Area coverage control method, device and equipment of air-ground unmanned aerial vehicle formation, and storage medium

Abstract

The present application relates to the technical field of unmanned aerial vehicle group control, and particularly relates to a regional coverage control method, device and equipment for air-ground unmanned aerial vehicle formation and a storage medium, which determines the total supervision area of each formation according to the real-time positions of unmanned aerial vehicles in each formation, divides the sub-areas according to the positions of ground unmanned aerial vehicles, then combines the division result with the distribution of global environmental field information, calculates the coverage loss formed by each formation at the edge of the area, controls the unmanned aerial vehicles to move to the corresponding optimal coverage positions based on the result, finally calculates the global coverage loss, and repeats the above steps until the global coverage loss reaches the convergence standard, thereby completing the global collaborative regional coverage of each type of unmanned aerial vehicle in multiple formations. The scheme dynamically adjusts the positions of each type of unmanned aerial vehicle by comprehensively considering the real-time positions of each unmanned aerial vehicle and environmental factors, effectively reduces coverage overlap and omission, enhances coverage collaboration between formations, and realizes the collaborative operation of different types of unmanned aerial vehicles in multiple formations.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) swarm control technology, and more particularly to a method, apparatus, equipment, and storage medium for regional coverage control of air-to-ground UAV formations. Background Technology

[0002] In today's era of rapid technological advancement, drone technology has been widely applied in numerous fields such as military reconnaissance, logistics delivery, agricultural plant protection, and disaster relief due to its unique advantages. Drone swarm operations have become a key mode for improving mission efficiency, with their characteristics of rapid deployment, flexibility, and low cost giving them significant advantages in performing area coverage missions.

[0003] Air-to-ground drone swarms, as a typical form of drone cluster operation, play a crucial role in practical applications. However, achieving efficient collaborative coverage of air-to-ground drone swarms in complex and ever-changing environments has become a highly challenging issue in the field of drone technology. Collaborative drone swarm operations not only need to consider mission efficiency but also the accuracy and uniformity of coverage to meet the complex requirements of different mission scenarios. In practical applications, drone swarms face problems such as uneven coverage, overlapping coverage, and missed areas, making it difficult to meet the demand for precise coverage in complex environments. Especially in multi-swarm collaborative operations, the lack of effective dynamic adjustment and optimization mechanisms leads to low coverage efficiency and poor coverage quality. For example, traditional control methods cannot adjust the drone coverage strategy in a timely manner when facing complex terrain and dynamically changing mission requirements, thus affecting the overall coverage effect.

[0004] Therefore, how to improve coverage efficiency and quality, reduce duplicate coverage and missed areas, and achieve efficient and uniform coverage in complex environments by dynamically adjusting the coverage area and target position of drones when multiple formations work together has become a technical problem that the industry urgently needs to solve. Summary of the Invention

[0005] The main objective of this invention is to provide a method, apparatus, device, and storage medium for regional coverage control of air-to-ground unmanned aerial vehicle (UAV) formations. This invention aims to solve the technical problem in the prior art of how to improve coverage efficiency and quality, reduce redundant coverage and missed areas, and achieve efficient and uniform coverage in complex environments by dynamically adjusting the coverage area and target position of UAVs when multiple formations are working together.

[0006] To achieve the above objectives, the present invention provides a method for area coverage control of air-to-ground unmanned aerial vehicle (UAV) formations, the method comprising the following steps: The total monitoring area for each formation is determined based on the real-time location of the drones in the air within each formation. Based on the real-time location of the ground drones in each formation, the total monitoring area is divided to obtain the monitoring sub-areas for each ground drone. Based on the heat map of the total monitoring area, sub-monitoring area, and global environmental field information distribution of each formation, calculate the edge coverage overlap loss of each formation; Based on the edge coverage overlap loss of each formation and the global environmental field information distribution heatmap, the target position of each UAV in each formation is calculated, and the UAV is controlled to move to the target position. When the UAV completes its movement, the global coverage loss at the current moment is calculated. The above steps are repeated until the global coverage loss meets the coverage loss convergence condition, so as to complete the global cooperative area coverage of various types of UAVs in multiple formations.

[0007] Optionally, determining the total monitoring area of ​​each formation based on the real-time location of the drones in each formation includes: Formations without defined regulatory areas are designated as pending formations, and the corresponding neighboring formation queues are determined based on the real-time positions of the drones within the pending formations. The real-time position of the UAV in the formation to be processed is taken as the first base point, and the real-time position of each UAV in the neighboring formation queue is taken as the second base point. Based on the first base point and the second base point, the initial boundaries of multiple regulatory areas of the formation to be processed are obtained; Based on the initial boundaries of the multiple regulatory areas and the total coverage target area, the total regulatory area of ​​the formation to be processed is obtained. The above steps are repeated until there are no formations that have not had their total regulatory area constructed, so as to determine the total regulatory area of ​​each formation.

[0008] Optionally, the step of calculating the edge coverage overlap loss of each formation based on the total monitoring area, monitoring sub-areas, and global environmental field information distribution heatmap of each formation includes: Based on the total monitoring area of ​​each formation and the monitoring sub-areas of the ground drones under each formation, the boundary area of ​​each formation is determined, wherein the boundary area is composed of the combination of the monitoring sub-areas corresponding to the ground drones under the formation. Based on the real-time position of each formation of ground UAVs and the boundary area of ​​each formation, determine the neighboring ground UAVs corresponding to each ground UAV in the boundary area; Based on the global environmental field information distribution heat map, calculate the difference in coverage contribution between the ground UAV and its corresponding neighboring ground UAV in the overlapping part of the boundary region; The edge coverage overlap loss of each formation is calculated based on the coverage contribution difference of the overlapping boundary portion.

[0009] Optionally, the step of calculating the coverage contribution difference between the ground-based UAV and its corresponding neighboring ground-based UAV in the overlapping portion of the boundary region based on the global environmental field information distribution heatmap includes: The local boundary of the ground drone combination is determined based on the monitoring sub-region corresponding to the ground drone and the monitoring sub-region corresponding to the neighboring drones. Based on the global environmental field information distribution heatmap, the environmental field information of the local boundary is determined; Based on the environmental field information of the local boundary, the real-time positions of the ground UAVs under the formation, and the real-time positions of the air UAVs in the formation, the coverage contribution of the formation at the local boundary is determined. Based on the environmental field information of the local boundary, the real-time positions of the neighboring ground UAVs under the neighboring formation, and the real-time positions of the neighboring aerial UAVs in the neighboring formation, the coverage contribution of the neighboring formation at the local boundary is determined. The difference in coverage contribution of the current formation at the local boundary is obtained based on the coverage contribution of the current formation at the local boundary and the coverage contribution of the neighboring formation at the local boundary. Repeat the above steps until the coverage contribution difference of all local boundaries in the overlapping boundary portion is obtained. Then, sum up the coverage contribution differences of the local boundaries to obtain the coverage contribution difference of the overlapping boundary portion.

[0010] Optionally, the coverage contribution of the local boundary satisfies the following formula: Coverage contribution ε j = ; Where, ε j This represents the coverage contribution of ground UAV j in this formation to the area where the local boundary is located, at the local boundary. t is the local boundary of the ground UAV j under the command of this formation within the boundary region formed by the UAV i in this formation and the UAV h in the neighboring formation, and t is the time point corresponding to the current calculation. This indicates the real-time position of UAV i in this formation at time t; This indicates the real-time position of the neighboring formation's aerial drone h at time t; This represents the real-time position of ground UAV j corresponding to the boundary portion of this formation at time t; q represents any point on the local boundary. The function value represents the environmental field information at point q.

[0011] Optionally, the step of calculating the target position of each UAV in each formation based on the edge coverage overlap loss of each formation and the global environmental field information distribution heatmap, and controlling the UAV to move to the target position, includes: Based on the real-time location of the ground UAV, the monitored sub-area of ​​the ground UAV, and the global environmental field information distribution heat map, the movement control parameters of each ground UAV are calculated. Based on the movement control parameters of the ground UAV, control the ground UAV to move to the corresponding target position; Based on the real-time location of the aerial drones, the total monitoring area of ​​the aerial drones, the edge coverage overlap loss of the corresponding formation of the aerial drones, and the global environmental field information distribution heat map, the movement control parameters of each aerial drone are calculated. Based on the movement control parameters of the aerial drone, the aerial drone is controlled to move to the corresponding target location.

[0012] Optionally, calculating the global coverage loss at the current moment includes: Based on the heat map of the total coverage area, global environmental field information distribution in each formation, and the real-time position of the UAVs corresponding to the total coverage area, the coverage loss score of the UAVs in each formation is calculated. Based on the heat map of the coverage sub-regions and global environmental field information distribution in each formation, as well as the real-time position of the ground UAVs corresponding to the coverage sub-regions, the coverage loss score of the ground UAVs in each formation is calculated. The coverage score of the airborne UAVs in each formation is added to the coverage score of the ground UAVs in each formation to obtain the global coverage loss at the current moment.

[0013] Furthermore, to achieve the above objectives, the present invention also proposes a regional coverage control device for air-to-ground unmanned aerial vehicle (UAV) formations, the regional coverage control device comprising: The area division module is used to determine the total monitoring area of ​​each formation based on the real-time location of the drones in the air within each formation; The region division module is also used to divide the total monitoring area according to the real-time position of the ground drones in each formation, so as to obtain the monitoring sub-regions of each ground drone. The coverage loss assessment module is used to calculate the edge coverage overlap loss of each formation based on the total regulatory area, regulatory sub-areas, and global environmental field information distribution heatmap of each formation. The control module is used to calculate the target position of each UAV in each formation based on the edge coverage overlap loss of each formation and the global environmental field information distribution heat map, and to control the UAV to move to the target position; The coverage loss assessment module is also used to calculate the global coverage loss at the current moment when the UAV completes its movement, and repeat the above steps until the global coverage loss meets the coverage loss convergence condition, so as to complete the global cooperative area coverage of various types of UAVs in multiple formations.

[0014] Furthermore, to achieve the above objectives, the present invention also proposes an area coverage control device for an air-to-ground unmanned aerial vehicle (UAV) formation. The area coverage control device for the air-to-ground UAV formation includes: a memory, a processor, and an area coverage control program for the air-to-ground UAV formation stored in the memory and executable on the processor. The area coverage control program for the air-to-ground UAV formation is configured to implement the steps of the area coverage control method for the air-to-ground UAV formation as described above.

[0015] Furthermore, to achieve the above objectives, the present invention also proposes a storage medium storing an area coverage control program for an air-to-ground UAV formation, wherein when the area coverage control program for the air-to-ground UAV formation is executed by a processor, the program implements the steps of the area coverage control method for the air-to-ground UAV formation as described above.

[0016] The present application proposes one or more technical solutions, which have at least the following technical effects: By comprehensively considering the real-time position and environmental factors of each UAV, the present invention dynamically adjusts the position of each type of UAV, effectively reducing coverage overlap and omission, enhancing the coverage coordination between formations, and combining economic benefits and practical value, providing strong support for the development of UAV swarm control technology. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the first embodiment of the area coverage control method for air-to-ground UAV formations of the present invention. Figure 2 This is a schematic diagram of the initial distribution of multiple UAV formations in the first embodiment of the air-to-ground UAV formation area coverage control method of the present invention; Figure 3 This is a schematic diagram of the overall regulatory area division process in the first embodiment of the air-to-ground UAV formation area coverage control method of the present invention; Figure 4 This is a flowchart illustrating the second embodiment of the area coverage control method for air-to-ground UAV formations of the present invention. Figure 5 This is a schematic diagram of the coverage area boundary structure of the second embodiment of the area coverage control method for air-to-ground UAV formation of the present invention; Figure 6 This is a flowchart illustrating the third embodiment of the area coverage control method for air-to-ground UAV formations of the present invention. Figure 7 This is a schematic diagram of a local boundary of the third embodiment of the air-to-ground UAV formation area coverage control method of the present invention; Figure 8 This is a structural block diagram of the first embodiment of the area coverage control device for air-to-ground UAV formation of the present invention; Figure 9 This is a schematic diagram of the structure of the area coverage control device for the air-to-ground UAV formation in the hardware operating environment involved in the embodiments of the present invention.

[0020] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0022] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0023] The main solution of this application embodiment is as follows: First, determine the total monitoring area of ​​each formation based on the real-time positions of the aerial drones in each formation. Second, divide the total monitoring area into sub-regions for each ground drone based on the real-time positions of the ground drones in each formation. Third, calculate the edge coverage overlap loss of each formation based on the total monitoring area, sub-regions, and global environmental field information distribution heatmap. Fourth, calculate the target position of each drone in each formation based on the edge coverage overlap loss and the global environmental field information distribution heatmap, and control the drone to move to the target position. Fifth, calculate the global coverage loss at the current moment when all drones have completed their movement, and repeat the above steps until the global coverage loss meets the coverage loss convergence condition, thereby achieving global collaborative area coverage of various types of drones within multiple formations.

[0024] Currently, in actual industrial production environments, drone swarms face numerous challenges in regional coverage tasks. In industrial inspections, the complex layout and numerous obstacles in large factories or industrial parks make traditional drone coverage methods prone to omissions or duplicate coverage, impacting inspection efficiency. In logistics monitoring, facing the real-time monitoring needs of warehouse areas, drone swarms often struggle to comprehensively monitor cargo status due to uneven coverage and insufficient dynamic adjustment. In environmental monitoring, the complex terrain and weather conditions in industrial parks or ecological reserves make it difficult for drone swarms to achieve efficient and uniform coverage, reducing data collection quality. How to improve coverage efficiency and quality, reduce duplicate coverage and omissions, and achieve efficient and uniform coverage in complex environments by dynamically adjusting the coverage area and target position of multiple swarms working collaboratively is a pressing technical problem that needs to be solved.

[0025] This application first roughly divides the coverage area using the real-time positions of each UAV according to a theoretically optimal coverage mathematical model (region partitioning model). Then, it finds the optimal coverage point within each UAV's corresponding region and controls each UAV to move to that point. After each UAV reaches its target position, the global coverage loss is calculated. If the coverage loss exceeds a convergence threshold, the three steps of region partitioning, optimal point selection, and coverage loss calculation are repeated. During this process, the partitioned regions and positions of each UAV continuously change until the global coverage loss stabilizes or other convergence conditions are met. The current UAV positions and region partitioning results are used as the final control result. Overall, this method can effectively solve the multi-squad cooperative coverage problem in complex environments, improve task execution efficiency, reduce operating costs, and has significant industrial application value.

[0026] It should be noted that the executing entity of this invention can be an area coverage control device for air-to-ground UAV formations, or a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or a thermal management device for an area coverage control device for air-to-ground UAV formations capable of the above functions. This embodiment does not specifically limit it in this way. The following uses an area coverage control device for air-to-ground UAV formations as an example to describe this embodiment and the following embodiments.

[0027] Based on this, embodiments of this application provide a method for area coverage control of air-to-ground UAV formations, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the area coverage control method for air-to-ground UAV formations in this application.

[0028] In this embodiment, the area coverage control method for the air-to-ground UAV formation includes steps S10 to S50: Step S10: Determine the total monitoring area for each formation based on the real-time location of the drones in each formation.

[0029] It is understood that the term "ground drone" in this application does not specifically refer to unmanned aerial vehicles (UAVs). For example, unmanned vehicles, robots, and unmanned boats can also be included. The specific operating methods are not limited. Although these devices operate in different spatial dimensions (such as ground, water, and air), they can still execute the area coverage control method for UAV formations described in this application through their own positioning systems. Furthermore, the air-to-ground UAVs in each formation can be of the same type or different types. The selection of UAV types within each formation is only related to the mission requirements of that formation and the overall mission requirements. The number of UAVs in each formation can also be flexibly determined according to mission requirements.

[0030] It should be noted that the real-time location of the aerial drones is a key basis for determining the overall monitoring area. By obtaining the precise location of each aerial drone, geometric algorithms can be used to divide the overall monitoring area of ​​each formation, ensuring that the distance from any point within each area to the drones in that formation is less than or equal to the distance to drones in other formations.

[0031] It should be understood that the aerial robot regulatory area model is as follows: V i (t) = {d∈D} G | ||d,P i (t)||≤||d,P h (t)||, i, h =1, 2,..., K, h≠i} In the above formula, Let i be the area under the supervision of aerial robot i at time t. It can be seen that the area under the supervision of aerial drone i will change dynamically as the location and time of the aerial drone change. Let d be the original ground region, that is, the spatial range containing all possible points d. According to the constraints on point d in the formula, d can be either a point on the boundary of this region or a point within the region. This indicates the position of aerial robot i at time t. For the neighboring aerial robot h at time t, the physical meaning of the above formula is the defined regulatory area. The distance from any point in the above region to the core of the formation's airborne UAV must be less than or equal to the distance to the core of the neighboring formation's airborne UAV.

[0032] like Figure 2 As shown, Figure 2 This is a schematic diagram of the initial distribution of multiple drone formations. In the initial state, the drones in each formation have not yet been divided into regions, and the positions of various types of drones are randomly distributed.

[0033] It is understandable that there is no limit to the number of aerial drones and ground drones in each formation. However, in this embodiment, the specific function of the aerial drones is to act as regulatory nodes to manage the ground drones in their respective formations in groups. After the area under the supervision of the aerial drones is divided, the area under the supervision of the aerial drones is then divided into sub-areas for each ground drone in the group. The aerial drones can then integrate the sub-areas to obtain the total area under the supervision of the formation.

[0034] It's important to note that the monitoring area for each aerial drone constitutes the team's total monitoring area. Based on this, the total area is further divided according to the number and location of the team's ground drones, resulting in each ground drone corresponding to a specific monitoring sub-area. For multiple teams, the total monitoring areas and the sub-areas will intersect at certain boundaries.

[0035] like Figure 3 As shown, Figure 3 This diagram illustrates the process of dividing the overall regulatory area for aerial drones. First, it shows the initial location distribution of the drones; at this point, the drones are in their initial state before any area division. Next, a geometric algorithm determines the regulatory boundary of each formation based on the real-time positions of each aerial drone, forming a preliminary regulatory area division. Subsequently, the drones gradually move towards their target positions according to calculated motion control parameters. Aerial drones adjust their positions to optimize coverage and connectivity with their subordinate ground drones, while ground drones adjust their positions to optimize coverage of the area boundaries. Finally, all types of drones complete their movement and stabilize at their target positions. At this point, the overall regulatory area division for each formation is complete, and each type of drone can efficiently execute tasks within its respective area, ensuring uniform coverage of the entire region.

[0036] Step S20: Based on the real-time location of the ground UAVs in each formation, the total monitoring area is divided to obtain the monitoring sub-areas for each ground UAV.

[0037] It should be noted that after each aerial drone completes the formation-level area division, the resulting division is the overall supervisory area of ​​the formation, also known as the total supervisory area. Based on this total supervisory area, each aerial drone assigns a sub-level supervisory area to each ground drone within the formation—this is the supervisory sub-area in this context. The real-time location of the ground drones is the key basis for dividing the supervisory sub-areas. By obtaining the precise location of each ground drone, a specific area division algorithm can be used to subdivide the total supervisory area into multiple sub-areas, ensuring that the distance from any point within each sub-area to its local ground drone is less than or equal to its distance to any other ground drone.

[0038] Understandably, the sub-area division for monitoring ground drones is dynamic and adjusts in real time as the location of the ground drones changes. This allows the entire system to adapt to changes in drone movement and mission requirements, ensuring that the coverage area of ​​each drone remains optimally configured when multiple formations are working together.

[0039] Step S30: Calculate the edge coverage overlap loss of each formation based on the total monitoring area, monitoring sub-areas, and global environmental field information distribution heatmap of each formation.

[0040] It should be noted that the edge coverage overlap loss reflects the degree of coverage overlap between adjacent formations in the boundary area. When calculating, it is necessary to comprehensively consider the total monitoring area and sub-areas of each formation, as well as the environmental field information distribution heat map, in order to quantify the impact of coverage overlap on the overall coverage effect.

[0041] Understandably, edge coverage overlap loss reflects the difference in coverage effectiveness between the current formation and its neighboring formations in the overlapping boundary regions. By calculating the coverage contribution difference for each local boundary and summing them, the edge coverage overlap loss for the entire formation can be obtained. This loss value quantifies the coverage effectiveness in the boundary region, providing a key indicator for the position adjustment of aerial and ground robots. By minimizing the edge coverage overlap loss, the coverage effectiveness of the entire formation can be optimized, ensuring more uniform and efficient coverage in the boundary region.

[0042] It should be understood that aerial robots Based on the motion state and environmental field information of the ground robots on the boundary of the supervised area of ​​their own team and neighboring teams, the edge coverage overlap loss is calculated as follows:

[0043] It is understandable that in the above formula: δ i That is, aerial robots The sum of the coverage contribution differences between the overlapping parts of each boundary and the other neighboring formation drones; i represents the aerial drones in this formation. This represents the position of UAV i in the air at time t; j represents the ground robot that shares the boundary area with the aerial robot h in this formation. This represents the position of ground-based UAV i at time t; h represents the aerial drones in the neighboring formation. This represents the position of UAV i in the air at time t; r represents a ground robot that shares a boundary area with aerial robot i in a neighboring formation. This represents the position of the ground-based UAV r at time t; h∈ This indicates that the integration process traverses all neighbor formations of aerial robot i; This represents the set of ground robots that intersect with the neighbor formation h of aerial robot i. Similarly, Let i represent the set of ground robots that intersect with the neighboring formation i of the aerial robot h; l ih This represents the boundary region formed by the formation containing aerial robot i and its neighboring formation h. Further, the local boundary region formed by the ground-based unmanned aerial vehicle (UAV) j is represented; Indicates the area The boundary; Indicates the area and region The intersecting parts; , indicating boundary and boundaries The intersecting parts; q represents the local boundary any point on, The function value of the environmental field information at point q; Step S40: Based on the edge coverage overlap loss of each formation and the global environmental field information distribution heatmap, calculate the target position of each UAV in each formation, and control the UAV to move to the target position.

[0044] In a feasible embodiment, the step of calculating the target position of each UAV in each formation based on the edge coverage overlap loss of each formation and the global environmental field information distribution heatmap, and controlling the UAV to move to the target position, includes steps A10 to A40: Step A10: Calculate the movement control parameters of each ground UAV based on its real-time location, the monitored sub-area of ​​the ground UAV, and the global environmental field information distribution heat map.

[0045] It should be noted that the global environmental field information distribution heatmap refers to a comprehensive situation map that quantitatively models and visualizes various key environmental elements (such as communication signal strength, weather conditions, terrain shading, and task demand density) in a grid or pixelated form within a wide-area task region. This heatmap forms a digital mapping of the entire operational environment through the fusion of multi-source heterogeneous data and dynamic spatiotemporal updates.

[0046] It is understandable that the method of this application is specifically applied to many large-scale drone swarm management application scenarios such as regional logistics distribution, agricultural plant protection, and disaster relief. Due to the large spatial range and the dispersed nature of the tasks to be performed in these scenarios, the content and intensity of the tasks to be performed at each location within the area will change dynamically. For example, in a disaster relief scenario, there may be unevenly distributed communication resource demands within the area. The corresponding communication support cluster will then dynamically allocate drone resources according to the task intensity at each location. Thus, in wide-area task execution, the intensity of environmental factors, the urgency of task demands, and the supply and demand matching degree of drone resources at each point within the area are all in a state of continuous change. It is necessary to perceive these changes in real time through a global environmental field information distribution heat map and drive the cluster to continuously and elastically reconstruct.

[0047] Step A20: Based on the movement control parameters of the ground UAV, control the ground UAV to move to the corresponding target location.

[0048] Step A30: Calculate the movement control parameters of each aerial drone based on the real-time location of the aerial drone, the total monitoring area of ​​the aerial drone, the edge coverage overlap loss of the corresponding formation of the aerial drone, and the global environmental field information distribution heat map.

[0049] Step A40: Based on the movement control parameters of the aerial drone, control the aerial drone to move to the corresponding target position.

[0050] It should be noted that the mobility control parameters for both ground-based and airborne UAVs are calculated based on their current status and environmental information to ensure that each UAV moves to the optimal position within its area of ​​responsibility, thereby achieving efficient area coverage. These parameters are dynamically adjusted and updated in real time to adapt to changes in the environment and mission requirements, optimizing coverage effectiveness.

[0051] The motion control parameters for ground-based unmanned aerial vehicles (UAVs) are:

[0052] The movement control parameters for an aerial drone are:

[0053] In the above formula, and These are the control input parameters for aerial robot i and ground robot j, respectively. and It is the control gain coefficient, used to adjust the strength of the control input; α and β are control parameters used to adjust the dynamic characteristics of the control input; It is a matrix representing the coverage contribution of aerial robot i; and These are the target positions of aerial robot i and ground robot j, respectively; and These are the current positions of aerial robot i and ground robot j, respectively. δ i It is the edge coverage overlap loss of the formation to which aerial robot i belongs; in, , Let q be the position of any point within the integration region. The function value of the environmental field information at point q.

[0054] Understandably, these control parameters, by comprehensively considering the drone's current location, coverage area, and environmental field information, can dynamically adjust the drone's direction of movement and speed, ensuring that it moves towards the optimal target location gradually and multiple times according to the set control coefficients, thereby steadily improving the overall coverage efficiency and quality through multiple movements.

[0055] It should be understood that these control commands are dynamically updated based on real-time location changes and environmental field functions within each coverage area. In addition, adjustments are made in real time to mitigate edge coverage overlap losses. This enables the entire system to respond to environmental changes and task requirements in real time, achieving efficient and uniform area coverage.

[0056] Step S50: When the UAV completes its movement, calculate the global coverage loss at the current moment, and repeat the above steps until the global coverage loss meets the coverage loss convergence condition, so as to complete the global cooperative area coverage of various types of UAVs in multiple formations.

[0057] In a feasible embodiment, calculating the global coverage loss at the current moment includes steps B10 to B30: Step B10: Calculate the coverage loss score of the UAVs in each formation based on the total coverage area, the global environmental field information distribution heat map, and the real-time position of the UAVs corresponding to the total coverage area.

[0058] Step B20: Calculate the coverage loss score of the ground UAVs in each formation based on the heat map of the coverage sub-regions and global environmental field information distribution in each formation, as well as the real-time position of the ground UAVs corresponding to the coverage sub-regions.

[0059] Step B30: Add the coverage scores of the aerial UAVs in each formation to the coverage scores of the ground UAVs in each formation to obtain the global coverage loss at the current moment.

[0060] It should be noted that global coverage loss is a key indicator for measuring the coverage effect of the entire drone formation. By comprehensively considering the coverage loss scores of both airborne and ground-based drones, the effectiveness and efficiency of the current coverage strategy can be fully evaluated.

[0061] It is understandable that the global coverage loss function model is as follows:

[0062] in, This represents the global coverage loss, used to quantify the coverage effect of the entire drone formation; Indicates the location of a point within the region; This represents the two-dimensional land area that the air-to-ground robot team needs to cover. Indicates the first Aerial robot Always The area under the responsibility of the superior; Indicates the first Aerial robot The position at that moment; Indicates the first Aerial robot Speed ​​of motion at any given moment; Indicates the first Aerial robot The input speed value at any given time; The sum of the number of aerial robots; Indicates the first A ground robot Always The area under the responsibility of the superior; Indicates the first A ground robot The position at that moment; Indicates aerial robot The set of serial numbers of the ground robots in the team; Indicates the first A ground robot Speed ​​of motion at any given moment; Indicates the first A ground robot The input speed value at any given time; The sum of the number of ground robots; Indicates position Environmental field function values; and It's the weight.

[0063] It should be noted that in the global coverage loss function model:

[0064] The outer summation represents summing the coverage loss over all K drone formations in total, i.e. This means that the loss of the entire system is the sum of the losses of all formations.

[0065] The left half of the inner integral function is as follows:

[0066] This represents the coverage loss score for the UAVs within the formation. Specifically, it is calculated as the weighted sum of squared distances from all points within the total coverage area of ​​UAV i at time t to the UAV's location. The weight α is used to adjust for the impact of this loss.

[0067] The right half of the inner integral function:

[0068] This represents the coverage loss score of the ground drones within the formation. Specifically, it is calculated as the weighted sum of the squared distances from all points within the coverage sub-region of ground drone j at time t to the drone's location. The weight β is used to adjust for the impact of this loss. Since a formation may contain multiple ground drones, it is necessary to accumulate the independent coverage loss scores of all ground drones.

[0069] It is understandable that by minimizing this loss function... This aims to optimize the deployment of drones and unmanned vehicles, enabling them to effectively cover the entire area while reducing the distance from points within the coverage area to the drones or unmanned vehicles, thereby improving coverage efficiency and quality.

[0070] Understandably, by repeatedly performing the above steps until the global coverage loss meets the convergence condition, the specific convergence condition can be a preset global coverage loss threshold or a relative rate of change. That is, when the rate of change of the global coverage loss is lower than a certain threshold, the loss is considered to have stabilized. For example, iteration can stop when the global coverage loss of two consecutive iterations is less than a preset convergence value. Another approach is to set a maximum number of iterations. To prevent infinite loops, a maximum number of iterations can be set. When the number of iterations reaches this threshold, iteration stops regardless of whether the global coverage loss meets other convergence conditions. This ensures that the UAV formation gradually optimizes the coverage effect in a dynamic environment, ultimately achieving the goal of efficient and uniform regional coverage.

[0071] It should be understood that this iterative optimization process not only improves coverage efficiency, but also enhances the system's adaptability to complex environments and dynamic tasks, ensuring coverage quality and stability when multiple formations work together.

[0072] This embodiment determines the total monitoring area of ​​each formation by the real-time position of each UAV in each formation, and divides the area into sub-regions according to the position of the ground UAVs. Then, by combining the division results with the distribution of global environmental field information, the coverage loss formed by each formation at the edge of the area is calculated. Based on the result, the UAVs are controlled to move to their respective optimal coverage positions. Finally, the global coverage loss is calculated, and the above steps are repeated until the global coverage loss reaches the convergence criterion, thereby completing the global collaborative area coverage of various types of UAVs in multiple formations.

[0073] In summary, this technical solution, by comprehensively considering the real-time location and environmental factors of each UAV, dynamically adjusts the position of each type of UAV, effectively reducing coverage overlap and omissions, enhancing coverage coordination between formations, and enabling collaborative operations of different types of UAVs within multiple formations.

[0074] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 4 Step S10 in the method for controlling the area coverage of air-to-ground UAV formations further includes steps S101 to S104: Step S101: The formations that have not been divided into regulatory areas are designated as the formations to be processed. Based on the real-time positions of the UAVs in the air within the formations to be processed, the corresponding neighbor formation queues are determined.

[0075] It should be noted that for any drone formation, its total monitoring area may intersect with the total monitoring areas of other formations. These two formations form neighbor formations. Furthermore, integrating all the neighbor formations of a certain formation together forms a neighbor formation queue.

[0076] Step S102: Take the real-time position of the UAV in the formation to be processed as the first base point, and take the real-time position of each UAV in the neighboring formation as the second base point.

[0077] It should be noted that the first base point is the real-time position of the UAV in the air within this formation, which serves as the basic reference point for determining the division of the supervision area of ​​this formation. The second base point is the real-time position of the UAV in the air within the neighboring formation, which is used as a reference point for determining the division of the supervision area of ​​the adjacent formation. The actual division of the area needs to ensure that the distance from any point in the area to the core of this formation is less than or equal to the distance to the core of the neighboring formation.

[0078] Step S103: Based on the first base point and the second base point, obtain the initial boundaries of multiple monitoring areas of the formation to be processed.

[0079] It should be noted that the boundary of the monitored area can be achieved by using the perpendicular bisector between two base points. Since the number of second base points is related to the number of neighboring formations, the initial number of perpendicular bisectors is not fixed. The area enclosed by these perpendicular bisectors is the target area of ​​this formation. Based on these base points, the monitored areas of each formation can be reasonably divided, ensuring that different formations can both cooperate and effectively cover the target area.

[0080] It should be understood that, in addition to determining the boundary based on the distance between base points, the process of determining the initial boundary can also be further optimized by considering other factors such as the communication parameters of each base point device, radiation intensity, or environmental characteristics of the base point's location. For example, the environmental characteristics of the base point's location, such as terrain and obstacle distribution, may also affect the division of the monitored area, and appropriate adjustments can be made in the specific initial boundary division process according to the specific task scenario.

[0081] Understandably, in this embodiment, the core objective of region division is to ensure that the distance from any point within a region to the core of the current formation (i.e., the first base point) is less than or equal to the distance to the core of the neighboring formation (i.e., the second base point). This division method ensures that each formation can effectively cover its assigned region and avoids situations where there are gaps in coverage or excessive overlap.

[0082] It should be understood that, based on these base points and vertical lines, the supervisory areas of each formation can be reasonably divided. Such division not only ensures coordinated operations between different formations but also effectively covers the target area, thereby achieving efficient operation of the entire UAV system.

[0083] like Figure 5 As shown, Figure 5 This is a schematic diagram illustrating the boundary structure of the coverage area in the air-to-ground UAV formation area coverage control method of the present invention.

[0084] It is understandable that, since the total monitoring area of ​​any formation is composed of multiple monitoring sub-areas corresponding to ground drones, the monitoring sub-areas that constitute the boundary of this formation and the monitoring sub-areas on the boundary of neighboring formations constitute neighboring monitoring sub-areas. Figure 3 Formations A, B, and C are adjacent to each other, and the overall monitoring area of ​​Formation A is divided into multiple monitoring sub-areas A1, A2, A3, etc., corresponding to each of its subordinate ground drones. Formations B and C are similar. Based on the boundary areas A3, B5, and C1, it can be seen that the distance from any two adjacent formations to the same boundary is the same.

[0085] Step S104: Based on the initial boundaries of the multiple regulatory areas and the total coverage target area, obtain the total regulatory area of ​​the formation to be processed.

[0086] It should be noted that the total coverage area refers to the restricted operating area of ​​all drones in the formation. In actual missions, it represents the area corresponding to the assigned mission. This area should be a general spatial range defined on the map, and the monitoring range of any drone in the formation participating in the mission is within this range.

[0087] It is understandable that the area enclosed by the initial boundaries of multiple regulatory zones is the total regulatory area corresponding to the drones in the formation. Based on this, the results need to be corrected by combining the total coverage area of ​​the target.

[0088] It should be understood that, since the mathematical essence of the aforementioned region division problem is to divide a certain region into multiple discrete points, and the division process only needs to consider the position of each discrete point and the overall area, the same technical principle will be used to divide the monitoring sub-regions of ground drones within their respective formations. Specifically, the ground robot monitoring region model is as follows:

[0089] In the above formula, The monitoring sub-area of ​​ground drones j under the command of aerial robot i at time t; Let j be the position of the ground robot at time t; Let r be the position of the neighboring ground robot at time t; the physical meaning of the above formula is that the distance from any point in the divided area to the core of the sub-region must be less than or equal to the distance to the core of the neighboring sub-region.

[0090] In this embodiment, the neighboring formation queue is determined by the real-time position of the UAVs in the formation to be processed; the positions of the UAVs in the current formation and the neighboring formation are respectively used as the first and second base points; the initial boundary is determined based on the perpendicular bisector between the base points to divide the monitoring area; and the final total monitoring area is obtained by combining the total coverage area.

[0091] In summary, this embodiment achieves a reasonable division of regions through the above steps, ensuring that each formation can both cooperate and effectively cover the target area. This method effectively reduces coverage gaps and overlaps between regions, is clear and easy to implement, suitable for complex task scenarios, and effectively improves operational efficiency. Furthermore, the region division and control method of this solution can be extended to other multi-robot collaborative tasks, demonstrating good versatility and scalability.

[0092] Based on the first embodiment of this application, in the third embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 6Step S30 further includes steps S301 to S304: Step S301: Determine the boundary area of ​​each formation based on the total monitoring area of ​​each formation and the monitoring sub-areas of the ground drones under each formation.

[0093] It should be noted that the boundary area of ​​each formation is determined by the boundary between the overall monitoring area of ​​the formation and the monitoring sub-areas of each ground drone. Figure 5 For example, Figure 5 In the A formation, A1 to A6 are ground drones related to the boundary, while A7 is not related to the boundary of the overall area and therefore does not participate in subsequent steps. For any formation covering the overall area, if the area corresponding to a part of the ground drones is directly adjacent to the area covered by other formations, then the area corresponding to this part of the ground drones symbolizes the boundary area of ​​this formation. Each ground drone's area symbolizes a local boundary area. Taking the A formation in the figure as an example, the boundary area of ​​the A formation includes six local boundary areas, A1 to A6.

[0094] It is understandable that the boundary area is composed of multiple sub-areas under the jurisdiction of ground drones.

[0095] Step S302: Based on the real-time position of each formation of ground UAVs and the boundary area of ​​each formation, determine the neighboring ground UAVs corresponding to each ground UAV in the boundary area.

[0096] It should be noted that, based on the real-time location and boundary area of ​​each formation of ground UAVs, the neighboring ground UAVs of each ground UAV in the boundary area can be identified. The coverage of the neighboring ground UAVs may overlap with or require coordination with the coverage of the current UAV.

[0097] Step S303: Based on the global environmental field information distribution heat map, calculate the coverage contribution difference between the ground UAV and its corresponding neighboring ground UAV in the overlapping part of the boundary region.

[0098] It's important to note that a global environmental field information distribution heatmap is a tool used to visually display the importance or coverage requirements of various points in the environment. It reflects the spatial distribution of environmental field information through color or grayscale variations. Darker colors indicate higher importance or coverage requirements for the area, while lighter colors indicate lower requirements. In multi-UAV collaborative coverage missions, this heatmap is generated by each ground UAV collecting data and uploading the raw data within its sensing range back to the cloud system. The cloud system then creates a global map based on the positions of each ground UAV and the locations of the collected data. This map provides crucial environmental information guidance for subsequent UAV position adjustments, helping them identify key coverage areas and optimize their own positions and coverage ranges, thereby improving coverage efficiency and quality.

[0099] In a feasible embodiment, the step of calculating the coverage contribution difference between the ground UAV and its corresponding neighboring ground UAV in the overlapping part of the boundary region based on the global environmental field information distribution heat map includes steps C10 to C60: Step C10: Determine the local boundary of the ground drone combination based on the monitoring sub-region corresponding to the ground drone and the monitoring sub-region of the corresponding neighboring drone.

[0100] like Figure 7 As shown, Figure 7 This is a schematic diagram of a local boundary of the third embodiment of the air-to-ground UAV formation area coverage control method of the present invention.

[0101] Understandable, Figure 5 The overall boundary region is composed of multiple local boundaries (e.g., boundary 1, boundary 2). Each local boundary corresponds to a set of monitoring sub-regions of ground drones that are neighbors. Boundary 1 corresponds to ground drones j1 and r1, and boundary 2 corresponds to ground drones j2 and r2.

[0102] Step C20: Determine the environmental field information of the local boundary based on the global environmental field information distribution heat map.

[0103] Understandably, by directly retrieving the data from the global environmental field information distribution heatmap based on the spatial location of the boundary region, the function value corresponding to the environmental field information at any point on the local boundary can be obtained.

[0104] Step C30: Based on the environmental field information of the local boundary, the real-time positions of the ground UAVs under the formation, and the real-time positions of the air UAVs in the formation, determine the coverage contribution of the formation at the local boundary.

[0105] It should be noted that the specific coverage contribution satisfies the following formula: Coverage contribution ε j= ； Where, ε j This indicates the coverage contribution of ground UAV j in this formation to the local boundary area; This refers to the local boundary of the ground UAV j belonging to this formation within the boundary area formed by the UAV i in this formation and the UAV h in the neighboring formation. This indicates the real-time position of UAV i in this formation at time t; This indicates the real-time position of the neighboring formation's aerial drone h at time t; Let represent the real-time position of ground UAV j corresponding to the boundary portion of this formation at time t; q represents any point on the local boundary. The function value represents the environmental field information at point q.

[0106] Understandably, the coverage contribution of a local boundary area refers to a measure of the coverage effect provided by drones or unmanned vehicles (UAVs) for monitoring or providing services based on environmental functions within a specific local boundary area. This measure is typically evaluated by calculating the distance from each point in the area to the nearest drone or UAV and incorporating a weighted function of environmental factors to assess the uniformity and adequacy of coverage. Generally, boundary areas are usually covered by ground-based drones on both sides simultaneously. However, the actual coverage contributions of the two sides will differ due to differences in the distance of the drones from the boundary, environmental field information, and other factors. Therefore, for boundary areas, the existence of differences means that the coverage effect can be balanced by further optimizing the drone positions. Extending from points to areas, overall coverage performance can be improved by optimizing the difference in coverage contribution of the global coverage boundary areas.

[0107] Step C40: Based on the environmental field information of the local boundary, the real-time positions of the neighboring ground UAVs under the neighboring formation, and the real-time positions of the neighboring aerial UAVs in the neighboring formation, determine the coverage contribution of the neighboring formation at the local boundary.

[0108] Step C50: Based on the coverage contribution of the current formation at the local boundary and the coverage contribution of the neighboring formation at the local boundary, obtain the coverage contribution difference of the current formation at the local boundary.

[0109] Understandably, considering the balance of data collection quality, the coverage contribution of ground drones on both sides of the same boundary should be as close as possible to meet the balance requirements. This balance helps ensure that ground drones in all areas maintain uniform coverage of the boundary area, avoiding situations where one side has strong coverage and the other side has weak coverage, thereby improving the coverage quality and data collection accuracy of the entire area.

[0110] Step C60: Repeat the above steps until the coverage contribution difference of all local boundaries in the overlapping boundary portion is obtained. The coverage contribution difference of the local boundaries is accumulated to obtain the coverage contribution difference of the overlapping boundary portion.

[0111] Understandably, the formula for the above summation process is as follows:

[0112] in, This represents the sum of the coverage contribution differences between aerial drone i and its neighboring drones in the overlapping areas of each boundary. , This represents the set of local boundary regions formed by aerial drones i and j.

[0113] It should be understood that the formula calculates the sum of coverage contribution differences by comparing the coverage contributions of the current formation and neighboring formations in the overlapping boundary area. This sum of differences provides a crucial basis for UAVs to adjust their positions to optimize coverage. By minimizing... This method can improve the coverage uniformity of the boundary area, thereby enhancing the coverage performance of the entire system. It fully considers the distribution of environmental field information and the positional relationship of the UAV, providing theoretical support for achieving efficient collaborative coverage control.

[0114] Step S304: Calculate the edge coverage overlap loss of each formation based on the coverage contribution difference of the overlapping boundary portion.

[0115] Understandably, edge coverage overlap loss reflects the difference in coverage effect between the current formation and its neighboring formations in the overlapping boundary regions. By calculating the coverage contribution difference for each local boundary and summing them up, the edge coverage overlap loss for the entire formation can be obtained. This loss value quantifies the coverage effect in the boundary region, providing a key indicator for the position adjustment of aerial and ground robots. Using this value as a basis for subsequent position adjustments of individual drones to minimize the edge coverage overlap loss can optimize the coverage effect of all formations globally, ensuring more uniform and efficient coverage in the boundary region.

[0116] In this embodiment, by monitoring the overall area of ​​each formation and its subordinate ground UAV monitoring sub-areas, the boundary areas of each formation are accurately located, excluding ground UAVs unrelated to the overall area boundary. Secondly, by combining the real-time positions of the ground UAVs with the boundary areas, neighboring UAVs corresponding to each UAV within the boundary area are identified. Then, based on a global environmental field information distribution heatmap, the coverage contribution difference of UAVs in the overlapping boundary areas is calculated to balance data acquisition quality. Finally, using the coverage contribution difference of the overlapping boundary areas, the edge coverage overlap loss of each formation is calculated, providing a basis for UAV position adjustments.

[0117] In summary, this embodiment effectively improves coverage efficiency and quality. By accurately delineating boundary areas and identifying neighboring drones, it avoids coverage gaps and overlaps, ensuring uniform coverage of boundary areas. Furthermore, by utilizing environmental field information distribution heatmaps, drones can perceive environmental changes in real time and dynamically adjust coverage strategies, enhancing system flexibility and adaptability. In addition, the calculated edge coverage overlap loss provides a crucial reference for drone position optimization, contributing to further improvements in coverage uniformity and overall system performance. This process not only ensures effective coverage of boundary areas but also provides a scientific and systematic solution for collaborative coverage tasks involving multiple drone formations.

[0118] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the area coverage control method of the air-to-ground UAV formation in this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0119] This application also provides a regional coverage control device for air-to-ground UAV formations; please refer to... Figure 8 The area coverage control device for the air-to-ground UAV formation includes: The area division module 10 is used to determine the total monitoring area of ​​each formation based on the real-time location of the drones in each formation. The region division module 10 is also used to divide the total monitoring area according to the real-time position of the ground UAVs in each formation, so as to obtain the monitoring sub-regions of each ground UAV. The coverage loss assessment module 20 is used to calculate the edge coverage overlap loss of each formation based on the total regulatory area, regulatory sub-area, and global environmental field information distribution heat map of each formation. The control module 30 is used to calculate the target position of each UAV in each formation based on the edge coverage overlap loss of each formation and the global environmental field information distribution heat map, and to control the UAV to move to the target position. The coverage loss assessment module 20 is also used to calculate the global coverage loss at the current moment when the UAV completes its movement, and repeat the above steps until the global coverage loss meets the coverage loss convergence condition, so as to complete the global cooperative area coverage of various types of UAVs in multiple formations.

[0120] In one embodiment, the region division module 10 is further configured to: classify formations that have not undergone regulatory region division as formations to be processed; determine the corresponding neighbor formation queues based on the real-time positions of the UAVs in the formations to be processed; use the real-time positions of the UAVs in the formations to be processed as first base points, and use the real-time positions of the UAVs in each formation in the neighbor formation queues as second base points; obtain multiple initial boundaries of regulatory regions for the formations to be processed based on the first and second base points; obtain the total regulatory region of the formations to be processed based on the multiple initial boundaries of regulatory regions and the total coverage area; repeat the above steps until there are no formations that have not undergone total regulatory region construction, thereby determining the total regulatory region of each formation.

[0121] In one embodiment, the coverage loss assessment module 20 is further configured to: determine the boundary area of ​​each formation based on the total monitoring area of ​​each formation and the monitoring sub-areas of the ground drones under each formation, wherein the boundary area is composed of a combination of monitoring sub-areas corresponding to the ground drones under multiple formations; determine the neighboring ground drones corresponding to each ground drone in the boundary area based on the real-time position of the ground drones in each formation and the boundary area of ​​each formation; calculate the coverage contribution difference between the ground drones in the boundary area and their corresponding neighboring ground drones in the overlapping part of the boundary based on the global environmental field information distribution heat map; and calculate the edge coverage overlap loss of each formation based on the coverage contribution difference in the overlapping part of the boundary.

[0122] In one embodiment, the coverage loss assessment module 20 is further configured to: determine the local boundary of the ground UAV group based on the monitoring sub-area corresponding to the ground UAV and the monitoring sub-area of ​​the corresponding neighboring UAVs; determine the environmental field information of the local boundary based on the global environmental field information distribution heatmap; determine the coverage contribution of the formation at the local boundary based on the environmental field information of the local boundary, the real-time position of the ground UAVs under the formation, and the real-time position of the air UAVs under the formation; determine the coverage contribution of the neighboring formation at the local boundary based on the environmental field information of the local boundary, the real-time position of the neighboring ground UAVs under the neighboring formation, and the real-time position of the air UAVs under the neighboring formation; obtain the coverage contribution difference of the formation at the local boundary based on the coverage contribution of the formation at the local boundary and the coverage contribution of the neighboring formation at the local boundary; repeat the above steps until the coverage contribution difference of all local boundaries in the overlapping boundary portion is obtained, and accumulate the coverage contribution difference of the local boundaries to obtain the coverage contribution difference of the overlapping boundary portion.

[0123] In one embodiment, the coverage loss assessment module 20 is further configured to determine the coverage contribution of local boundaries according to the following formula: Coverage contribution ε j = ; Where, ε j This represents the coverage contribution of ground UAV j in this formation to the area where the local boundary is located, at the local boundary. t is the local boundary of the ground UAV j under the command of this formation within the boundary region formed by the UAV i in this formation and the UAV h in the neighboring formation, and t is the time point corresponding to the current calculation. This indicates the real-time position of UAV i in this formation at time t; This indicates the real-time position of the neighboring formation's aerial drone h at time t; This indicates the real-time position of the ground UAV j corresponding to the boundary portion of this formation at time t; Let q be any point on the local boundary. The function value represents the environmental field information at point q.

[0124] In one embodiment, the control module 30 is further configured to calculate the movement control parameters of each ground UAV based on the real-time position of the ground UAV, the monitored sub-area of ​​the ground UAV, and the global environmental field information distribution heat map; control the ground UAV to move to the corresponding target position based on the movement control parameters of the ground UAV; calculate the movement control parameters of each air UAV based on the real-time position of the air UAV, the total monitored area of ​​the air UAV, the edge coverage overlap loss of the corresponding formation of the air UAV, and the global environmental field information distribution heat map; and control the air UAV to move to the corresponding target position based on the movement control parameters of the air UAV.

[0125] In one embodiment, the control module 30 is further configured to calculate the coverage loss score of the airborne UAVs in each formation based on the total coverage area in each formation, the global environmental field information distribution heat map, and the real-time position of the airborne UAVs corresponding to the total coverage area; calculate the coverage loss score of the ground UAVs in each formation based on the coverage sub-regions in each formation, the global environmental field information distribution heat map, and the real-time position of the ground UAVs corresponding to the coverage sub-regions; and sum the coverage scores of the airborne UAVs in each formation with the coverage scores of the ground UAVs in each formation to obtain the global coverage loss at the current moment.

[0126] This embodiment first roughly divides the coverage area according to the theoretically optimal coverage mathematical model (region partitioning model) based on the real-time positions of each UAV. Then, it finds the optimal coverage point within the corresponding region for each UAV and controls each UAV to move to the corresponding optimal coverage point. After each UAV reaches the target position, the global coverage loss is calculated. If the coverage loss exceeds the convergence threshold, the three steps of region partitioning, optimal point selection, and coverage loss calculation are repeated. During this process, the partitioned regions and positions of each UAV will continuously change until the global coverage loss tends to stabilize or other convergence conditions are met. The current position of each UAV and the region partitioning result are used as the final control result. Overall, this method can effectively solve the multi-squad cooperative coverage problem in complex environments, improve task execution efficiency, reduce operating costs, and has significant industrial application value.

[0127] The area coverage control device for air-to-ground UAV formations provided in this application adopts the area coverage control method for air-to-ground UAV formations in the above embodiments. It can solve the technical problem of how to improve coverage efficiency and quality, reduce redundant coverage and missed areas, and achieve efficient and uniform coverage in complex environments by dynamically adjusting the coverage area and target position of UAVs during multi-formation collaborative operations. Compared with the prior art, the beneficial effects of the area coverage control device for air-to-ground UAV formations provided in this application are the same as those of the area coverage control method for air-to-ground UAV formations provided in the above embodiments, and other technical features in the area coverage control device for air-to-ground UAV formations are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0128] This application provides an area coverage control device for an air-to-ground unmanned aerial vehicle (UAV) formation. The area coverage control device for the air-to-ground UAV formation includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the area coverage control method for the air-to-ground UAV formation in the above embodiment 1.

[0129] The following is for reference. Figure 9 This document illustrates a schematic diagram of a regional coverage control device suitable for implementing air-to-ground drone formations in the embodiments of this application. The regional coverage control device for air-to-ground drone formations in the embodiments of this 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 Description), PMPs (Portable Media Players), vehicle-mounted terminals (e.g., vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 9 The area coverage control device for the air-to-ground drone formation shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0130] like Figure 9As shown, the area coverage control device for an air-to-ground UAV formation may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the area coverage control device for the air-to-ground UAV formation. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the area coverage control equipment of an air-to-ground UAV formation to exchange data wirelessly or via wired communication with other devices. Although the figure shows an area coverage control equipment for an air-to-ground UAV formation with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems may be implemented alternatively.

[0131] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0132] The area coverage control device for air-to-ground UAV formations provided in this application, employing the area coverage control method for air-to-ground UAV formations described in the above embodiments, can solve the technical problem of how to improve coverage efficiency and quality, reduce redundant coverage and missed areas, and achieve efficient and uniform coverage in complex environments by dynamically adjusting the coverage area and target position of UAVs during multi-formation collaborative operations. Compared with the prior art, the beneficial effects of the area coverage control device for air-to-ground UAV formations provided in this application are the same as those of the area coverage control method for air-to-ground UAV formations provided in the above embodiments, and other technical features in this area coverage control device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0133] It should be understood that the various parts disclosed in this application can be implemented using 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 suitable manner in one or more embodiments or examples.

[0134] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0135] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the area coverage control method for air-to-ground UAV formations in the above embodiments.

[0136] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. 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 conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0137] The aforementioned computer-readable storage medium may be included in the area coverage control equipment of the air-to-ground UAV formation; or it may exist independently and not be assembled into the area coverage control equipment of the air-to-ground UAV formation.

[0138] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the area coverage control device of the air-to-ground UAV formation, the area coverage control device causes the air-to-ground UAV formation to: determine the total monitoring area of ​​each formation based on the real-time positions of the airborne UAVs in each formation; divide the total monitoring area into monitoring sub-areas for each ground UAV based on the real-time positions of the ground UAVs in each formation; calculate the edge coverage overlap loss of each formation based on the total monitoring area, monitoring sub-areas, and global environmental field information distribution heatmap; calculate the target position of each UAV in each formation based on the edge coverage overlap loss and global environmental field information distribution heatmap, and control the UAV to move to the target position; and calculate the global coverage loss at the current moment when the UAV completes its movement, repeating the above steps until the global coverage loss meets the coverage loss convergence condition, thereby completing the global cooperative area coverage of various types of UAVs within multiple formations.

[0139] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0140] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0141] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0142] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., computer programs) for executing the aforementioned area coverage control method for air-to-ground UAV formations. This method addresses the technical problem of how to improve coverage efficiency and quality, reduce redundant coverage and missed areas, and achieve efficient and uniform coverage in complex environments by dynamically adjusting the coverage area and target position of UAVs during multi-formation collaborative operations. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the area coverage control method for air-to-ground UAV formations provided in the above embodiments, and will not be elaborated upon here.

[0143] The computer program product provided in this application can solve the technical problem of area coverage control for air-to-ground UAV formations. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the area coverage control method for air-to-ground UAV formations provided in the above embodiments, and will not be repeated here.

[0144] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for area coverage control of an air-to-ground unmanned aerial vehicle (UAV) formation, characterized in that, The area coverage control method for the air-to-ground UAV formation includes: Based on the real-time location of the drones in each formation, determine the total monitoring area for each formation; Based on the real-time location of the ground drones in each formation, the total monitoring area is divided to obtain the monitoring sub-areas for each ground drone. Based on the heat map of the total monitoring area, sub-monitoring area, and global environmental field information distribution of each formation, calculate the edge coverage overlap loss of each formation; The calculation of edge coverage overlap loss for each formation based on the total monitoring area, sub-monitoring area, and global environmental field information distribution heatmap of each formation includes: Based on the total monitoring area of ​​each formation and the monitoring sub-areas of the ground drones under each formation, the boundary area of ​​each formation is determined, wherein the boundary area is composed of the combination of the monitoring sub-areas corresponding to the ground drones under the formation. Based on the real-time position of each formation of ground UAVs and the boundary area of ​​each formation, determine the neighboring ground UAVs corresponding to each ground UAV in the boundary area; Based on the global environmental field information distribution heat map, calculate the difference in coverage contribution between the ground UAV and its corresponding neighboring ground UAV in the overlapping part of the boundary region; Based on the difference in coverage contribution of the overlapping boundary portions, calculate the edge coverage overlap loss for each formation; The step of calculating the coverage contribution difference between a ground-based UAV and its corresponding neighboring ground-based UAV in the overlapping portion of the boundary region based on the global environmental field information distribution heatmap includes: The local boundary of the ground drone combination is determined based on the monitoring sub-region corresponding to the ground drone and the monitoring sub-region corresponding to the neighboring drones. Based on the global environmental field information distribution heatmap, the environmental field information of the local boundary is determined; Based on the environmental field information of the local boundary, the real-time positions of the ground UAVs under the formation, and the real-time positions of the air UAVs in the formation, the coverage contribution of the formation at the local boundary is determined. Based on the environmental field information of the local boundary, the real-time positions of the neighboring ground UAVs under the neighboring formation, and the real-time positions of the neighboring aerial UAVs in the neighboring formation, the coverage contribution of the neighboring formation at the local boundary is determined. The difference in coverage contribution of the current formation at the local boundary is obtained based on the coverage contribution of the current formation at the local boundary and the coverage contribution of the neighboring formation at the local boundary. Repeat the above steps until the coverage contribution difference of all local boundaries in the overlapping boundary portion is obtained. Then, sum up the coverage contribution differences of the local boundaries to obtain the coverage contribution difference of the overlapping boundary portion. Based on the edge coverage overlap loss of each formation and the global environmental field information distribution heatmap, the target position of each UAV in each formation is calculated, and the UAV is controlled to move to the target position. When the UAV completes its movement, the global coverage loss at the current moment is calculated. The above steps are repeated until the global coverage loss meets the coverage loss convergence condition, so as to complete the global cooperative area coverage of various types of UAVs in multiple formations.

2. The area coverage control method for air-to-ground UAV formations according to claim 1, characterized in that, The determination of the total monitoring area for each formation based on the real-time positions of the drones in each formation includes: Formations without defined regulatory areas are designated as pending formations, and the corresponding neighboring formation queues are determined based on the real-time positions of the drones within the pending formations. The real-time position of the UAV in the formation to be processed is taken as the first base point, and the real-time position of each UAV in the neighboring formation queue is taken as the second base point. Based on the first base point and the second base point, the initial boundaries of multiple regulatory areas of the formation to be processed are obtained; Based on the initial boundaries of the multiple regulatory areas and the total coverage target area, the total regulatory area of ​​the formation to be processed is obtained. The above steps are repeated until there are no formations that have not had their total regulatory area constructed, so as to determine the total regulatory area of ​​each formation.

3. The area coverage control method for air-to-ground UAV formations according to claim 1, characterized in that, The coverage contribution of the local boundary satisfies the following formula: Coverage contribution ε j = ; Where, ε j This represents the coverage contribution of ground UAV j in this formation to the area where the local boundary is located, at the local boundary. t is the local boundary of the ground UAV j under the command of this formation within the boundary region formed by the UAV i in this formation and the UAV h in the neighboring formation, and t is the time point corresponding to the current calculation. This indicates the real-time position of UAV i in this formation at time t; This indicates the real-time position of the neighboring formation's aerial drone h at time t; This indicates the real-time position of the ground UAV j corresponding to the boundary portion of this formation at time t; Let q be any point on the local boundary. The function value represents the environmental field information at point q.

4. The area coverage control method for air-to-ground UAV formations according to claim 1, characterized in that, The step of calculating the target position of each UAV in each formation based on the edge coverage overlap loss of each formation and the global environmental field information distribution heatmap, and controlling the UAV to move to the target position, includes: Based on the real-time location of the ground UAV, the monitored sub-area of ​​the ground UAV, and the global environmental field information distribution heat map, the movement control parameters of each ground UAV are calculated. Based on the movement control parameters of the ground UAV, control the ground UAV to move to the corresponding target position; Based on the real-time location of the aerial drones, the total monitoring area of ​​the aerial drones, the edge coverage overlap loss of the corresponding formation of the aerial drones, and the global environmental field information distribution heat map, the movement control parameters of each aerial drone are calculated. Based on the movement control parameters of the aerial drone, the aerial drone is controlled to move to the corresponding target location.

5. The area coverage control method for air-to-ground UAV formations according to claim 1, characterized in that, The calculation of the global coverage loss at the current moment includes: Based on the heat map of the total coverage area, global environmental field information distribution in each formation, and the real-time position of the UAVs corresponding to the total coverage area, the coverage loss score of the UAVs in each formation is calculated. Based on the heat map of the coverage sub-regions and global environmental field information distribution in each formation, as well as the real-time position of the ground UAVs corresponding to the coverage sub-regions, the coverage loss score of the ground UAVs in each formation is calculated. The coverage score of the airborne UAVs in each formation is added to the coverage score of the ground UAVs in each formation to obtain the global coverage loss at the current moment.

6. A regional coverage control device for air-to-ground unmanned aerial vehicle (UAV) formations, characterized in that, The area coverage control device for the air-to-ground UAV formation includes: The area division module is used to determine the total monitoring area of ​​each formation based on the real-time location of the drones in the air within each formation; The region division module is also used to divide the total monitoring area according to the real-time position of the ground drones in each formation, so as to obtain the monitoring sub-regions of each ground drone. The coverage loss assessment module is used to calculate the edge coverage overlap loss of each formation based on the total regulatory area, regulatory sub-areas, and global environmental field information distribution heatmap of each formation. The coverage loss assessment module is further configured to: determine the boundary area of ​​each formation based on the total monitoring area of ​​each formation and the monitoring sub-areas of the ground drones under each formation, wherein the boundary area is composed of a combination of monitoring sub-areas corresponding to the ground drones under multiple formations; determine the neighboring ground drones corresponding to each ground drone in the boundary area based on the real-time positions of the ground drones in each formation and the boundary areas of each formation; calculate the coverage contribution difference between the ground drones in the boundary area and their corresponding neighboring ground drones in the overlapping part of the boundary based on the global environmental field information distribution heatmap; and calculate the edge coverage overlap loss of each formation based on the coverage contribution difference in the overlapping part of the boundary. The coverage loss assessment module is further configured to: determine the local boundary of the ground UAV group based on the monitored sub-area corresponding to the ground UAV and the monitored sub-area of ​​the corresponding neighboring UAVs; determine the environmental field information of the local boundary based on the global environmental field information distribution heatmap; determine the coverage contribution of the formation at the local boundary based on the environmental field information of the local boundary, the real-time position of the ground UAVs under the formation, and the real-time position of the air UAVs under the formation; determine the coverage contribution of the neighboring formation at the local boundary based on the environmental field information of the local boundary, the real-time position of the neighboring ground UAVs under the neighboring formation, and the real-time position of the air UAVs under the neighboring formation; obtain the coverage contribution difference of the formation at the local boundary based on the coverage contribution of the formation at the local boundary and the coverage contribution of the neighboring formation at the local boundary; repeat the above steps until the coverage contribution difference of all local boundaries in the overlapping boundary portion is obtained, and accumulate the coverage contribution difference of the local boundaries to obtain the coverage contribution difference of the overlapping boundary portion. The control module is used to calculate the target position of each UAV in each formation based on the edge coverage overlap loss of each formation and the global environmental field information distribution heat map, and to control the UAV to move to the target position; The coverage loss assessment module is also used to calculate the global coverage loss at the current moment when the UAV completes its movement, and repeat the above steps until the global coverage loss meets the coverage loss convergence condition, so as to complete the global cooperative area coverage of various types of UAVs in multiple formations.

7. A regional coverage control device for air-to-ground unmanned aerial vehicle (UAV) formations, characterized in that, The area coverage control device for the air-to-ground drone formation includes: a memory, a processor, and an area coverage control program for the air-to-ground drone formation stored in the memory and executable on the processor, wherein the area coverage control program for the air-to-ground drone formation is configured to implement the steps of the area coverage control method for the air-to-ground drone formation as described in any one of claims 1 to 5.

8. A storage medium, characterized in that, The storage medium stores a regional coverage control program for an air-to-ground UAV formation, which, when executed by a processor, implements the steps of the regional coverage control method for an air-to-ground UAV formation as described in any one of claims 1 to 5.

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