Target area division and sub-area coverage route planning method and system thereof

Abstract

The present disclosure relates to a target area division and sub-area coverage route planning method and system thereof, the method comprising the following steps: taking a target area definition as the main input parameter, determining the minimum circumscribed rectangle of the target area; preferably covering the unit size level, and calculating the best overall displacement, thereby dividing the covering unit set, so that the number of covering units and the effective coverage rate are optimized; for each covering unit, according to whether it is completely in the target area, using a prefabricated route as a coverage route, or calculating the best grid overall displacement and optimizing the coverage route; all covering units of the target area and their coverage routes and costs are output as the final result. The present disclosure is aimed at the task division and route planning problem of multi-unmanned aerial vehicle executing large-scale complex shape area coverage search task, which realizes problem simplification, reduces calculation scale, and reduces solving difficulty, thereby improving task execution efficiency and reducing task cost.

Description

Technical Field

[0001] This disclosure relates to the field of planning multi-UAV collaborative systems, specifically to a method and system for target area division and sub-area coverage route planning. Background Technology

[0002] Unmanned aerial vehicles (UAVs) have successfully matured, diversified, and become civilian-use products, widely applied in various fields. In applications such as military reconnaissance, precision agriculture, environmental monitoring, and security patrols, thanks to their flexible and convenient flight capabilities, UAVs can carry operational resources and overcome the mobility limitations of ground transportation to complete long-distance operations. They are an efficient means of performing area coverage search missions such as aerial reconnaissance, border patrol, criminal investigation search, forest fire prevention, and farmland spraying. Furthermore, with the rapid development of unmanned intelligent equipment technology, it has become possible to use multi-UAV collaborative systems composed of multiple UAVs to perform certain complex tasks. Through reasonable scheduling, the UAVs in a multi-UAV collaborative system can cooperate with each other, overcoming the shortcomings of single UAVs such as small coverage area and insufficient operational resources / endurance, greatly improving the execution efficiency of large-area area coverage search missions. Moreover, by optimizing route planning, the flexibility and maneuverability of each UAV can be fully utilized, making collaborative coverage search of complex-shaped areas possible. Therefore, multi-UAV collaborative systems have become an ideal mode for performing large-area complex-shaped area coverage search missions. Therefore, in recent years, many research institutions and companies have conducted extensive discussions, research and experiments on the application of multi-UAV collaborative systems in regional search, aerial reconnaissance, regional patrol and agricultural spraying and other regional coverage search missions.

[0003] Reasonable task allocation and optimized route planning are crucial for the successful completion of area coverage search tasks by multi-UAV collaborative systems. Reasonable task allocation balances the operational benefits and time and resource costs among UAVs; optimized route planning improves the ratio of operational benefits to costs for each UAV, thereby increasing the efficiency and reducing the cost of the multi-UAV collaborative system. However, for coverage search tasks in large, complex-shaped areas, directly performing task allocation and route planning results in an enormous problem scale, making it unsolvable. After dividing the target area and planning sub-region coverage routes, the task allocation and route planning problem for large, complex-shaped area coverage search tasks can be simplified into a UAV-sub-region allocation problem (how to allocate sub-regions to each UAV) and a UAV coverage route combination problem (for any given UAV, how to connect the coverage routes of the sub-regions assigned to it), significantly reducing the computational scale and making the problem solvable. Therefore, for large, complex-shaped area coverage search tasks, the division of the target area and the planning of sub-region coverage routes are crucial.

[0004] To ensure that the task allocation and route planning for large-scale, complex-shaped area coverage search tasks can effectively reduce the problem size while avoiding significant optimization losses after target area division and sub-region coverage path planning, the target area division and sub-region coverage path planning need to meet the following requirements: 1) The costs and benefits of each sub-region after division are similar (i.e., the areas of each sub-region are similar); 2) The cost of the sub-region matches the UAV's endurance and operational resources (i.e., the area of ​​the sub-region is similar to the UAV's maximum range or maximum operational area); 3) The coverage route within the sub-region should maximize the ratio of benefits to costs (i.e., the movement segments without operational benefits within the coverage route within the sub-region should be as short as possible); 4) The cost difference for the UAV to enter and exit the sub-region from different directions to execute the coverage route is small (i.e., the length and width of the sub-region are similar, and the difference in the UAV's arrival at the start / end point of the sub-region coverage route from different boundary directions is not significant). This makes the division of large-scale, complex-shaped areas and the planning of sub-region coverage routes a challenging task. Summary of the Invention

[0005] This disclosure provides a method and system for target area division and sub-region coverage route planning, which can be used in scenarios where multi-UAV cooperative systems perform large-scale complex-shaped area coverage search tasks, complete the division of the target area, and the coverage route planning and cost calculation for each sub-region. This disclosure provides the following technical solutions:

[0006] As one aspect of this disclosure, a method for target area division and sub-area coverage route planning is provided, comprising the following steps:

[0007] S10, Input the definitions of all target regions, calculate the minimum bounding rectangle of each target region and its length and width, and initialize the value of i to 1;

[0008] S20, taking into account both the total number of effective coverage units and the effective coverage rate of the coverage unit set, determine the i-th target region A. i Coverage unit size level S i And find the optimal global displacement D of the covering element set. i ;

[0009] S30, based on the selected coverage unit size level S i With the optimal overall displacement D i Divide the target area A i Obtain the covering unit set U, and initialize j to 1;

[0010] S40, determine the coverage unit U j Is it completely within target area A? i In the middle, if the covering unit U j Completely within target area A iIn the process, a pre-fabricated route pattern is used to generate the coverage unit U. j The coverage route; if the coverage unit U j Some are in target area A i In addition, the optimal overall mesh displacement is calculated, the coverage path is optimized, and the coverage cell U is recorded. j The coverage routes and their costs;

[0011] S50, determine whether target area A has been completed. i If the coverage route planning for all coverage units is not yet complete, then update j = j + 1, and then return to step S40 to proceed to the next coverage unit U. j If the processing is complete, then determine whether the processing of all target areas has been completed.

[0012] S60, if not all target regions have been processed, update i = i + 1, then return to step S20 to process the next target region A. i The processing is as follows: if the processing of all target areas has been completed, then all coverage units of all target areas, their coverage routes, and corresponding costs are output as results.

[0013] Optionally, the UAV coverage operation grid is the smallest coverage unit in the area coverage search task scenario, centered on the UAV projection point and with respect to l d A square with side length of [length missing].

[0014] Optionally, the coverage unit is square and contains multiple UAV coverage operation grids. The size of the coverage unit is determined by the ratio of the side length of the coverage unit to the side length of the UAV coverage operation grid. d The ratio of .

[0015] Optionally, the coverage unit set is a collection of coverage units, the effective coverage unit refers to a coverage unit in the coverage unit set that contains part or all of the target area, and the effective coverage rate represents the ratio of the total number of effective coverage units to the total number of units in the coverage unit set.

[0016] Optionally, the determination of the coverage unit size level S i And the optimal global displacement D of the covering unit set i This includes determining whether the following conditions are met: 1) The flight time corresponding to the drone's full-range energy is less than the minimum coverage route cost of a coverage unit of a specified size, or 2) Target area A i The ratio of the side length of the smallest bounding rectangle to the side length of the cover cell of a specified size level is less than a specified threshold. If this condition is met, then the cover cell size level S is selected. i Set the value to 1, and construct the target region A. i Given a set of covering cells, find the optimal global displacement D of the set of covering cells that minimizes the effective coverage.i Otherwise, based on the flight time corresponding to the drone's full-range energy, determine the size levels of all candidate coverage units; for each candidate coverage unit size level, temporarily construct the corresponding target area A. i For the set of covering elements, calculate and record the optimal overall displacement, the total number of effective covering elements, and the effective coverage rate of the corresponding set of covering elements; then, considering both the total number of effective covering elements and the effective coverage rate of the set of covering elements, select the optimal candidate covering element size level S. i and the optimal global displacement D of the corresponding covering element set i .

[0017] Optionally, the coverage unit can be divided into S×S UAV coverage operation grids according to its size level S; by expanding the grid on this basis, (S+1)×(S+1) UAV coverage operation grids are obtained, which are called the UAV coverage grid group of the coverage unit.

[0018] Optionally, in the UAV coverage grid group, the grids that overlap with the target area are called effective coverage grids. The UAV coverage grid group can be shifted as a whole to change the number of effective coverage grids required to fully cover a portion of the target area contained within a unit.

[0019] Optionally, the determination coverage unit U j Is it completely within target area A? i It also includes: if the covering unit U j Completely within target area A i In the middle, the covering unit U is... j The center points of the grid at the four corners are defined as the entry and exit directions, and the coverage unit U is generated using a pre-made route pattern. j The coverage route; if the coverage unit U j Some are in target area A i In addition, the covering unit U j The center point of the effective coverage grid closest to the four corners is defined as the entry and exit azimuth, and the coverage cell U is defined as follows. j The overall offset of the UAV coverage grid group is optimized to minimize the ratio of the effective coverage grid number to the total number of grids. Then, the cell U is optimized and obtained. j The coverage route.

[0020] As another aspect of this disclosure, a target area division and sub-area coverage route planning system is provided, including:

[0021] Target Region Input Module: Input the definition of all target regions, and calculate the minimum bounding rectangle of each target region and its length and width;

[0022] Target region segmentation module: Taking into account both the total number of effective coverage units and the effective coverage rate of the coverage unit set, determine the i-th target region A. i Coverage unit size level S i and target area A i The optimal global displacement D of the covering element set i Then, based on the selected coverage unit size level S i With the optimal overall displacement D i Divide the target area A i , obtain the covering unit set U;

[0023] Coverage Unit Coverage Route Planning Module: Determines Coverage Unit U j Is it completely within target area A? i In the middle, if the covering unit U j Completely within target area A i In the process, a pre-fabricated route pattern is used to generate the coverage unit U. j The coverage route; if the coverage unit U j Some are in target area A i In addition, optimize the calculation of the coverage route and record the coverage unit U. j The coverage routes and their costs;

[0024] Coverage Unit and Coverage Route Output Module: If all target areas and all coverage units have been processed, output all coverage units and their coverage routes and corresponding costs for all target areas as the result.

[0025] As another aspect of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described target area division and sub-area coverage route planning method.

[0026] As another aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the above-described target area division and sub-area coverage route planning method.

[0027] Compared to the prior art, the beneficial effects of this disclosure are as follows:

[0028] 1. After the target area is divided and the sub-area coverage route is planned, the task division and route planning problem of multiple UAVs performing large-scale complex shape area coverage search tasks can be simplified into UAV-sub-area allocation problem and UAV coverage route combination problem. This will greatly reduce the computational scale, reduce the difficulty of solving the problem, and thus improve the task execution efficiency and reduce the task cost.

[0029] 2. Using coverage units of the same size to divide the target area can prevent excessive cost and benefit differences between coverage units. Each unit has different combinations of entry and exit directions, and coverage routes are planned for different combinations of entry and exit directions. On the one hand, this can make the cost of coverage routes for each combination of entry and exit directions basically the same. On the other hand, it can provide more coverage route options within the unit for subsequent solving of UAV coverage route combination problems, thereby reducing optimization losses.

[0030] 3. The optimal size and overall displacement of the coverage unit can adapt to the shape and size of the target area. While controlling the number of units in the coverage unit set, it reduces the effective coverage rate of the coverage unit set, which greatly reduces the scale of task division and route planning problems and effectively reduces the loss of optimization.

[0031] 4. By adopting the method of "pre-made routes and "overall optimization offset of UAV coverage grid + coverage route optimization planning", the coverage routes within each unit can be obtained, which can effectively solve the route planning problem of coverage units located inside or at the boundary of the target area, thus enabling adaptability to target areas with complex shapes. Attached Figure Description

[0032] Figure 1 This is a flowchart of the target area division and sub-area coverage route planning method in Example 1;

[0033] Figure 2 This is a flowchart illustrating the implementation process of the target area division and sub-region coverage route planning method in Example 1;

[0034] Figure 3 This is a schematic diagram of the method in Example 1 for constructing coverage units to divide the target area, performing the optimal overall displacement of the coverage unit set, and calculating the effective coverage rate.

[0035] Figure 4 This is a schematic diagram of the coverage unit, the UAV coverage operation grid, the UAV coverage grid group, and the overall displacement of the grid group in Example 1;

[0036] Figure 5 This is a schematic diagram of the UAV coverage operation grid provided in Example 1;

[0037] Figure 6 This is a schematic diagram of the task scenario environment and its target area in Example 1;

[0038] Figure 7 This is a schematic diagram of the target region and its minimum bounding rectangle in Example 1;

[0039] Figure 8 This is a schematic diagram of the target area and its coverage unit group in Example 1;

[0040] Figure 9 This is a schematic diagram of the target area and its coverage unit group in Example 1, as well as the coverage route within each unit;

[0041] Figure 10 This is a schematic block diagram of the target area division and sub-area coverage route planning system in Example 2. Detailed Implementation

[0042] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0043] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0044] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0045] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0046] It is understood that the various method embodiments mentioned above in this disclosure can be combined with each other to form combined embodiments without violating the principle and logic. Due to space limitations, this disclosure will not elaborate further.

[0047] In addition, this disclosure also provides a target area division and sub-area coverage route planning method and system. All of the above can be used to implement any of the target area division and sub-area coverage route planning methods provided by this disclosure. The corresponding technical solutions and descriptions are described in the corresponding records in the method section and will not be repeated here.

[0048] The execution entity of a target area division and sub-area coverage route planning method can be a computer or other device capable of implementing target area division and sub-area coverage route planning. For example, the method can be executed by a terminal device, server, or other processing device. The terminal device can be a user equipment (UE), mobile device, user terminal, terminal, cellular phone, cordless phone, personal digital assistant (PDA), handheld device, computing device, vehicle-mounted device, wearable device, etc. In some possible implementations, the target area division and sub-area coverage route planning method can be implemented by a processor calling computer-readable instructions stored in memory.

[0049] Example 1

[0050] This embodiment provides a method for target area division and sub-area coverage route planning, such as... Figure 1 As shown, it includes the following steps:

[0051] S10, Input the definitions of all target regions, calculate the minimum bounding rectangle of each target region and its length and width, and initialize the value of i to 1;

[0052] S20, taking into account both the total number of effective coverage units and the effective coverage rate of the coverage unit set, determine the i-th target region A. i Coverage unit size level S i And find the optimal global displacement D of the covering element set. i ;

[0053] S30, based on the selected coverage unit size level S i With the optimal overall displacement D i Divide the target area A i Obtain the covering unit set U, and initialize j to 1;

[0054] S40, determine the coverage unit U j Is it completely within target area A? i In the middle, if the covering unit U j Completely within target area A i In the process, a pre-fabricated route pattern is used to generate the coverage unit U. j The coverage route; if the coverage unit U j Some are in target area A i In addition, the optimal overall mesh displacement is calculated, the coverage path is optimized, and the coverage cell U is recorded. j The coverage routes and their costs;

[0055] S50, determine whether target area A has been completed. iIf the coverage route planning for all coverage units is not yet complete, then update j = j + 1, and then return to step S40 to proceed to the next coverage unit U. j If the processing is complete, then determine whether the processing of all target areas has been completed.

[0056] S60, if not all target regions have been processed, update i = i + 1, then return to step S20 to process the next target region A. i The processing is as follows: if the processing of all target areas has been completed, then all coverage units of all target areas, their coverage routes, and corresponding costs are output as results.

[0057] In this embodiment, the specific implementation process of a target area division and sub-region coverage route planning method is as follows: Figure 2 As shown, it includes the following steps:

[0058] S10, Input the definitions of all target regions, calculate the minimum bounding rectangle of each target region and its length and width, and initialize the value of i to 1;

[0059] In this embodiment, the input includes the definition of all target regions in the scenario of a multi-UAV collaborative system performing a large-scale complex shape region coverage search, as well as other scene parameters and method coefficients. A polygon is used to fit the boundary of the target region, and the boundary points of the fitted polygon are recorded in counter-clockwise order to form the target region definition. Other scene parameters and method coefficients can be assigned values ​​to each parameter with reference to Table 1.

[0060] Other scenario parameters include performance parameters such as UAV endurance, coverage grid side length, and flight speed; the method coefficients control the execution process of this embodiment. In Table 1, R... e The size of the coverage unit to be selected is determined by energy cost constraints; that is, the energy cost of the coverage unit should be greater than 1 / 12 of the drone's full-range energy and less than 1 / 4 of the drone's full-range energy. S The size level of the coverage unit to be selected based on the side length constraint is specified; that is, the side length of the coverage unit should be greater than 1 / 30 of the width of the minimum bounding rectangle of the target area and less than 1 / 3 of the width of the minimum bounding rectangle. S1 f S2 Used when calculating the candidate size levels of coverage cells.

[0061] Table 1 Examples of assigning values ​​to parameters and method coefficients in other scenarios

[0062]

[0063] Furthermore, calculate the minimum bounding rectangle of each target region and its length and width, and initialize the value of i to 1.

[0064] S20, taking into account both the total number of effective coverage units and the effective coverage rate of the coverage unit set, determine the i-th target region A. i Coverage unit size level S i And find the optimal global displacement D of the covering element set. i ;

[0065] In this embodiment, the determination of the coverage unit size level S i And the optimal global displacement D of the covering unit set i This includes: determining the target region A i Does condition 1 meet? If condition 1 meets, then take the coverage cell size level S. i Set the value to 1, construct coverage units to divide the target region A. i And find the optimal global displacement D of the set of covering cells that minimizes the effective coverage. i If condition 1 is not met, then calculate all candidate coverage unit size levels based on the flight time corresponding to the UAV's full-range energy. For each candidate coverage unit size level, temporarily construct coverage units to divide the target area, and calculate and record the corresponding optimal overall displacement and effective coverage rate. Then, considering the total number of effective coverage units and the effective coverage rate of the coverage unit set, select the optimal candidate coverage unit size level S. i and the optimal global displacement D of the corresponding covering element set i .

[0066] Furthermore, condition 1 is the flight time E corresponding to the drone's full-range energy. d Smaller than the coverage cell size level S i The minimum coverage route cost for a full coverage cell of 2, or the target area A. i The short side length of the smallest bounding rectangle is less than the size level S of the covering unit. i The coverage unit is 2 / 3 of the side length of a 2. A full coverage unit is defined as a unit that is completely contained within the target area, meaning the area covered by the unit is entirely within or equal to the target area. Otherwise, it is called a non-full coverage unit.

[0067] The coverage unit is the basic unit for dividing the target area and planning the coverage route. It is square, and the size of the coverage unit is determined by the ratio of the side length of the coverage unit to the side length of the UAV coverage operation grid. d The ratio of the coverage cell size level S i It can be represented as

[0068] S i =s b ×2 i ,i∈{0,1,2,…,∞},s d∈{2,3,5,7}

[0069] Furthermore, in this embodiment, the method for determining the candidate coverage unit size level based on the UAV's endurance is specifically as follows: for any coverage unit size level S calculated using the above formula... i If the size level is S i The average coverage route cost of a fully covered unit is in the range Within, S is determined i It can be used as a candidate coverage unit size level.

[0070] Furthermore, in this embodiment, the method for constructing coverage units to divide the target area, calculating and recording the corresponding optimal overall displacement and effective coverage rate is as follows: Figure 3 As shown, the steps are as follows:

[0071] S201, starting from the origin of the smallest bounding rectangle of the target area, construct covering units along the positive directions of the length and width of the smallest bounding rectangle until the smallest bounding rectangle is completely covered.

[0072] S202, starting from the origin of the smallest bounding rectangle of the target region, expand one row and one column of covering cells in the opposite direction of the length and width of the smallest bounding rectangle. The set of covering cells is then called the covering cell set, and the total number of cells in the covering cell set is denoted as N. U .

[0073] S203, in a set of coverage cells, a coverage cell that contains part or all of the target area is called an effective coverage cell. Let N′ be the total number of effective coverage cells in the set of coverage cells. U Then the effective coverage rate of the covering unit set is r′ U =N′ U / N U .

[0074] S204, the covering element set is shifted globally along the length and width directions of the minimum bounding rectangle. The permissible range of the global displacement is [0, (S i ×l d Find a global displacement within the permissible value range such that the effective coverage of the covering cell set is r′. U If the minimum value is found, then the overall displacement is the optimal overall displacement D for the covering element set. i .

[0075] S30, based on the selected coverage unit size level S i With the optimal overall displacement D i Divide the target area A i Obtain the covering unit set U, and initialize j to 1;

[0076] For size level Si The coverage unit can be divided into S i ×S i A drone covers the operational grid; by expanding the grid on this basis, we obtain (S) i +1)×(S i +1) drone coverage operation grids, called a drone coverage grid group, such as Figure 4 As shown.

[0077] S40, Initialize the drone coverage operation grid of the coverage unit, and determine the coverage unit U. j Is it completely within target area A? i In the middle, if the covering unit U j Completely within target area A i In the process, a pre-fabricated route pattern is used to generate the coverage unit U. j The coverage route; if the coverage unit U j Some are in target area A i In addition, the optimal overall mesh displacement is calculated, the coverage path is optimized, and the coverage cell U is recorded. j The coverage routes and their costs;

[0078] Optionally, the initialization coverage unit's UAV coverage operation grid is defined as a grid containing (S i +1)×(S i +1) Coverage unit U of the drone coverage operation grid j The drones cover the grid.

[0079] Optionally, the UAV coverage operation grid is the smallest coverage unit in the area coverage search task scenario, centered on the UAV projection point and with respect to l d A square with sides of length 100. The drone coverage grid is as follows: Figure 5 As shown, it represents the effective coverage area formed by a drone on the ground when the drone is in a certain position in the air performing a coverage operation. When the drone is located at or passes through the center point of a drone coverage operation grid, the coverage operation of that grid is completed.

[0080] In this embodiment, the UAV coverage grid group can be displaced as a whole to change the effective number of coverage grids required to fully cover a portion of the target area contained within a coverage cell. The permissible range for the overall displacement of the UAV coverage grid group along the edges (x and y directions) of the coverage cell is [0, l]. d The effective coverage grid is defined as the grid within the UAV coverage group that overlaps with the target area A. i A grid with overlapping areas.

[0081] In this embodiment, the coverage path of a cell needs to traverse the center points of all effective coverage grids in the UAV coverage grid group passing through the cell. The starting and ending points of the coverage path of a coverage cell can only be selected from a limited set of grid center points, which are called the entry and exit points of the coverage cell. The entry and exit points of a full-coverage cell are the grid center points at the four corners of the cell (numbered 1, 2, 3, and 4 counterclockwise from the lower left corner); the entry and exit points of a non-full-coverage cell are the effective coverage grid center points that are closest to the four corners of the cell after the UAV coverage grid group has shifted.

[0082] Optionally, the determination coverage unit U j Is it completely within target area A? i It also includes: if the covering unit U j Completely within target area A i In the middle, the covering unit U j As a full-coverage unit, the coverage unit U j The center points of the grid at the four corners are defined as the entry and exit directions, and the coverage unit U is generated using a pre-made route pattern. j The coverage route; if the coverage unit U j Some are in target area A i Outside, the covering unit U j For non-full coverage units, the coverage unit U j The center point of the effective coverage grid closest to the four corners is defined as the entry and exit azimuth, and the coverage cell U is defined as follows. j The overall offset of the UAV coverage grid group is optimized to maximize the ratio of the effective coverage grid number to the total number of grids. Then, the cell U is optimized and obtained. j The coverage route.

[0083] Furthermore, for full-coverage cells, the size level S can be determined. i Whether the number is odd or even, an optimized coverage route pattern is pre-specified for all combinations of entry and exit directions, and a corresponding formula for calculating the coverage route cost is provided as a pre-designed route pattern. In this embodiment, the coverage route cost refers to the time required for the UAV to complete the coverage route. The pre-designed route pattern can be directly used to generate unit coverage routes and calculate their costs, thus shortening the planning time of unit coverage routes. Table 2 shows examples of pre-designed route patterns for coverage units.

[0084] Table 2 Examples of Prefabricated Route Patterns for Covering Units

[0085]

[0086]

[0087] Furthermore, for incomplete coverage units, optimization methods such as genetic algorithms can be used to minimize the time required for the UAV to complete the coverage route. For each combination of entry and exit directions, the traversal coverage unit U can be optimized. j Coverage routes for all valid coverage grid center points.

[0088] S50, determine whether target area A has been completed. i If the coverage route planning for all coverage units is not yet complete, then update j = j + 1 and return to step S40 to proceed to the next coverage unit U. j If the processing is complete, then determine whether the processing of all target areas has been completed.

[0089] S60, if not all target regions have been processed, update i = i + 1, and return to step S20 to proceed to the next target region A. i The processing is as follows: if the processing of all target areas has been completed, then all coverage units of all target areas, their coverage routes, and corresponding costs are output as results.

[0090] The user defines the target region prepared in S10, along with other scenario parameters and method coefficients, as follows: Figure 6 The target area shown is an instance object. Refer to Table 1 to assign values ​​to the parameters. Input the above target area division and coverage route planning program, and the program will automatically complete the calculation of the minimum bounding rectangle of the target area, the division of the target area's coverage units and the optimal overall displacement, and the planning of the coverage routes in each unit, such as... Figure 7 — Figure 9 As shown, the final output includes data on all coverage units in the target area, their coverage routes, and corresponding costs.

[0091] Example 2

[0092] As another aspect of the embodiments of this disclosure, a target area division and sub-area coverage route planning system 100 is also provided, such as... Figure 10 As shown, it includes the following modules:

[0093] Target Region Input Module 1: Input the definition of all target regions, and calculate the minimum bounding rectangle of each target region and its length and width;

[0094] Target Region Division Module 2: Taking into account both the total number of effective coverage units and the effective coverage rate of the coverage unit set, determine the i-th target region A. i Coverage unit size level S i and target area A i The optimal global displacement D of the covering element set i Then, based on the selected coverage unit size level S i With the optimal overall displacement Di Divide the target area A i , obtain the covering unit set U;

[0095] Coverage Unit Coverage Route Planning Module 3: Determine Coverage Unit U j Is it completely within target area A? i In the middle, if the covering unit U j Completely within target area A i In the process, a pre-fabricated route pattern is used to generate the coverage unit U. j The coverage route; if the coverage unit U j Some are in target area A i In addition, optimize the calculation of the coverage route and record the coverage unit U. j The coverage routes and their costs;

[0096] Coverage Unit and Coverage Route Output Module 4: If all target areas and all coverage units have been processed, output all coverage units and their coverage routes and corresponding costs for all target areas as results.

[0097] Based on the above modules, this embodiment of the disclosure constructs a target region division and sub-region coverage route planning method. The target region is defined as the main input parameter, and the minimum bounding rectangle of the target region is determined. The size level of the coverage unit is optimized, and the optimal overall displacement is calculated. Based on this, a set of coverage units is divided, achieving an optimal combination of the number of coverage units and the effective coverage rate. For each coverage unit, depending on whether it is completely within the target region, a pre-made route is used as the coverage route, or the optimal overall grid displacement is calculated and optimized to obtain the coverage route. All coverage units of the target region, their coverage routes, and costs are output as the final result. This method addresses the task division and route planning problem of multi-UAV large-area complex shape region coverage search tasks, simplifying the problem, reducing the computational scale, and lowering the solution difficulty, thereby improving task execution efficiency and reducing task costs. A target region division and sub-region coverage route planning system 100 is implemented.

[0098] The various modules of the embodiments of this disclosure will be described in detail below.

[0099] Target Region Input Module 1: Input the definition of all target regions and calculate the minimum bounding rectangle of each target region and its length and width.

[0100] In this embodiment, the input includes the definition of all target regions in the scenario of a multi-UAV collaborative system performing a large-scale complex shape region coverage search, as well as other scene parameters and method coefficients. A polygon is used to fit the boundary of the target region, and the boundary points of the fitted polygon are recorded in counter-clockwise order to form the target region definition. Other scene parameters and method coefficients can be assigned values ​​to each parameter with reference to Table 1.

[0101] Other scenario parameters include performance parameters such as UAV endurance, coverage grid side length, and flight speed; the method coefficients control the execution process of this embodiment. In Table 1, R... e The size of the coverage unit to be selected is determined by energy cost constraints; that is, the energy cost of the coverage unit should be greater than 1 / 12 of the drone's full-range energy and less than 1 / 4 of the drone's full-range energy. S The size level of the coverage unit to be selected based on the side length constraint is specified; that is, the side length of the coverage unit should be greater than 1 / 30 of the width of the minimum bounding rectangle of the target area and less than 1 / 3 of the width of the minimum bounding rectangle. S1 f S2 Used when calculating the candidate size levels of coverage cells.

[0102] Table 1 Examples of assigning values ​​to parameters and method coefficients in other scenarios

[0103]

[0104] Furthermore, calculate the minimum bounding rectangle of each target region and its length and width, and initialize the target region A. i Initialize the value of i to 1.

[0105] Target Region Division Module 2: Taking into account both the total number of effective coverage units and the effective coverage rate of the coverage unit set, determine the i-th target region A. i Coverage unit size level S i and target area A i The optimal global displacement D of the covering element set i Then, based on the selected coverage unit size level S i With the optimal overall displacement D i Divide the target area A i , obtain the set of covered units U.

[0106] In this embodiment, the determination of the coverage unit size level S i And the optimal global displacement D of the covering unit set i This includes: determining the target region A i Does condition 1 meet? If condition 1 meets, then take the coverage cell size level S. i Set the value to 1, construct coverage units to divide the target region A. i And find the optimal global displacement D of the set of covering cells that minimizes the effective coverage. iIf condition 1 is not met, then calculate all candidate coverage unit size levels based on the flight time corresponding to the UAV's full-range energy. For each candidate coverage unit size level, temporarily construct coverage units to divide the target area, and calculate and record the corresponding optimal overall displacement and effective coverage rate. Then, considering the total number of effective coverage units and the effective coverage rate of the coverage unit set, select the optimal candidate coverage unit size level S. i and the optimal global displacement D of the corresponding covering element set i .

[0107] Furthermore, condition 1 is the flight time E corresponding to the drone's full-range energy. d Smaller than the coverage cell size level S i The minimum coverage route cost for a full coverage cell of 2, or the target area A. i The short side length of the smallest bounding rectangle is less than the size level S of the covering unit. i The coverage unit is 2 / 3 of the side length of a 2. A full coverage unit is defined as a unit that is completely contained within the target area, meaning the area covered by the unit is entirely within or equal to the target area. Otherwise, it is called a non-full coverage unit.

[0108] The coverage unit is the basic unit for dividing the target area and planning the coverage route. It is square, and the size of the coverage unit is determined by the ratio of the side length of the coverage unit to the side length of the UAV coverage operation grid. d The ratio of the coverage cell size level S i It can be represented as

[0109] S i =s b ×2 i ,i∈{0,1,2,…,∞},s d ∈{2,3,5,7}

[0110] Furthermore, in this embodiment, the method for determining the candidate coverage unit size level based on the UAV's endurance is specifically as follows: for any coverage unit size level S calculated using this formula... i If the size level is S i The average coverage route cost of a fully covered unit is in the range Within, S is determined i It can be used as a candidate coverage unit size level.

[0111] Furthermore, in this embodiment, the method steps for constructing coverage units to divide the target area, calculating and recording the corresponding optimal overall displacement and effective coverage rate are as follows:

[0112] S201, starting from the origin of the smallest bounding rectangle of the target area, construct covering units along the positive directions of the length and width of the smallest bounding rectangle until the smallest bounding rectangle is completely covered.

[0113] S202, starting from the origin of the smallest bounding rectangle of the target region, expand one row and one column of covering cells in the opposite direction of the length and width of the smallest bounding rectangle. The set of covering cells is then called the covering cell set, and the total number of cells in the covering cell set is denoted as N. U .

[0114] S203, in a set of coverage cells, a coverage cell that contains part or all of the target area is called an effective coverage cell. Let N′ be the total number of effective coverage cells in the set of coverage cells. U Then the effective coverage rate of the covering unit set is r′ U =N′ U / N U .

[0115] S204, the covering element set is shifted globally along the length and width directions of the minimum bounding rectangle. The permissible range of the global displacement is [0, (S i ×l d Find a global displacement within the permissible value range such that the effective coverage of the covering cell set is r′. U If the minimum value is found, then the overall displacement is the optimal overall displacement D for the covering element set. i .

[0116] Furthermore, based on the selected coverage unit size level S i With the optimal overall displacement D i Divide the target area A i Obtain the covering unit set U, and initialize j to 1.

[0117] Coverage Unit Coverage Route Planning Module 3: Determine Coverage Unit U j Is it completely within target area A? i In the middle, if the covering unit U j Completely within target area A i In the process, a pre-fabricated route pattern is used to generate the coverage unit U. j The coverage route; if the coverage unit U j Some are in target area A i In addition, optimize the calculation of the coverage route and record the coverage unit U. j The coverage routes and their costs.

[0118] Optionally, for size order S i The coverage unit can be divided into S i ×S iA drone covers the operational grid; by expanding the grid on this basis, we obtain (S) i +1)×(S i +1) drone coverage operation grids are called drone coverage grid groups, which are called coverage units.

[0119] Optionally, the initialization of the coverage unit's UAV coverage operation grid will... j Divided into (S) i +1)×(S i +1) drone coverage operation grid.

[0120] Optionally, the UAV coverage operation grid is the smallest coverage unit in the area coverage search task scenario, centered on the UAV projection point and with respect to l d A square with sides of length 1.5. A drone coverage operation grid represents the effective coverage area formed on the ground when a drone is in a certain position in the air performing a coverage operation. When a drone is located at or passes through the center point of a drone coverage operation grid, the coverage operation of that grid is completed.

[0121] In this embodiment, the UAV coverage grid group can be displaced as a whole to change the effective number of coverage grids required to fully cover a portion of the target area contained within a coverage cell. The permissible range for the overall displacement of the UAV coverage grid group along the edges (x and y directions) of the coverage cell is [0, l]. d The effective coverage grid is defined as the grid within the UAV coverage group that overlaps with the target area A. i A grid with overlapping areas.

[0122] In this embodiment, the coverage path of a cell needs to traverse the center points of all effective coverage grids in the UAV coverage grid group passing through the cell. The starting and ending points of the coverage path of a coverage cell can only be selected from a limited set of grid center points, which are called the entry and exit points of the coverage cell. The entry and exit points of a full-coverage cell are the grid center points at the four corners of the cell (numbered 1, 2, 3, and 4 counterclockwise from the lower left corner); the entry and exit points of a non-full-coverage cell are the effective coverage grid center points that are closest to the four corners of the cell after the UAV coverage grid group has shifted.

[0123] Optionally, the determination coverage unit U j Is it completely within target area A? i It also includes: if the covering unit U j Completely within target area A i In the middle, the covering unit U j To achieve full coverage, the coverage unit U is... j The center points of the grid at the four corners are defined as the entry and exit directions, and the coverage unit U is generated using a pre-made route pattern. jThe coverage route; if the coverage unit U j Some are in target area A i Outside, the covering unit U j For non-full coverage units, the coverage unit U j The center point of the effective coverage grid closest to the four corners is defined as the entry and exit azimuth, and the coverage cell U is defined as follows. j The overall offset of the UAV coverage grid group is optimized to minimize the ratio of the effective coverage grid number to the total number of grids. Then, the cell U is optimized and obtained. j The coverage route.

[0124] Furthermore, for full-coverage cells, the size level S can be determined. i Whether the number is odd or even, an optimized coverage route pattern is pre-specified for all combinations of entry and exit directions, and a corresponding formula for calculating the coverage route cost is provided as a pre-designed route pattern. In this embodiment, the coverage route cost refers to the time required for the UAV to complete the coverage route. The pre-designed route pattern can be directly used to generate unit coverage routes and calculate their costs, thus shortening the planning time of unit coverage routes. Table 2 shows examples of pre-designed route patterns for coverage units.

[0125] Table 2 Examples of Prefabricated Route Patterns for Covering Units

[0126]

[0127] Furthermore, for incomplete coverage units, optimization methods such as genetic algorithms can be used to minimize the time required for the UAV to complete the coverage route. For each combination of entry and exit directions, the traversal coverage unit U can be optimized. j Coverage routes for all valid coverage grid center points.

[0128] Coverage unit and its coverage route output module 4: Determine whether the target area A has been completed. i If the coverage route planning for all coverage units is not yet complete, then update j = j + 1 and return to step S40 to proceed to the next coverage unit U. j If the processing is complete, then determine whether the processing of all target regions is complete; if the processing of all target regions is not complete, then update i = i + 1 and return to step S20 to proceed to the next target region A. i The processing is as follows: if the processing of all target areas has been completed, then all coverage units of all target areas, their coverage routes, and corresponding costs are output as results.

[0129] The user inputs the target area definition prepared in S10, along with other scenario parameters and method coefficients, into the target area division and coverage route planning program. The program automatically completes the calculation of the minimum bounding rectangle of the target area, the division of the coverage units of the target area and the optimal overall displacement, the planning of the coverage routes in each unit, and finally outputs the data of all coverage units of the target area, their coverage routes and corresponding costs.

[0130] In some embodiments, the system 100 described above operates in the following manner:

[0131] S1: Run the target region input module. Input the definitions of all target regions, calculate the minimum bounding rectangle of each target region and its length and width, and initialize target region A. i Initialize the value of i to 1;

[0132] S2: Run the target region partitioning module. Taking into account both the total number of effective coverage units and the effective coverage rate of the coverage unit set, determine the i-th target region A. i Coverage unit size level S i and target area A i The optimal global displacement D of the covering element set i Then, based on the selected coverage unit size level S i With the optimal overall displacement D i Divide the target area A i , obtain the covering unit set U;

[0133] S3: Run the coverage unit coverage route planning module. Initialize the UAV coverage operation grid of the coverage unit; determine the coverage unit U. j Is it completely within target area A? i In the middle, if the covering unit U j Completely within target area A i In the process, a pre-fabricated route pattern is used to generate the coverage unit U. j The coverage route; if the coverage unit U j Some are in target area A i In addition, optimize the calculation of the coverage route and record the coverage unit U. j The coverage routes and their costs;

[0134] S4: Run the coverage unit and its coverage route output module. Determine whether target area A has been completed. i If the coverage route planning for all coverage units is not yet complete, update j = j + 1 and return to step S3 to proceed to the next coverage unit U. j If the processing is complete, then determine whether the processing of all target regions is complete; if the processing of all target regions is not complete, then update i = i + 1 and return to step S2 to proceed to the next target region A.i The processing is as follows: if the processing of all target areas has been completed, then all coverage units of all target areas, their coverage routes, and corresponding costs are output as results.

[0135] Based on the description of the above embodiments, it can be seen that the embodiments of this disclosure can achieve the following technical effects:

[0136] 1. After the target area is divided and the sub-area coverage route is planned, the task division and route planning problem of multiple UAVs performing large-scale complex shape area coverage search tasks can be simplified into UAV-sub-area allocation problem and UAV coverage route combination problem. This will greatly reduce the computational scale, reduce the difficulty of solving the problem, and thus improve the task execution efficiency and reduce the task cost.

[0137] 2. Using coverage units of the same size to divide the target area can prevent excessive cost and benefit differences between coverage units. Each unit has different combinations of entry and exit directions, and coverage routes are planned for different combinations of entry and exit directions. On the one hand, this can make the cost of coverage routes for each combination of entry and exit directions basically the same. On the other hand, it can provide more coverage route options within the unit for subsequent solving of UAV coverage route combination problems, thereby reducing optimization losses.

[0138] 3. The optimal size and overall displacement of the coverage unit can adapt to the shape and size of the target area. While controlling the number of units in the coverage unit set, it can improve the effective coverage rate of the coverage unit set, which can significantly reduce the scale of task division and route planning problems and effectively reduce the loss of optimization.

[0139] 4. By adopting the method of "pre-made routes and "overall optimization offset of UAV coverage grid + coverage route optimization planning", the coverage routes within each unit can be obtained, which can effectively solve the route planning problem of coverage units located inside or at the boundary of the target area, thus enabling adaptability to target areas with complex shapes.

[0140] Example 3

[0141] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the target area division and sub-area coverage route planning method in Embodiment 1.

[0142] Embodiment 3 of this disclosure is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this disclosure.

[0143] Electronic devices can take the form of general-purpose computing devices, such as server devices. Components of an electronic device may include, but are not limited to: at least one processor, at least one memory, and buses connecting different system components (including memory and processor).

[0144] The bus includes a data bus, an address bus, and a control bus.

[0145] The memory may include volatile memory, such as random access memory (RAM) and / or cache memory, and may further include read-only memory (ROM).

[0146] The memory may also include program tools having a set (at least one) of program modules, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0147] The processor performs various functional applications and data processing by running computer programs stored in memory.

[0148] Electronic devices can also communicate with one or more external devices (such as keyboards, pointing devices, etc.). This communication can be achieved through input / output (I / O) interfaces. Furthermore, electronic devices can communicate with one or more networks (such as local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via network adapters. The network adapter communicates with other modules of the electronic device via a bus. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.

[0149] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0150] Example 4

[0151] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the target region division and sub-region coverage route planning method in Embodiment 1.

[0152] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0153] In a possible implementation, this disclosure can also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of implementing the target area division and sub-area coverage route planning method described in Embodiment 1.

[0154] The program code for executing this disclosure can be written in any combination of one or more programming languages, and the program code can be executed entirely on a user device, partially on a user device, as a stand-alone software package, partially on a user device and partially on a remote device, or entirely on a remote device.

[0155] Although embodiments of the present disclosure have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the present disclosure, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A target area division and sub-area coverage route planning method, characterized in that, The method comprises the following steps: S10, input the definition of all target regions, calculate the minimum circumscribed rectangle of each target region and its length and width, and initialize the value of i to 1; S20, considering the total number of effective coverage units and the effective coverage rate of the coverage unit set, determine the i-th target area A i , the coverage unit size level S i of the i-th target area A i , and obtain the optimal overall displacement D of the coverage unit set. S30, according to the selected coverage unit size level S i with the best overall displacement D i , dividing the target area A i , obtaining a coverage unit set U, and initializing the value of j to 1; S40, judging the coverage unit U j whether it is completely in the target area A i In the embodiment, if the coverage unit U j is completely in the target area A i , a pre-made route mode is used to generate a coverage route of the coverage unit U j ; if the coverage unit U j has a part outside the target area A i , a best grid overall displacement is calculated, a coverage route is optimized, and the coverage route and its cost of the coverage unit U j are recorded. S50, judging whether the target area A is completed i the coverage route planning of all coverage units of the target area A, if not completed, updating j = j + 1, and then returning to step S40 to perform the next coverage unit U j ; if completed, judging whether the processing of all target areas is completed; S60, if the processing of all target regions has not been completed, then i = i + 1 is updated, and then the process returns to step S20 to perform the next target region A i processing; If the processing of all target regions is completed, all covering units and their covering routes of all target regions and the corresponding costs are output as results.

2. The target area partitioning and sub-area covering route planning method of claim 1, wherein, The drone coverage grid is centered on the drone's projection point and uses l d The coverage unit is a square with sides of length l. The UAV coverage operation grid is the smallest coverage unit in the area coverage search task scenario. Each coverage unit is square and contains multiple UAV coverage operation grids. The size of the coverage unit is determined by the ratio of its side length to the side length of the UAV coverage operation grid. d The ratio; the coverage unit set is a collection of coverage units; the effective coverage unit refers to a coverage unit that contains part or all of the target area, and the effective coverage grid refers to a UAV coverage operation grid that contains part or all of the target area; the effective coverage rate represents the ratio of the total number of effective coverage units to the total number of units in the coverage unit set.

3. The target area partitioning and sub-area covering route planning method of claim 2, wherein, According to the size level S, the covering unit can be divided into SxS UAV covering operation grids; on this basis, the grid is expanded to obtain (S+1)x(S+1) UAV covering operation grids, which are referred to as the UAV covering grid group of the covering unit; in the UAV covering grid group, the grid with overlapping area with the target region is referred to as the effective covering grid; the UAV covering grid group can be displaced as a whole to change the number of effective covering grids required for completely covering part of the target region.

4. The target area partitioning and sub-area covering route planning method of claim 3, wherein, The judgment coverage unit U j Is it completely within target area A? i It also includes: if the covering unit U j Completely within target area A i In the middle, the covering unit U is... j The center points of the grid at the four corners are defined as the entry and exit directions, and the coverage unit U is generated using a pre-made route pattern. j The coverage route; if the coverage unit U j Some are in target area A i In addition, the covering unit U j The center point of the effective coverage grid closest to the four corners is defined as the entry and exit azimuth, and the coverage cell U is defined as follows. j The overall offset of the UAV coverage grid group is optimized to minimize the ratio of the effective coverage grid number to the total number of grids. Then, the cell U is optimized and obtained. j The coverage route.

5. A target area division and sub-area coverage route planning system, characterized by, The method comprises the following steps: The target region input module: input the definition of all target regions, calculate the minimum circumscribed rectangle of each target region and its length and width; Target region segmentation module: Taking into account both the total number of effective coverage units and the effective coverage rate of the coverage unit set, determine the i-th target region A. i Coverage unit size level S i and target area A i The optimal global displacement D of the covering element set i Then, based on the selected coverage unit size level S i With the optimal overall displacement D i Divide the target area A i , obtain the covering unit set U; Coverage unit coverage route planning module: judge whether the coverage unit U j is completely in the target area A i , if the coverage unit U j is completely in the target area A i , generate the coverage route of the coverage unit U j using the pre-made route mode; if the coverage unit U j has part outside the target area A i , optimize to obtain the coverage route, and record the coverage route of the coverage unit U j and its cost; The covering unit and its covering route output module: if the processing of all target regions and all covering units is completed, all covering units and their covering routes of all target regions and the corresponding costs are output as results.

6. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the target region division and sub-region covering route planning method of any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium having stored thereon a computer program, characterized in that The program is executed by the processor to implement the target region division and sub-region covering route planning method of any one of claims 1 to 4.

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