Unmanned aerial vehicle cluster multifunctional area revisit coverage method and system

Abstract

The invention discloses an unmanned aerial vehicle cluster multifunctional area revisit coverage method and system, and relates to the unmanned aerial vehicle technology, and the method comprises the steps: configuring the area revisit coverage parameters of an unmanned aerial vehicle cluster, and calculating an area convex hull polygon; determining a region coverage direction according to the calculated length direction of the region convex hull polygon; based on the area coverage direction, segmenting the to-be-covered area to obtain a plurality of to-be-covered sub-areas and corresponding coverage directions; determining an initial path point and a termination path point of the to-be-covered sub-region based on each to-be-covered sub-region and the corresponding covering direction; and calculating a cooperative revisit coverage path according to the initial path point and the termination path point of the to-be-covered sub-region. The invention provides a multi-group, multi-angle and multi-region unmanned aerial vehicle cluster revisit coverage route planning scheme based on region segmentation.

Description

Technical Field

[0001] The present application relates to the field of drone technology, and in particular to a drone cluster multifunctional area revisit coverage method and system. Background Art

[0002] Many real-world applications require drone swarms to revisit and cover one or more irregular target areas in the most efficient way to detect possible moving targets therein.

[0003] The main disadvantages of the existing technical inventions are as follows:

[0004] The existing technology does not consider the situation of multi-angle coverage;

[0005] The existing techniques do not consider the case of cluster grouping;

[0006] Existing technology requires too many drones. Summary of the invention

[0007] The embodiments of the present application provide a method and system for revisiting and covering a multi-functional area of ​​a drone swarm, which are used to propose a multi-group, multi-angle, and multi-area drone swarm revisiting and covering route planning scheme based on area segmentation.

[0008] The present application embodiment provides a method for revisiting and covering a multifunctional area of ​​a drone cluster, comprising:

[0009] Configure the parameters of the area revisit coverage of the drone cluster and calculate the area convex hull polygon;

[0010] Determine the area coverage direction according to the length direction of the calculated area convex hull polygon;

[0011] Based on the area coverage direction, the area to be covered is divided to obtain multiple sub-areas to be covered and corresponding coverage directions;

[0012] Determine the initial path point and the terminal path point of the sub-area to be covered based on each sub-area to be covered and the corresponding coverage direction;

[0013] The collaborative revisit coverage path is calculated based on the initial path point and the terminal path point of the sub-area to be covered.

[0014] Optionally, the parameters for configuring the area revisit coverage of the drone cluster include:

[0015] Define the cruising speed of each drone in the drone cluster as V uav ; The detection deviation angle of the detection equipment on the drone is α, the distance between the center of the field of view and the position of the drone is d, and the detection overlap rate required for regional coverage is ρ;

[0016] Computing the convex hull polygon of a region involves:

[0017] For each area A to be covered l (l=1,2,L,N A ), select a set number of points, then the selected points form a polygon;

[0018] Calculating the convex polygon of the polygon using a Graham scan algorithm;

[0019] The vertex set of the convex polygon to be calculated is {p1,p2,L,p J-1 ,p J}, where p1 is the point with the smallest ordinate and the leftmost position.

[0020] Optionally, determining the area coverage direction according to the length direction of the calculated area convex hull polygon includes:

[0021] For each area A to be covered l (l=1,2,L,N A ), use the radial function method to calculate the length direction of its convex polygon;

[0022] The main scanning direction is determined according to the length direction, and the clock angle of the main scanning direction is recorded as θ opt ;

[0023] Determine the angle of each scanning direction as Where i=1,2,L,N D .

[0024] Optionally, based on the area coverage direction, segmenting the area to be covered to obtain multiple sub-areas to be covered and corresponding coverage directions includes:

[0025] For each area A to be covered l (l=1,2,L,N A ), for each coverage direction θ i (i=1,2,L,N D ) The region is segmented as follows:

[0026] Using the coverage direction angle θ i And the corresponding rotation matrix, rotate the area to be covered by θ i degrees, then the rotated area A (i) The coverage direction angle is 0;

[0027] Calculation area A (i) The minimum and maximum ordinate values ​​of all vertices;

[0028] Calculate the number of rectangles divided in is the ceiling function, y minand max For area A (i) The minimum and maximum ordinate values ​​of all vertices of , L1 is the width of the drone’s detection field of view;

[0029] For n = 1, 2, L, N R -1, calculate the vertical coordinate as y n =y min +nL1 horizontal straight line and area A (i) The intersection of the boundaries, then the nth rectangle is the one whose ordinate is in the interval [y n-1 ,y n ] is the minimum bounding rectangle of the polygon formed by all the vertices and intersection points of ;

[0030] For n = N R , the corresponding rectangle is the one with ordinate in the interval [y n-1 ,y n The bounding rectangle of the polygon formed by all the vertices and intersection points of ], the height of the bounding rectangle is L1;

[0031] Rotate all rectangles in the opposite direction by θ i degree, and obtain the original area A to be covered l Rectangular region segmentation.

[0032] Optionally, determining the initial path point and the terminal path point of the sub-area to be covered based on each sub-area to be covered and the corresponding coverage direction includes:

[0033] Rotate the current rectangle to obtain rectangle C′, so that the length direction of rectangle C′ is along the X axis;

[0034] Calculate the state Q of the first set of initial field of view centers s,1 and the state Q at the end of the visual field center e,1 ,satisfy:

[0035]

[0036] Where C1′ is the coordinate of the lower left corner of rectangle C′, C2′ is the coordinate of the lower right corner of rectangle C′, θ i is the heading angle of the first set of initial field of view center and terminal field of view center;

[0037] Calculate the state Q of the second set of initial field of view centers s,2 and the state Q at the end of the visual field center e,2 ,satisfy:

[0038]

[0039]

[0040] where π+θi is the heading angle of the second group of initial field of view center and terminal field of view center;

[0041] Calculate the states of the initial and final path points of the drone corresponding to the first set of field of view centers, where the state of the initial path point of the drone is:

[0042]

[0043] The status of the drone's final path point is:

[0044]

[0045] Let the first set of path points of the rectangle be

[0046] Calculate the states of the initial and final path points of the drone corresponding to the second set of field of view centers, where the state of the initial path point of the drone is:

[0047]

[0048] The state of the drone's final path point is

[0049]

[0050] The second set of path points of the rectangle is recorded as

[0051] Optionally, determining the initial path point and the terminal path point of the sub-area to be covered based on each sub-area to be covered and the corresponding coverage direction further includes:

[0052] For all areas to be covered and all coverage directions, the path points of the first group of all segmented rectangles are set as P (1) , and its second set of path points is set as P (2) , the number of path points in the two groups is the same, denoted by N w =2N rect .

[0053] Optionally, calculating the collaborative revisit coverage path according to the initial path point and the terminal path point of the sub-area to be covered includes:

[0054] If there is no prior grouping, automatic grouping is performed to minimize the difference in the number of drones in each group. Suppose the jth group (j = 1, 2, L, N g ) The number of drones is n j , N rect The rectangle is divided into N g groups, so that the difference between the number of rectangles in the group with the most rectangles and the group with the least rectangles is the smallest. Let the jth group (j = 1, 2, L, Ng ) The number of rectangles is m j indivual;

[0055] Assign all the segmented rectangles to each group;

[0056] According to the path point access list of each group of drones, a closed curve is generated for each group of drones, where the generated closed curve consists of 2m j The Dubins curve is composed of segments, for p = 1, 2, L, 2m j The starting state of the pth segment Dubins curve is the Dth segment j (p) Group C j (p) path point states, the end point state is the Dth j The Cth in the (p+1) group j The states of (p+1) waypoints.

[0057] Optionally, assign all the segmented rectangles to each group including:

[0058] Let M1 = 0, where j = 1, 2, L, N g ;

[0059] For j = 1, 2, L, N g ,

[0060] Let the rectangular sequence number set that the j-th group of drones needs to cover be B j ={M j +1,M j +2,L,M j+1};

[0061] Let the number of path points that the jth group of drones needs to visit be 2m j +1, the order of path point visits is C j ={2M j +1,2M j +2,2M j +3,L,2M j+1 ,2M j +1}, where the last point coincides with the starting point to form a closed route;

[0062] When m j When is an odd number, let the group number visiting each path point be D j ={1,1,2,2,L,1,1,1};

[0063] When m j When is an even number, let the group number visiting each path point be D j ={1,1,2,2,L,2,2,1}.

[0064] An embodiment of the present application also proposes a drone cluster multifunctional area revisit coverage system, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the steps of the drone cluster multifunctional area revisit coverage method as described above are implemented.

[0065] The embodiments of the present application provide an efficient solution for the "area revisit coverage problem of drone clusters" based on area segmentation, which can adapt to multiple groups and revisit coverage of multiple areas from multiple angles.

[0066] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0068] Figure 1 This is a basic flow diagram of the multifunctional area revisit coverage method of a drone swarm according to an embodiment of the present application;

[0069] Figure 2 This is a schematic diagram of the drone detection area of ​​the drone cluster multifunctional area revisit coverage method in the embodiment of the present application;

[0070] Figure 3 This is a revisit coverage route (1 area, 2 directions, 2 groups) for implementing the calculation example of the multifunctional area revisit coverage method of the drone cluster in the embodiment of the present application;

[0071] Figure 4 Another example of a revisit coverage route (2 areas, 2 directions, 3 groups) is implemented for the multifunctional area revisit coverage method of the drone cluster in the embodiment of the present application. DETAILED DESCRIPTION

[0072] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0073] The present application embodiment provides a method for revisiting and covering a multifunctional area of ​​a drone cluster. The method of the present application is based on the following:

[0074] The installation angle of the onboard sensors of each drone is the same and fixed.

[0075] The target maximum speed is less than the cruising speed of the UAV when performing a revisit coverage mission.

[0076] like Figure 1 As shown, the method of the present application comprises the following steps:

[0077] In step S101, the parameters of the area revisit coverage of the drone cluster are configured, and the area convex hull polygon is calculated. Figure 2 As shown in the figure, the parameters for configuring the area revisit coverage of the drone cluster include:

[0078] Define the cruising speed of each drone in the drone cluster as V uav Each drone is equipped with an optoelectronic camera, whose field of view is a rectangular area of ​​L1×L2. The detection deviation angle of the detection equipment on the drone (the angle between the flight direction of the drone and the line connecting the drone position and the center of the field of view) is α, and the distance between the center of the field of view and the position of the drone is d. The area coverage requires the detection overlap rate to be ρ, (0<ρ<1) to facilitate subsequent image stitching and other work. The height of the effective detection area is still recorded as L1=(1-2ρ)L1.

[0079] Given one or more regions to be covered. Each region may be convex or concave. The number of regions is N. A . The number of coverage directions is recorded as N D . The number of drone clusters is recorded as N g .

[0080] The regional revisit coverage problem of the drone cluster in the embodiment of the present application is to plan a collaborative revisit coverage path for each group of drone clusters so that each area to be covered is revisited from multiple angles, that is, each point therein can be revisited from multiple angles at regular intervals.

[0081] In step S102, the region coverage direction is determined according to the length direction of the calculated region convex hull polygon.

[0082] In step S103, based on the area coverage direction, the area to be covered is divided to obtain a plurality of sub-areas to be covered and corresponding coverage directions.

[0083] In step S104, the initial path point and the terminal path point of the sub-area to be covered are determined based on each sub-area to be covered and the corresponding coverage direction.

[0084] In step S105, a collaborative revisit coverage path is calculated according to the initial path point and the terminal path point of the sub-area to be covered.

[0085] The embodiments of the present application provide an efficient solution for the "area revisit coverage problem of drone clusters" based on area segmentation, which can adapt to multiple groups and revisit coverage of multiple areas from multiple angles.

[0086] In some embodiments, calculating the convex hull polygon of the region includes:

[0087] For each area A to be covered l (l=1,2,L,N A ), select a set number of points, then the selected points form a polygon;

[0088] Calculating the convex polygon of the polygon using a Graham scan algorithm;

[0089] The vertex set of the convex polygon to be calculated is {p1,p2,L,p J-1 ,p J}, where p1 is the point with the smallest ordinate and the leftmost position.

[0090] In some embodiments, determining the area coverage direction according to the length direction of the calculated area convex hull polygon includes:

[0091] For each area A to be covered l (l=1,2,L,N A ), use the radial function method to calculate the length direction of its convex polygon;

[0092] The main scanning direction is determined according to the length direction, and the clock angle of the main scanning direction is recorded as θ opt .

[0093] Determine the angle of each scanning direction as Where i=1,2,L,N D .

[0094] In some embodiments, based on the area coverage direction, segmenting the area to be covered to obtain multiple sub-areas to be covered and corresponding coverage directions includes:

[0095] For each area A to be covered l (l=1,2,L,N A ), for each coverage direction θ i (i=1,2,L,N D ) The region is segmented as follows:

[0096] Using the coverage direction angle θi And the corresponding rotation matrix, rotate the area to be covered by θ i degrees, for example, the area to be covered is rotated clockwise by θ i degrees, then the rotated area A (i) The coverage direction angle is 0.

[0097] Calculation area A (i) The minimum and maximum ordinate values ​​of all vertices are denoted by y min and max , and record y0=y min .

[0098] Calculate the number of rectangles divided in is a round-up function, and L1 is the detection field width of the UAV.

[0099] For n = 1, 2, L, N R -1, calculate the vertical coordinate as y n =y min +nL1 horizontal straight line and area A (i) The intersection of the boundaries, then the nth rectangle is the one whose ordinate is in the interval [y n-1 ,y n ] is the minimum bounding rectangle of a polygon formed by all the vertices and intersection points of ].

[0100] For n = N R , the corresponding rectangle is the one with ordinate in the interval [y n-1 ,y n The bounding rectangle of the polygon formed by all the vertices and intersection points of ] has a height of L1.

[0101] Rotate all rectangles in the opposite direction by θ i degrees, for example, counterclockwise rotation θ i degree, and obtain the original area A to be covered l Rectangular region segmentation.

[0102] Suppose that for all areas to be covered and all scanning directions, a total of N rect A rectangle.

[0103] For each area A to be covered l (l=1,2,L,N A ), for each coverage direction θ i (i=1,2,L,N D ), for each rectangle C segmented, determine the states of the initial path points and the final path points covering the rectangle according to the following steps:

[0104] Rotate the current rectangle, for example, rotate the current rectangle clockwise to obtain rectangle C′, so that the length direction of rectangle C′ is along the X-axis.

[0105] Calculate the state Q of the first set of initial field of view centers s,1 and the state Q at the end of the visual field center e,1 ,satisfy:

[0106]

[0107] Where C1′ is the coordinate of the lower left corner of rectangle C′, C2′ is the coordinate of the lower right corner of rectangle C′, θ i is the heading angle of the first set of initial field of view center and terminal field of view center.

[0108] Calculate the state Q of the second set of initial field of view centers s,2 and the state Q at the end of the visual field center e,2 ,satisfy:

[0109]

[0110] where π+θ i is the heading angle of the second group of initial field of view center and terminal field of view center;

[0111] Calculate the states of the initial and final path points of the drone corresponding to the first set of field of view centers, where the state of the initial path point of the drone is:

[0112]

[0113] The status of the drone's final path point is:

[0114]

[0115] Let the first set of path points of the rectangle be

[0116] Calculate the states of the initial and final path points of the drone corresponding to the second set of field of view centers, where the state of the initial path point of the drone is:

[0117]

[0118] The state of the drone's final path point is

[0119]

[0120] The second set of path points of the rectangle is recorded as

[0121] In some embodiments, determining the initial path point and the terminal path point of the sub-area to be covered based on each sub-area to be covered and the corresponding coverage direction further includes:

[0122] For all areas to be covered and all coverage directions, the path points of the first group of all segmented rectangles are set as P (1) , and its second set of path points is set as P (2) , the number of path points in the two groups is the same, denoted by N w =2N rect . Each path point corresponds to a desired heading angle, and each drone is required to reach a certain path point at a corresponding heading angle. In addition, to avoid collisions between drones, the height of each path point can be designed. For example, for each area to be covered, the corresponding coverage direction θ i The waypoints are set at different heights.

[0123] In some embodiments, calculating the collaborative revisit coverage path according to the initial path point and the terminal path point of the sub-area to be covered includes:

[0124] If there is no prior grouping, automatic grouping is performed to minimize the difference in the number of drones in each group. Suppose the jth group (j = 1, 2, L, N g ) The number of drones is n j , N rect The rectangle is divided into N g groups, so that the difference between the number of rectangles in the group with the most rectangles and the group with the least rectangles is the smallest. Let the jth group (j = 1, 2, L, N g ) The number of rectangles is m j indivual;

[0125] Assign all the segmented rectangles to each group;

[0126] According to the path point access list of each group of drones, a closed curve is generated for each group of drones, where the generated closed curve consists of 2m j The Dubins curve is composed of segments, for p = 1, 2, L, 2m j The starting state of the pth segment Dubins curve is the Dth segment j (p) Group C j (p) path point states, the end point state is the Dth j The Cth in the (p+1) group j The states of (p+1) waypoints.

[0127] In some embodiments, assigning all segmented rectangles to each group includes:

[0128] Let M1 = 0, where j = 1, 2, L, N g ;

[0129] For j = 1, 2, L, N g ,

[0130] Let the rectangular sequence number set that the j-th group of drones needs to cover be B j ={M j +1,M j +2,L,M j+1};

[0131] Let the number of path points that the jth group of drones needs to visit be 2m j +1, the waypoints are visited in order of C j ={2M j +1,2M j +2,2M j +3,L,2M j+1 ,2M j +1}, where the last point coincides with the starting point to form a closed route;

[0132] When m j When it is an odd number, let the group number of each path point visited (corresponding to the path point from the first group P (1) Or the second group P (2) D j ={1,1,2,2,L,1,1,1};

[0133] When m j When is an even number, let the group number visiting each path point be D j ={1,1,2,2,L,2,2,1}.

[0134] Figure 3 , Figure 4 An implementation example of the multifunctional area revisit coverage method of drone swarm in this application is shown. Figure 3 The figure shows the routes of two groups of clusters revisiting an area from two directions. The gray polygon is the area to be covered, the circle represents the vertex of the area, the curve is the coverage route of the cluster, the numbers around the drones are their numbers, and the rectangular shadow area is the rectangular field of view of each drone. Drones 1, 2, and 3 form the first group, and drones 4 and 5 form the second group. Figure 4 The figure shows the routes of three groups of clusters revisiting two areas from two directions. UAVs 1 and 2 form the first group, UAVs 3 and 4 form the second group, and UAV 5 is the third group alone. The second group of UAVs partially covers both the first area and the second area.

[0135] The solution of this application can be used for the problem of revisiting and covering any number of non-convex areas. This application can revisit and cover the area from multiple angles to improve the probability of target discovery.

[0136] The method of the present application realizes inter-group coordination of multiple groups of drones, and compared with traditional methods, fewer drones are required.

[0137] An embodiment of the present application also proposes a drone cluster multifunctional area revisit coverage system, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the steps of the drone cluster multifunctional area revisit coverage method as described above are implemented.

[0138] It should be noted that in the various embodiments of the present application, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0139] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0140] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0141] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A multifunctional area revisit coverage method for drone swarms, characterized in that: include: Configure the parameters of the area revisit coverage of the drone cluster and calculate the area convex hull polygon; Determine the area coverage direction according to the length direction of the calculated area convex hull polygon; Based on the area coverage direction, the area to be covered is divided to obtain multiple sub-areas to be covered and corresponding coverage directions; Determine the initial path point and the terminal path point of the sub-area to be covered based on each sub-area to be covered and the corresponding coverage direction; The collaborative revisit coverage path is calculated based on the initial path point and the terminal path point of the sub-area to be covered.

2. The multifunctional area revisit coverage method of drone cluster as claimed in claim 1, characterized in that: The parameters for configuring the area revisit coverage of the drone cluster include: Define the cruising speed of each drone in the drone cluster as V uav ; The detection deviation angle of the detection equipment on the drone is α, the distance between the center of the field of view and the position of the drone is d, and the detection overlap rate required for regional coverage is ρ; Computing the convex hull polygon of a region involves: For each area A to be covered l ,l=1,2,L,N A , N A is the number of areas to be covered, select a set number of points, and the selected points form a polygon; Calculating the convex polygon of the polygon using a Graham scan algorithm; The vertex set of the convex polygon to be calculated is {p1,p2,L,p J-1 ,p J }, where p1 is the point with the smallest ordinate and the leftmost position.

3. The multifunctional area revisit coverage method of drone cluster as claimed in claim 2, characterized in that: Determining the area coverage direction according to the length direction of the calculated area convex hull polygon includes: For each area A to be covered l , use the radial function method to calculate the length direction of its convex polygon; The main scanning direction is determined according to the length direction, and the clock angle of the main scanning direction is recorded as θ opt ; Determine the angle of each scanning direction as Where i=1,2,L,N D , N D is the number of coverage directions.

4. The multifunctional area revisit coverage method of drone cluster as claimed in claim 2, characterized in that: Based on the area coverage direction, the area to be covered is divided to obtain multiple sub-areas to be covered and the corresponding coverage directions include: For each area A to be covered l (l=1,2,L,N A ), for each coverage direction θ i (i=1,2,L,N D ) The region is segmented as follows: Using the coverage direction angle θ i And the corresponding rotation matrix, rotate the area to be covered by θ i degrees, then the rotated area A (i) The coverage direction angle is 0; Calculation area A (i) The minimum and maximum ordinate values ​​of all vertices; Calculate the number of rectangles divided in is the ceiling function, y min and max For area A (i) The minimum and maximum ordinate values ​​of all vertices of , L1 is the width of the drone’s detection field of view; For n = 1, 2, L, N R -1, calculate the vertical coordinate as y n =y min +nL1 horizontal straight line and area A (i) The intersection of the boundaries, then the nth rectangle is the one whose ordinate is in the interval [y n-1 ,y n ] is the minimum bounding rectangle of the polygon formed by all the vertices and intersection points of ; For n = N R , the corresponding rectangle is the one with ordinate in the interval [y n-1 ,y n The bounding rectangle of the polygon formed by all the vertices and intersection points of ], the height of the bounding rectangle is L1; Rotate all rectangles in the opposite direction by θ i degree, and obtain the original area A to be covered l Rectangular region segmentation.

5. The multifunctional area revisit coverage method of drone cluster as claimed in claim 4, characterized in that: Determining the initial path point and the terminal path point of the sub-area to be covered based on each sub-area to be covered and the corresponding coverage direction includes: Rotate the current rectangle to obtain rectangle C′, so that the length direction of rectangle C′ is along the X axis; Calculate the state Q of the first set of initial field of view centers s,1 and the state Q at the end of the visual field center e,1 ,satisfy: Where C1′ is the coordinate of the lower left corner of rectangle C′, C2′ is the coordinate of the lower right corner of rectangle C′, θ i is the heading angle of the first set of initial field of view center and terminal field of view center; Calculate the state Q of the second set of initial field of view centers s,2 and the state Q at the end of the visual field center e,2 ,satisfy: where π+θ i is the heading angle of the second group of initial field of view center and terminal field of view center; Calculate the states of the initial and final path points of the drone corresponding to the first set of field of view centers, where the state of the initial path point of the drone is: The status of the drone's final path point is: Let the first set of path points of the rectangle be Calculate the states of the initial and final path points of the drone corresponding to the second set of field of view centers, where the state of the initial path point of the drone is: The state of the drone's final path point is The second set of path points of the rectangle is recorded as 6. The multifunctional area revisit coverage method of drone cluster as claimed in claim 5, characterized in that: Determining the initial path point and the terminal path point of the sub-area to be covered based on each sub-area to be covered and the corresponding coverage direction also includes: For all areas to be covered and all coverage directions, the path points of the first group of all segmented rectangles are set as P (1) , and its second set of path points is set as P (2) , the number of path points in the two groups is the same, denoted by N w =2N rect , where N rect is the total number of rectangles segmented.

7. The multifunctional area revisit coverage method of drone cluster as claimed in claim 6, characterized in that: Calculating the collaborative revisit coverage path based on the initial path point and the terminal path point of the sub-area to be covered includes: If there is no prior grouping, automatic grouping is performed to minimize the difference in the number of drones in each group. Suppose the jth group (j = 1, 2, L, N g , where N g The number of drones is n j , N rect The rectangle is divided into N g groups, so that the difference between the number of rectangles in the group with the most rectangles and the number of rectangles in the group with the least rectangles is the smallest. Let the jth group (j = 1, 2, L, N g ) The number of rectangles is m j indivual; Assign all the segmented rectangles to each group; According to the path point access list of each group of drones, a closed curve is generated for each group of drones, where the generated closed curve consists of 2m j The Dubins curve is composed of segments, for p = 1, 2, L, 2m j The starting state of the pth segment Dubins curve is the Dth segment j (p) Group C j (p) path point states, the end point state is the Dth j The Cth in the (p+1) group j The states of (p+1) waypoints.

8. The multifunctional area revisit coverage method of drone cluster as claimed in claim 7, characterized in that: Assign all the split rectangles to each group including: Let M1 = 0, where j = 1, 2, L, N g ; For j = 1, 2, L, N g , Let the rectangular sequence number set that the j-th group of drones needs to cover be B j ={M j +1,M j +2,L,M j+1 }; Let the number of path points that the jth group of drones needs to visit be 2m j +1, the waypoints are visited in order of C j ={2M j +1,2M j +2,2M j +3,L,2M j+1 ,2M j +1}, where the last point coincides with the starting point to form a closed route; When m j When is an odd number, let the group number visiting each path point be D j ={1,1,2,2,L,1,1,1}; When m j When is an even number, let the group number visiting each path point be D j ={1,1,2,2,L,2,2,1}.

9. A multifunctional regional revisit coverage system for drone swarms, characterized in that: It comprises a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the multifunctional area revisit coverage method of a drone cluster as described in any one of claims 1 to 8 are implemented.

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