage area.

[0025] Optionally, the step of determining the target height when the coverage range is maximum includes:

[0026] Determine path loss information between the user;

[0027] Determining a maximum coverage radius according to the path loss;

[0028] The target height when the coverage range is maximum is determined based on the maximum coverage radius and the optimal elevation angle.

[0029] In addition, to achieve the above-mentioned purpose, the present application also proposes a drone deployment device, the drone deployment device comprising:

[0030] A determination module, used for determining the target height when the coverage range is maximum;

[0031] The receiving module is used to initialize the drone and receive broadcast information from neighboring drones;

[0032] A mobile strategy determination module, used to determine a current mobile strategy according to the broadcast information;

[0033] The drone deployment module is used to deploy drones based on the mobile strategy.

[0034] In addition, to achieve the above-mentioned purpose, the present application also proposes a drone deployment device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the drone deployment method as described above.

[0035] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the drone deployment method described above are implemented.

[0036] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the drone deployment method described above.

[0037] The present application determines the target height when the coverage is the largest; initializes the drone and receives broadcast information from neighboring drones; determines the current mobile strategy based on the broadcast information; and deploys the drone based on the mobile strategy. Since the present application determines the current mobile strategy based on the broadcast information of neighboring drones and deploys the drone based on the mobile strategy. Compared with the existing method in which a specific drone obtains all the information of the entire network in advance and then deploys it, the above method of the present application can reduce the cost and energy consumption of drone deployment and improve the efficiency of drone deployment. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0040] Figure 1 A flowchart of the first embodiment of the method for deploying a drone according to the present application is provided;

[0041] Figure 2 A schematic diagram of a communication model between a drone and a ground user provided in Embodiment 1 of the drone deployment method of the present application;

[0042] Figure 3 A flowchart of the second embodiment of the method for deploying a drone in this application is provided;

[0043] Figure 4This is a schematic diagram of the module structure of the drone deployment device according to an embodiment of the present application;

[0044] Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the drone deployment method in the embodiment of the present application.

[0045] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0046] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0047] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0048] The main solution of the embodiment of the present application is: determine the target height when the coverage is the largest; initialize the drone and receive the broadcast information of the neighboring drones; determine the current mobile strategy based on the broadcast information; deploy the drone based on the mobile strategy. Since the present application determines the current mobile strategy based on the broadcast information of the neighboring drones, the drones are deployed based on the mobile strategy. Compared with the existing method in which a specific drone obtains all the information of the entire network in advance and then deploys it, the above method of the present application can reduce the cost and energy consumption of drone deployment and improve the efficiency of drone deployment.

[0049] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a drone, etc. The following takes the drone deployment device as an example to illustrate this embodiment and the following embodiments.

[0050] Based on this, the present application embodiment provides a method for deploying a drone, referring to Figure 1 , Figure 1 A flowchart of the first embodiment of the drone deployment method of the present application is provided.

[0051] In this embodiment, the drone deployment method includes the following steps:

[0052] Step S10, determining the target height when the coverage range is maximum;

[0053] It should be noted that the embodiment of the present application adopts a distributed deployment mechanism of drones, that is, the drones do not need to obtain all the information of the entire network in advance, but all drones in the network jointly perform deployment based on the single-hop routing information obtained by each drone. Therefore, distributed deployment is more practical and effective to a certain extent. In this embodiment, the goal is to maximize the coverage area while minimizing the number of drones. The target height can be the optimal height h of the drone when the drone coverage range is the largest. op t The specific calculation method can be: refer to Figure 2 , Figure 2 A schematic diagram of a communication model between a drone and a ground user provided in Embodiment 1 of the drone deployment method of the present application, Figure 2 UAV in the text is used to represent UAVs, User is used to represent ground users, and N i Used to characterize the i-th UAV, h i is the vertical height of the UAV, d ik is the straight-line distance between the drone and the user, r ik For drones and users k The horizontal distance, θ ik is the upward angle of the drone. First, set the drone N i and user U k The path loss between i ,r il ) can be expressed as:

[0054]

[0055] Where f2 represents the carrier frequency of the communication channel between the drone and the user, η LoS and η NLoS are the average additional path losses for line-of-sight and non-line-of-sight links, respectively, a and b are constants that depend on the environment (rural, urban, dense urban, etc.), and c represents the speed of light.

[0056] Calculate and derive the maximum coverage radius R of the drone opt Since R(r ik ) is h(h i ) can be calculated by calculating L(h o ,r ok ), that is, solving formula (2) to obtain the optimal height of the maximum coverage range of the drone:

[0057]

[0058] From formula (3), we can see that searching (h opt , R opt ) can be obtained by searching (θopt ,R opt ), that is, solving formula (4) for θ, and obtaining formula (5).

[0059]

[0060] From formula (5), it can be concluded that the optimal elevation angle θopt depends only on the environment. Therefore, given the optimal elevation angle θopt and the path loss threshold L ′ th , maximum coverage radius R opt It can be obtained by solving the following formula (7).

[0061] Get the optimal height h of the drone when the drone coverage is the largest opt By solving formula (6) and formula (7), we can get the optimal height h of the UAV: opt , that is, the target height when the coverage range is maximum.

[0062]

[0063] h opt =R opt tan(θ opt ) Formula (7)

[0064] Step S20, initializing the drone and receiving broadcast information from neighboring drones;

[0065] It should be noted that the UAV initialization may be performed by UAV N i The basic information of (i=1,2,…,n) is initialized. i The identification number of UAV N should be initialized to be unique, and in this embodiment is initialized to i. i The state is initialized to the active state (i.e. S i =1), its timer is initialized to zero (i.e., δ i =0). During the deployment process, UAV N i will fly at the same optimal altitude, so its velocity in the horizontal dimension is initialized to zero, i.e., v i,1 =0,v i,2 = 0. Drone N i The horizontal position (p i,1 ,p i,2 ) is randomly initialized in the area of ​​interest. And the time slot t is initially set to 1, that is, t = 1. In each time slot t, the steps need to be repeated to receive the broadcast information of the neighboring drones until the time slot t reaches the maximum deployment time T maxThe receiving of the broadcast information of neighboring drones may be that each drone Ni broadcasts its own information while sensing the environment and receiving neighbor information to update the local information of the drone.

[0066] Step S30, determining a current mobility strategy according to the broadcast information;

[0067] It should be noted that the mobile strategy includes a diffusion mobile strategy and an enhanced mobile strategy. The current mobile strategy determined according to the broadcast information can be to determine whether the drone is a redundant drone according to its dormancy strategy. If the drone is a redundant drone, it is determined that it needs to be updated. At this time, when the drone Ni receives any deletion or insertion mark, that is, F del ∨F ins = = 1, the diffusion movement strategy is executed, otherwise, the drone Ni executes the enhanced movement strategy and the drone sleep strategy in sequence. If the drone is not a redundant drone, it remains in the sleep state, that is, the non-working state.

[0068] Step S40: deploying drones based on the mobile strategy.

[0069] It should be noted that the deployment of the drone based on the mobile strategy may be to determine the candidate positions of the drone according to the mobile strategy, and then deploy the drone based on the candidate positions.

[0070] This embodiment determines the target height when the coverage range is the largest; initializes the drone and receives the broadcast information of neighboring drones; determines the current mobile strategy based on the broadcast information; and deploys the drone based on the mobile strategy. Since this embodiment determines the current mobile strategy based on the broadcast information of neighboring drones and deploys drones based on the mobile strategy. Compared with the existing method in which a specific drone obtains all the information of the entire network in advance and then deploys, the above method of this embodiment can reduce the cost and energy consumption of drone deployment and improve the efficiency of drone deployment.

[0071] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 3 , Figure 3 The flowchart of the second embodiment of the method for deploying a drone of the present application is provided, wherein step S30 further includes the following steps:

[0072] Step S301: determining whether the current state is redundant according to the broadcast information;

[0073] It should be noted that the redundant state is a dormant state of the drone. Determining whether the current state is a redundant state according to the broadcast information may be determining the redundancy of the drone according to the broadcast information, and judging whether the drone should enter a dormant state according to the redundancy.

[0074] Step S302: If the current state is not redundant, determine whether the target mark is currently received;

[0075] It should be noted that the target mark may be a mark broadcast by other drones, a deletion mark or an insertion mark. The insertion mark may be an insertion mark generated when a drone with almost exhausted battery needs to insert a drone with sufficient battery when flying back to the base station. The deletion mark may be a deletion mark broadcast by other drones when they enter a dormant state or change their position.

[0076] Step S303: Determine the current movement strategy according to whether the target mark is received.

[0077] It should be noted that the current movement strategy determined according to whether the target mark is received can be when the drone N i When receiving any deletion or insertion mark, the diffusion movement strategy is executed, otherwise, UAV N i The enhanced mobile strategy and the drone sleep strategy are executed in sequence. The diffusion mobile strategy can be that each drone uses the diffusion mobile strategy to move away from adjacent drones and adjacent boundaries, so that all drones are quickly dispersed and evenly distributed in the area of ​​interest. Each drone can further improve its local coverage area through the enhanced mobile strategy, thereby improving the overall coverage area. Each drone determines whether it is a redundant drone through the sleep strategy, and reduces the number of deployed drones by shutting down redundant drones, thereby reducing costs and energy consumption. When executing the diffusion mobile strategy and the enhanced mobile strategy, it is necessary to calculate the candidate positions of the drone. In different mobile strategies, the virtual forces used to calculate the candidate positions of the drone are different. In the drone diffusion mobile strategy, the virtual forces received come from adjacent drones and adjacent boundaries. In the drone enhanced mobile strategy, the virtual forces received come from Voronoi vertices and Voronoi edges. Among them, the specific steps of the drone diffusion mobile strategy include: 8.1 Initialize and set the diffusion mobile timer to 1, that is, t VCF = 1. Step 8.2: In each time slot t VCF Repeat steps 8.3 to 8.6 until time slot t VCF Maximum deployment time reached

[0078] Step 8.3: Calculate the new position. Calculate the new drone position based on the virtual Coulomb force.

[0079] Step 8.4: Move to the calculated new position. The detailed steps of position calculation can be referred to step 11 below.

[0080] Step 8.5: The timer increases by 1, t=t+1.

[0081] Step 8.6: The local timer increases by 1, t VCF =t VCF +1.

[0082] It should be noted that the drone diffusion movement strategy is based on Virtual Coulomb Forcebased (VCF). In the VCF movement strategy, the drone calculates a new position and then moves directly to the new position. In particular, once a drone starts to execute the VCF movement strategy, it will run time slots to ensure that the drone is completely dispersed with its neighboring drones and adjacent boundaries. The computational complexity of VCF is

[0083] Furthermore, the step of deploying drones based on the mobile strategy includes:

[0084] When the movement strategy is an enhanced movement strategy, calculating local Voronoi information;

[0085] Determining whether to search for a candidate position according to the local Voronoi information;

[0086] If so, the candidate position is determined based on the virtual Coulomb force and Voronoi partitioning;

[0087] The drone is deployed according to the candidate location.

[0088] It should be noted that the enhanced mobility strategy of the drone is based on virtual Coulomb force and Voronoi diagram, referred to as VCV (Virtual Coulomb force and Voronoi diagram based). The VCV mobility strategy is divided into three steps. First, the drone obtains its Voronoi polygon based on the local information (i.e., broadcast information) it obtains and calculates the area of ​​its Voronoi polygon. Local coverage area and local coverage vulnerability area Then, the drone decides whether to find a candidate location and move to it. If its local coverage hole area is zero, that is, Then it will remain stationary. Otherwise, it will find a candidate position within its corresponding Voronoi polygon. The detailed steps of position calculation can refer to the following step 11. Finally, after finding its candidate position, the drone compares the obtained candidate position with its original position according to the area of ​​its local coverage area. When the area of ​​its local coverage area increases by ε% or more, the drone will move to this candidate position, otherwise, it will remain stationary. Then the timer is incremented by 1, t=t+1. Among them, ε% is a preset threshold, which can be customized.

[0089] It should be understood that this embodiment proposes a ground-to-sky integrated network emergency communication system with a drone deletion and insertion function that can provide long-term wireless communication services. First, each drone is embedded with a global positioning system (GPS) to obtain its accurate location. Second, the drone can be deleted or inserted from the emergency communication system. The drone may be deleted from the emergency communication system due to redundancy, energy exhaustion or damage. If the drone is deleted due to redundancy or energy exhaustion, it will fly back to the ground charging station to charge, then shut down and wait for reuse. In particular, when the energy-exhausted drone flies back to the charging station, it will send information to the charging station to notify the charging station to send a fully charged drone, so as to replace it to provide sufficient communication services for users. In order to avoid coverage holes caused by the inability of the drone to fly back to the charging station due to damage, the charging station will regularly send a drone to fly into the area of ​​interest at regular intervals. In addition, in this distributed system, each drone can broadcast its own information and receive single-hop information from neighbors, so it has good system scalability and flexibility.

[0090] This embodiment simulates a a A UAV network with UAVs flying above the ground provides communication coverage for users distributed in a two-dimensional area of ​​interest of size L×W. Assuming that time is discrete and iterative, let An index set representing time, where T max is the maximum deployment time. i |i=1,2,…,n a} and B={B i ∣i=1,2,3,4} are the sets of drones and the boundaries of the region of interest. For any point P in the region of interest i , whose position is denoted as P i =(p i,1 ,p i,2 ), where p i,1 ∈[0,L] and p i,2 ∈[0,W] are the position constraints of the two horizontal dimensions. In addition, point P i and point Pj The Euclidean distance between Indicates, where * = {a,u,b,v,e} is the point type, a, u, b, v and e represent the points P respectively. j There is a UAV, a user device, a boundary, a Voronoi vertex, and a Voronoi edge at .

[0091] It should be noted that, first, in order to evaluate the redundancy of each drone, this embodiment gives the average local coverage rate according to Voronoi segmentation: The local coverage quality is defined based on Voronoi segmentation. The two-dimensional region of interest is divided into n Voronoi polygons Ω = {Ω1,Ω2,…,Ω n}, that is, each drone corresponds to a Voronoi polygon. The local coverage rate and local coverage quality of each drone based on Voronoi segmentation are defined as follows. i The local coverage τ i It refers to the ratio of its local coverage area to the maximum area it can cover, which can be defined as follows:

[0092]

[0093] in is the Voronoi polygon Ω i The local coverage area, R cov is the radius of the communication coverage area, that is, the coverage range.

[0094] The specific steps of the drone sleep strategy in this embodiment include: i The average local coverage It refers to the average of the local coverage of its Voronoi neighbor drones and itself, and the formula is expressed as follows:

[0095]

[0096] in, Used to represent the number of neighboring drone nodes that can be received.

[0097] The sleep strategy is used to shut down redundant drones. The specific steps are as follows: The drone checks its local coverage vulnerability area and the average local coverage Determine whether there is a possibility of dormancy. If the local coverage hole area of ​​the drone is zero (i.e. ), and its average local coverage is less than a predefined average local coverage threshold It may enter a dormant state, that is, a non-working state. The steps of determining whether to dormant include: generating a random number p in the range [0,1]. If p is less than a predefined probability threshold p th, the drone will enter a dormant state, S i = 0, and broadcast a message containing a deletion mark (F del =1). Otherwise, the drone will remain in working state, i.e. S i =1.

[0098] In this embodiment, the specific step 11 of calculating the candidate position of the drone includes:

[0099] Force modeling: The resultant force acting on the UAV Ni can be expressed as formula (9):

[0100]

[0101] Specifically, inspired by the law of universal gravitation, VCF is used to push drones away from their neighboring drones, neighboring boundaries, Voronoi vertices, and Voronoi edges. i Receiving point P j The power of influence Indicates. Drone N i Each force is expressed in polar coordinates (r,θ), where r represents the UAV N i With point P j The distance between them, θ represents the distance between drones N i With point P j Angle in polar coordinates. Force The calculation is as follows formula (9-1):

[0102]

[0103] where k c is the factor constant representing the Coulomb force, It's a drone i and point P j Angle in polar coordinates. To characterize point P i and point P j The Euclidean distance between is the number of points*.

[0104] In each time slot, in order to map the resultant force from 0 to +∞ to the sum from 0 to v max The limited moving distance of , the following mapping formula (10) is used:

[0105]

[0106] in, is the maximum moving distance of each time slot. Then the position is obtained as follows:

[0107]

[0108] is the initial position of the drone. Through the above steps, we can get the new position in the VCF mobile strategy and the candidate position in the VCV mobile strategy. In the VCF mobile strategy, according to its combined force Calculate the new position. In the VCV mobile strategy, each drone uses its combined force and Two positions are obtained, and then the position with a higher local coverage area is selected as the candidate position.

[0109] This embodiment determines whether it is currently in a redundant state based on the broadcast information; if it is not currently in a redundant state, it determines whether the target tag is currently received; and determines the current mobility strategy based on whether the target tag is received. This embodiment aims to achieve efficient distributed deployment of drone networks, while ensuring coverage performance and ensuring that sufficient network services are provided to user devices with the least number of drones. By adopting a distributed deployment mechanism, each drone cooperates with other drones to perform deployment tasks based on the single-hop routing information it obtains.

[0110] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the drone deployment method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0111] This application also provides a drone deployment device, please refer to Figure 4 , the drone deployment device comprises:

[0112] A determination module 10 is used to determine the target height when the coverage range is maximum;

[0113] The receiving module 20 is used to initialize the drone and receive broadcast information from neighboring drones;

[0114] A mobile strategy determination module 30, configured to determine a current mobile strategy according to the broadcast information;

[0115] The drone deployment module 40 is used to deploy drones based on the movement strategy.

[0116] This embodiment determines the target height when the coverage range is the largest; initializes the drone and receives the broadcast information of neighboring drones; determines the current mobile strategy based on the broadcast information; and deploys the drone based on the mobile strategy. Since this embodiment determines the current mobile strategy based on the broadcast information of neighboring drones and deploys drones based on the mobile strategy. Compared with the existing method in which a specific drone obtains all the information of the entire network in advance and then deploys, the above method of this embodiment can reduce the cost and energy consumption of drone deployment and improve the efficiency of drone deployment.

[0117] The drone deployment device provided by the present application adopts the drone deployment method in the above embodiment, which can solve the technical problem of low efficiency of existing drone deployment. Compared with the prior art, the beneficial effects of the drone deployment device provided by the present application are the same as the beneficial effects of the drone deployment method provided by the above embodiment, and other technical features in the drone deployment device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0118] The present application provides a drone deployment device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the drone deployment method in the above-mentioned embodiment one.

[0119] Reference below Figure 5 , which shows a schematic diagram of the structure of the drone deployment device suitable for implementing the embodiment of the present application. The drone deployment device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The drone deployment device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present application.

[0120] like Figure 5As shown, the drone deployment device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the drone deployment device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the drone deployment device to communicate with other devices wirelessly or wired to exchange data. Although the figure shows a drone deployment device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0121] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0122] The drone deployment device provided by the present application adopts the drone deployment method in the above embodiment, which can solve the technical problem of low efficiency of existing drone deployment. Compared with the prior art, the beneficial effects of the drone deployment device provided by the present application are the same as the beneficial effects of the drone deployment method provided by the above embodiment, and the other technical features in the drone deployment device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0123] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0124] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0125] The present application provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the drone deployment method in the above-mentioned embodiment.

[0126] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0127] The above-mentioned computer-readable storage medium may be included in the drone deployment device; or it may exist independently without being assembled into the drone deployment device.

[0128] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0129] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0130] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0131] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned drone deployment method, and can solve the technical problem of low efficiency of existing drone deployment. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the drone deployment method provided in the above-mentioned embodiment, and will not be repeated here.

[0132] The present application also provides a computer program product, including a computer program, which implements the steps of the drone deployment method as described above when executed by a processor.

[0133] The computer program product provided by this application can solve the technical problem of low efficiency of existing drone deployment. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the drone deployment method provided by the above embodiment, which will not be repeated here.

[0134] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for deploying a drone, characterized in that: The drone deployment method comprises the following steps: Determine the target height at which coverage is maximum; Initialize the drone and receive broadcast information from neighboring drones; Determine a current mobility strategy according to the broadcast information; The drones are deployed based on the mobility strategy.

2. The method for deploying a drone as claimed in claim 1, wherein: The step of determining the current mobility strategy according to the broadcast information comprises: Determine whether the current state is redundant according to the broadcast information; If the current state is not redundant, determine whether the target mark is currently received; A current movement strategy is determined according to whether the target mark is received.

3. The method for deploying a drone as claimed in claim 2, characterized in that: The step of determining the current movement strategy according to whether the target mark is received comprises: When receiving the target mark, determining that the current movement strategy is a diffusion movement strategy; When the target mark is not received, it is determined that the current movement strategy is an enhanced movement strategy.

4. The method for deploying a drone according to claim 1, wherein: The step of deploying the drone based on the mobile strategy includes: When the movement strategy is an enhanced movement strategy, calculating local Voronoi information; Determining whether to search for a candidate position according to the local Voronoi information; If so, the candidate position is determined based on the virtual Coulomb force and Voronoi partitioning; The drone is deployed according to the candidate location.

5. The method for deploying a drone as claimed in claim 1, wherein: The step of deploying the drone according to the candidate location includes: Determine the area of ​​the historical coverage area corresponding to the historical location; Obtaining the candidate coverage area corresponding to the candidate position; The drones are deployed according to the historical coverage area and the candidate coverage area.

6. The method for deploying a drone according to any one of claims 1 to 5, characterized in that: The step of determining the target height when the coverage range is maximum comprises: Determine path loss information between the user; Determining a maximum coverage radius according to the path loss; The target height when the coverage range is maximum is determined based on the maximum coverage radius and the optimal elevation angle.

7. A drone deployment device, characterized in that: The drone deployment device comprises: A determination module, used for determining the target height when the coverage range is maximum; The receiving module is used to initialize the drone and receive broadcast information from neighboring drones; A mobile strategy determination module, used to determine a current mobile strategy according to the broadcast information; The drone deployment module is used to deploy drones based on the mobile strategy.

8. A drone deployment device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the drone deployment method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the drone deployment method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, which, when executed by a processor, implements the steps of the drone deployment method according to any one of claims 1 to 6.

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