Multi-robot multi-area key continuous monitoring method, storage medium and electronic device

Abstract

The present invention discloses a multi-robot multi-area key continuous monitoring method, storage medium, and electronic device. The method includes: establishing a two-dimensional grid map, treating robots and targets as point masses; assigning a target influence value to the target's initial position, and causing the target influence value to propagate to the surroundings with a first gradient to establish a target influence map; assigning a robot influence value to the robot's current position, and causing it to propagate to the surroundings with a second gradient to establish a robot influence map; for a single robot, superimposing the robot influence maps of the remaining robots and all target influence maps to obtain a comprehensive influence map; performing position allocation; updating the robot's position when the robot reaches the destination, and updating the target influence value at the sensor access position. According to the multi-robot multi-area key continuous monitoring method of the present invention, key monitoring areas can be quickly marked, allowing multiple robots to perform continuous monitoring tasks in key areas.

Description

Technical Field

[0001] The present invention relates to the field of continuous monitoring technology, and in particular to a multi-robot multi-area key continuous monitoring method, a storage medium and an electronic device. Background Art

[0002] Confined spaces present the potential for unknown threats, as moving targets such as people and vehicles may emerge from hidden passages or escape monitoring at any time. These unknown risks can trigger dynamic events such as robot destruction or the placement of potentially threatening equipment within the space. This often requires the coordination of multiple robots to continuously monitor abnormal areas. Active targets influence the importance of related areas, and their impact propagates from their location of appearance, making these areas key areas. When an abnormality occurs in a local area requiring focused and continuous monitoring, robots must prioritize or frequently visit these areas. In multi-robot continuous monitoring missions, these key areas must be quickly marked to increase the frequency of robot visits.

[0003] Figure 1' Middle D im0 Indicates the key area where the target emerges from the secret passage, D im1 Indicates the key area where robot failure occurs, D im2 Indicates the key area where the target leaves the monitoring range, D im1 With D im2 Intersecting areas are generated. The key areas generated by different targets may overlap. The importance of the overlapping area is greater than the importance of the area affected by a single target and deserves more attention. Therefore, it is necessary to explore a method to integrate the importance of multiple key areas. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention proposes a multi-robot multi-area continuous key monitoring method, which can quickly mark key monitoring areas.

[0005] The present invention also provides a computer-readable storage medium.

[0006] The present invention also provides an electronic device.

[0007] According to a first embodiment of the present invention, a multi-robot multi-area focused continuous monitoring method is provided for allocating target locations of multiple robots in a task area, wherein the robots are provided with sensors for accessing the task area, the task area is provided with a passageway for the robots to travel, and the task area contains multiple targets, each of which affects the importance of a certain area. The method includes:

[0008] Evenly dividing the task area into a plurality of grids on a two-dimensional plane to establish a two-dimensional grid map, and considering the robot and the target as mass points on the two-dimensional grid map;

[0009] Assigning a target influence value to the initial position of the target, and propagating the target influence value to the surrounding areas with a first gradient to establish a target influence graph;

[0010] Assigning a robot influence value to the current position of the robot, and propagating the robot influence value to the surrounding areas with a second gradient to establish a robot influence graph;

[0011] For a single robot, the robot influence diagrams of the remaining robots and all the target influence diagrams are superimposed to obtain a comprehensive influence diagram, wherein each position of the comprehensive influence diagram has a comprehensive influence value;

[0012] Perform location-allocation:

[0013] Obtaining adjacent positions of the robot;

[0014] If the number of the adjacent positions is greater than 1, selecting the one with the largest comprehensive influence value among the adjacent positions as the pre-allocated position; otherwise, updating the pre-allocated position with the only adjacent position;

[0015] If the current position allocation is the wth time, and the current position of the robot, the pre-allocated position, and the positions of the robot during the (w-1)th and (w-2)th allocations together cover the four vertices of the rectangle, then a self-loop is executed to update the pre-allocated position with the adjacent positions excluding the four positions of the rectangle;

[0016] Taking the pre-assigned position as the destination position, and moving the robot toward the destination position;

[0017] updating the position of the robot when the robot reaches the destination position, and updating the target impact value at the sensor access position;

[0018] The target impact value and the robot impact value are interrupted when encountering obstacles in the propagation direction.

[0019] According to the multi-robot multi-area continuous monitoring method of an embodiment of the present invention, facing the complex scenario where multiple key areas appear simultaneously in a limited space, the position of each robot is allocated from a global optimal perspective based on the influence diagram, which can achieve rapid response to multiple areas at the same time.

[0020] In addition, the multi-robot multi-area continuous monitoring method according to an embodiment of the present invention also has the following additional technical features:

[0021] According to some embodiments of the present invention, the initial position p(x, y) of the target is the propagation center. Assume that the target influence value at p is positive, and the initial values ​​of the target influence values ​​at other positions in the two-dimensional grid map are 0. The following propagation model is established:

[0022] The influence is propagated by moving from point p on the two-dimensional grid map using the propagation matrix M:

[0023]

[0024] Where m 22 =1; the value range of the remaining elements is (0,1), indicating that the farther away from the propagation center, the greater the attenuation of the target influence value; the matrix P represents the adjacent positions of p:

[0025]

[0026] Where p 22 =p; the matrix O represents the target impact value of the elements in P, and the arrangement position of the target impact value corresponds to the position of the elements in P:

[0027]

[0028] Define the matrix operator @:

[0029]

[0030] Update the matrix O according to the following formula:

[0031] O=O@M

[0032] The above process is a propagation process of the target influence value, and the remaining elements in P are used as new propagation centers in turn to move the propagation matrix M, while updating the matrix P and the target influence value of each element in P.

[0033] In some embodiments of the present invention, the robot influence value is a negative value, and the robot influence value is propagated using the propagation model.

[0034] According to some embodiments of the present invention, the number of locations visited by the robot within the certain area within a specified time T is used as the access efficiency E T Calculate E according to the following formula T :

[0035]

[0036] Where, ||J v || represents the set of locations J visited within the certain area v The size of || Jdot || represents the location set J within the certain area dot size.

[0037] In some specific embodiments of the present invention, the specified time T is calculated according to the following formula:

[0038]

[0039] Where n is the number of robots; |v| is the average speed of the robots; the middle{·} operation means that after arranging the contents in {} in descending order, the largest value in the middle is taken; when the number of elements in {} is even, the median is the arithmetic mean of the two middle values; Dist k is the kth robot and J dot The minimum Manhattan distance between the elements in .

[0040] According to some embodiments of the present invention, executing the jump out of the self-loop further comprises:

[0041] The adjacent position with the largest comprehensive influence value is selected as the pre-allocated position.

[0042] According to some embodiments of the present invention, the target influence value is cleared when the mesh or a vertex of the mesh is accessed.

[0043] According to some embodiments of the present invention, a vertex of the mesh located in the channel is used as the position of the target, and the target influence value of the vertex is calculated based on the target influence values ​​of the meshes surrounding the vertex;

[0044] A vertex of the mesh located in the channel is used as the position of the robot, and the robot influence value of the vertex is calculated according to the robot influence values ​​of the mesh surrounding the vertex.

[0045] According to the computer-readable storage medium of the second embodiment of the present invention, a computer program is stored thereon, and when the computer program is executed by a processor, the multi-robot multi-area key continuous monitoring method as described in the first embodiment of the present invention is implemented.

[0046] According to the computer-readable storage medium of an embodiment of the present invention, in the face of a complex scenario in which multiple key areas of interest appear simultaneously in a limited space, the position of each robot is allocated from a global optimal perspective based on the influence diagram, which can achieve rapid response to multiple areas at the same time.

[0047] According to an electronic device of an embodiment of the third aspect of the present invention, the electronic device includes a processor and a memory, the processor and the memory are connected, and the memory is used to store a computer program. When the computer program is executed by the processor, the multi-robot multi-area key continuous monitoring method as described in the embodiment of the first aspect of the present invention is implemented.

[0048] According to the electronic device of the embodiment of the present invention, facing the complex scenario where multiple key areas of interest appear simultaneously in a limited space, the position of each robot is allocated from a global optimal perspective based on the influence diagram, which can achieve rapid response to multiple areas at the same time.

[0049] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1' It is a schematic diagram of multiple key areas in a limited space;

[0051] Figure 1 is a finite space grid map according to an embodiment of the present invention;

[0052] Figure 2 is a schematic diagram of force propagation according to an embodiment of the present invention;

[0053] Figure 3 (a) is a schematic diagram of multiple non-overlapping impact areas according to an embodiment of the present invention;

[0054] Figure 3 (b) is a schematic diagram of overlapping multiple impact areas according to an embodiment of the present invention;

[0055] Figure 4 is a propagation schematic diagram of a propagation matrix according to an embodiment of the present invention;

[0056] Figure 5 is a trajectory planning flow chart according to an embodiment of the present invention;

[0057] Figure 6 4 is a flow chart of a single-step position allocation method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0059] The following describes a multi-robot multi-area focused continuous monitoring method according to a first embodiment of the present invention with reference to the accompanying drawings.

[0060] According to an embodiment of the present invention, a multi-robot multi-area focused continuous monitoring method is used to assign target locations to multiple robots within a mission area. The robots are equipped with sensors for accessing the mission area, and the mission area is provided with a passageway for the robots to travel. The mission area contains multiple targets, each of which affects the importance of a certain area. The method includes:

[0061] The task area is evenly divided into multiple grids on a two-dimensional plane to establish a two-dimensional grid map, and the robot and the target are regarded as mass points on the two-dimensional grid map;

[0062] Assign a target influence value to the initial position of the target, and propagate the target influence value to the surrounding areas with the first gradient to establish a target influence graph;

[0063] Assigning a robot influence value to the current position of the robot, and propagating the robot influence value to the surrounding areas with a second gradient to establish a robot influence graph;

[0064] For a single robot, the robot influence diagrams of the remaining robots and all target influence diagrams are superimposed to obtain a comprehensive influence diagram, where each position in the comprehensive influence diagram has a comprehensive influence value;

[0065] Perform location-allocation:

[0066] Get the robot's adjacent position;

[0067] If the number of adjacent positions is greater than 1, the one with the largest comprehensive influence value among the adjacent positions is selected as the pre-allocated position; otherwise, the pre-allocated position is updated with the only adjacent position;

[0068] If the current position allocation is the wth time, and the robot's current position, pre-allocated position, and the robot's positions during the (w-1)th and (w-2)th allocations all cover the four vertices of the rectangle, then the execution jumps out of the self-loop and updates the pre-allocated position with the adjacent positions other than the four positions of the rectangle;

[0069] The pre-assigned position is used as the destination position, and the robot is moved toward the destination position;

[0070] Update the robot's position when it reaches the destination, and update the target impact value at the sensor access location;

[0071] Among them, the propagation of the target impact value and the robot impact value is interrupted when they encounter obstacles in the propagation direction.

[0072] To focus on a local area, we first need to determine the key access range. The initial location of the target, p(x,y), is the propagation center. The target influence value at p is set to a positive value, and the initial value of the target influence value at other locations in the two-dimensional grid map is 0. The key access range is determined by the propagation range of the influence value at p, and the following propagation model is established:

[0073] The influence is propagated by moving from point p on a two-dimensional grid map using the propagation matrix M:

[0074]

[0075] Where m 22 =1; the value range of the remaining elements is (0,1), which means that the farther away from the propagation center, the greater the attenuation of the target influence value; the matrix P represents the adjacent positions of p:

[0076]

[0077] Where p 22 =p; the matrix O represents the target impact value of the elements in P, and the arrangement position of the target impact value corresponds to the position of the elements in P:

[0078]

[0079] Define the matrix operator @:

[0080]

[0081] Update the matrix O according to the following formula:

[0082] O=O@M (5)

[0083] The above process is a propagation process of the target influence value. The remaining elements in P are used as new propagation centers in turn to move the propagation matrix M. During each propagation process, the matrix P and the target influence value of each element in P are updated according to equations (2) to (5). Ultimately, the influence of the target on the robot trajectory planning is quantified.

[0084] Similarly, in order to disperse the robots, the robot influence value is negative, and the above propagation model is used to propagate the influence of multiple robots on each other.

[0085] In order to reflect the response effect of the robot in performing continuous monitoring tasks in key areas, the number of locations that the robot visits within a certain area within a specified time is used as the access efficiency E T Calculate E according to the following formula T :

[0086]

[0087] Where, ||J v|| represents the set of visited locations J within a certain area v The size of || J dot || represents the location set J within a certain area dot size.

[0088] The specified time T is calculated according to the following formula:

[0089]

[0090] Where n is the number of robots; |v| is the average speed of the robots; the middle{·} operation means that after arranging the contents in {} in descending order, the largest value in the middle is taken; when the number of elements in {} is even, the median is the arithmetic mean of the two middle values; Dist k is the kth robot and J dot The minimum Manhattan distance between the elements in .

[0091] In some embodiments of the present invention, the target influence value is reset to zero when a mesh or a vertex of the mesh is accessed, and the corresponding value is calculated based on the target influence value or robot influence value of the meshes surrounding the vertex.

[0092] Specifically, in Figure 1 The xOy coordinate system is established on the grid map D shown in the figure. The black thick solid line represents the obstacle, and the dot represents the robot r1. The robot r1 needs to visit the key area D as soon as possible along the dotted arrow. im . F g A free vertex.

[0093] Assume the robot walks along a free vertex. To enable the robot to quickly patrol key areas, the influence of the target should be able to propagate to the robot and generate an attractive force on it. To enable the robot to perform continuous monitoring tasks in a decentralized manner, assume that the robot exerts an influence on the surrounding area centered on its location. This influence should be able to propagate to the other robots and generate a repulsive force on them.

[0094] In order to quantitatively describe the above effects of multiple targets and multiple robots, the following constraints are imposed:

[0095] ① Ignore factors such as the target's mass, shape, and structure, and treat the target as a point mass.

[0096] ② The robot can only move to the unoccupied vertices in its four neighborhoods, and the speed direction is one of the four directions: up, down, left, and right. The speeds of the n robots are the same.

[0097] ③ The target moves along the grid vertices and moves to one of the four adjacent positions: up, down, left, and right with equal probability.

[0098] ④ The target has a virtual attractive force on the robot that spreads outwards from the target's initial position, and the robots have a virtual repulsive force on each other that spreads outwards from their respective positions.

[0099] ⑤ The attraction of the target to the robot and the repulsion between the robots weaken as the distance increases.

[0100] ⑥ Both the attractive force and the repulsive force propagate in eight directions: up, down, left, right, upper left, upper right, lower left and lower right, and propagate in one direction starting from the initial propagation position.

[0101] ⑦ The influence areas between targets, between robots, and between targets and robots can be superimposed.

[0102] ⑧The propagation is interrupted when encountering a wall blocking the propagation direction.

[0103] like Figure 2 As shown in the figure, the white hollow circle represents the robot or target, and the arrows represent the transmission of virtual force in various directions. At each level of transmission, the force in the up-down-left-right-up-right, down-left-down, and down-right directions is stronger than the force in the up-left, up-right, down-left, and down-right directions.

[0104] exist Figure 3 In the 28×23 grid map shown, the positions of the three targets are (8,19), (15,13) and (18,17) respectively. Figure 3 The three impact areas circled by dashed lines in (a) do not overlap, and the target has the same impact on each position within the impact area. Figure 3 In (b), the impact of the target decreases from the center to the edges of the three impact zones A, B, and C, as indicated by the color change from dark to light. According to the agreed-upon direction of impact propagation, zone A is unobstructed by the wall, while zones B and C are each obstructed by the wall. The dotted box indicates the overlap between zones A and B. The color of the overlapping zone is darker than that of the individual zones, indicating that the overlapping zone is more important than the individual zones.

[0105] Assume that the detection range of the sensor is 4 grids around the current position of the robot. In order to quantify the influence of the target on the importance of the region, the propagation of attraction is described as the propagation of the influence value at the initial position of the target on the grid map according to equations (2) to (5). Figure 4 The propagation matrix M shown in (a) is:

[0106]

[0107] Figure 4 In (b), the initial influence value 2 is set for the initial propagation position p:

[0108]

[0109] Figure 4 (c) Update P to propagate vertex p ij The impact value o ij :

[0110]

[0111] The remaining vertices in P are used as the centers of the propagation matrix M, such as Figure 4 (d) The vertex to the left of the initial propagation position p, performs @ operation on O centered at this point, Figure 4 Update the impact value of O in (e).

[0112] Considering the limited range of a target's movement within a certain period of time and the fact that walls can block the spread of influence, the propagation distance of M is limited. A movement threshold is set for M, and propagation stops when the number of moves exceeds the threshold.

[0113] When the distance between the robot and the initial position of the target is far, the influence of the target may spread over a wider range. Therefore, the distance between the robot and the target is a factor that should be considered when selecting the threshold.

[0114] Thus, by propagating the initial target influence value on the grid map, a target influence graph is generated. The difference between the robot influence graph and the target influence graph is that the influence of other robots on the robot is repulsive, so the initial influence value of the robot influence graph is negative.

[0115] Single robot k The comprehensive influence diagram of is the result of superimposing all target influence diagrams and the influence diagrams of the remaining robots. Considering the decrease in the importance of the locations visited by the robot, the target influence values ​​of the visited vertices on the comprehensive influence diagram are set to 0. k When assigning positions, the influence value of any position This should be the sum of all targets and other robots' influence values ​​here:

[0116]

[0117] Where, objim i The impact value generated by the target i at this location; robim i is the robot r that is transmitted to this location i The impact value generated.

[0118] Based on the target influence diagram, robot influence diagram, and robot comprehensive influence diagram, the trajectory planning process is designed as follows Figure 5 As shown:

[0119] ① Calculate the single target influence diagram and superimpose all target influence diagrams.

[0120] ②To the robot k For , the influence graphs of the remaining robots are calculated and superimposed.

[0121] ③To the robot k In terms of the superposition of the results of ① and ②, we get the robot r k The comprehensive impact diagram.

[0122] ④Assign robot r k The adjacent positions on the comprehensive influence diagram are selected according to the single-step position allocation method.

[0123] ⑤The positions of the remaining robots are assigned according to ②~④.

[0124] When the robot occupies a grid vertex, it visits the vertex and the influence value of the target on the vertex is cleared. After the robot reaches the assigned position, the comprehensive influence graph is updated.

[0125] In order to avoid conflicts between the two robots in planning positions, the following Figure 6 The single-step position allocation method shown in the figure selects the vertex with the largest comprehensive influence value on the comprehensive influence diagram when the robot is prohibited from turning back or self-looping:

[0126] ① Find the adjacent position set N of the robot's current position f When N f When the number of vertices is greater than 1, the point with the largest comprehensive influence value on the comprehensive influence diagram is selected according to the no-turnback strategy:

[0127]

[0128] U(u,w)=IM -1 (u,w), if |N f |>1 (13)

[0129] Where IM(u,w) is the N f The maximum influence value of the middle vertex on the comprehensive influence diagram; is vertex p i The influence value of; U(u,w) is the utility function of assigning a single-step position u to the robot. f When there is only one vertex in the list, assign that vertex to the robot.

[0130] ②When the robot has a self-loop p1p2p3p4, from N f Exclude the points in the self-loop, that is, The point with the largest influence value on the comprehensive influence diagram among the remaining adjacent positions is selected as the pre-allocated position.

[0131] According to the multi-robot multi-area continuous monitoring method of an embodiment of the present invention, facing the complex scenario where multiple key areas appear simultaneously in a limited space, the position of each robot is allocated from a global optimal perspective based on the influence diagram, which can achieve rapid response to multiple areas at the same time.

[0132] According to the computer-readable storage medium of the second embodiment of the present invention, a computer program is stored thereon, and when the computer program is executed by a processor, the multi-robot multi-area key continuous monitoring method as described in the first embodiment of the present invention is implemented.

[0133] According to the computer-readable storage medium of an embodiment of the present invention, in the face of a complex scenario in which multiple key areas of interest appear simultaneously in a limited space, the position of each robot is allocated from a global optimal perspective based on the influence diagram, which can achieve rapid response to multiple areas at the same time.

[0134] According to the electronic device of the third aspect embodiment of the present invention, the electronic device includes a processor and a memory, the processor and the memory are connected, the memory is used to store a computer program, and when the computer program is executed by the processor, the multi-robot multi-area key continuous monitoring method as described in the first aspect embodiment of the present invention is implemented.

[0135] According to the electronic device of the embodiment of the present invention, facing the complex scenario where multiple key areas of interest appear simultaneously in a limited space, the position of each robot is allocated from a global optimal perspective based on the influence diagram, which can achieve rapid response to multiple areas at the same time.

[0136] Other structures and operations of the electronic device according to the embodiment of the present invention are known to those skilled in the art and will not be described in detail here.

[0137] In the description of the present invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0138] In the description of the present invention, "a first feature" or "a second feature" may include one or more such features. A first feature being "above" or "below" a second feature may include the first and second features being in direct contact, or may also include the first and second features being in contact not directly but through another feature therebetween. A first feature being "above," "above," or "above" a second feature may include the first feature being directly above or obliquely above the second feature, or may simply mean that the first feature is at a higher level than the second feature.

[0139] It should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "connected" and "connection" should be understood in a broad sense. For example, they can refer to fixed connection, detachable connection, or integral connection; mechanical connection, electrical connection; direct connection, indirect connection through an intermediate medium, or internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0140] Throughout this specification, references to terms such as "one embodiment," "some embodiments," "specific embodiments," "example," or "some examples" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0141] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

Claims

1. A multi-robot multi-area continuous monitoring method, characterized in that: The method is used to assign target positions of multiple robots in a task area, wherein the robots are provided with sensors for accessing the task area, the task area is provided with a passageway for the robots to travel, and the task area contains multiple targets, each of which affects the importance of a certain area. The method includes: Evenly dividing the task area into a plurality of grids on a two-dimensional plane to establish a two-dimensional grid map, and considering the robot and the target as mass points on the two-dimensional grid map; Assigning a target influence value to the initial position of the target, and propagating the target influence value to the surrounding areas with a first gradient to establish a target influence graph; Assigning a robot influence value to the current position of the robot, and propagating the robot influence value to the surrounding areas with a second gradient to establish a robot influence graph; For a single robot, the robot influence diagrams of the remaining robots and all the target influence diagrams are superimposed to obtain a comprehensive influence diagram, wherein each position of the comprehensive influence diagram has a comprehensive influence value; Perform location-allocation: Obtaining adjacent positions of the robot; If the number of the adjacent positions is greater than 1, selecting the one with the largest comprehensive influence value among the adjacent positions as the pre-allocated position; otherwise, updating the pre-allocated position with the only adjacent position; If the current position allocation is the wth time, and the current position of the robot, the pre-allocated position, and the positions of the robot during the (w-1)th and (w-2)th allocations together cover the four vertices of the rectangle, then a self-loop is executed to update the pre-allocated position with the adjacent positions excluding the four positions of the rectangle; Taking the pre-assigned position as the destination position, and moving the robot toward the destination position; updating the position of the robot when the robot reaches the destination position, and updating the target impact value at the sensor access position; The target impact value and the robot impact value are interrupted when encountering obstacles in the propagation direction.

2. The multi-robot multi-area continuous monitoring method according to claim 1, characterized in that: The initial position p(x, y) of the target is the propagation center. Assume that the target influence value at p is positive and the initial values ​​of the target influence values ​​at other positions in the two-dimensional grid map are 0. The following propagation model is established: The influence is propagated by moving from point p on the two-dimensional grid map using the propagation matrix M: Where m 22 =1; the value range of the remaining elements is (0,1), indicating that the farther away from the propagation center, the greater the attenuation of the target influence value; the matrix P represents the adjacent positions of p: Where p 22 =p; the matrix O represents the target impact value of the elements in P, and the arrangement position of the target impact value corresponds to the position of the elements in P: Define the matrix operator @: Update the matrix O according to the following formula: O=O@M The above process is a propagation process of the target influence value, and the remaining elements in P are used as new propagation centers in turn to move the propagation matrix M, while updating the matrix P and the target influence value of each element in P.

3. The multi-robot multi-area continuous monitoring method according to claim 2, characterized in that: The robot influence value is a negative value, and the robot influence value is propagated using the propagation model.

4. The multi-robot multi-area continuous monitoring method according to claim 1, characterized in that: The number of locations that the robot visits within the specified area within a specified time T is taken as the access efficiency E T Calculate E according to the following formula T : Where, ||J v || represents the set of locations J visited within the certain area v The size of || J dot || represents the location set J within the certain area dot size.

5. The multi-robot multi-area continuous monitoring method according to claim 4, characterized in that: The specified time T is calculated according to the following formula: Where n is the number of robots; |v| is the average speed of the robots; the middle{·} operation means that after arranging the contents in {} in descending order, the largest value in the middle is taken; when the number of elements in {} is even, the median is the arithmetic mean of the two middle values; Dist k is the kth robot and J dot The minimum Manhattan distance between the elements in .

6. The multi-robot multi-area continuous monitoring method according to claim 1, characterized in that: The execution jumps out of the self-loop further comprises: The adjacent position with the largest comprehensive influence value is selected as the pre-allocated position.

7. The multi-robot multi-area continuous monitoring method according to claim 1, characterized in that: The target influence value is cleared when the mesh or a vertex of the mesh is accessed.

8. The multi-robot multi-area continuous monitoring method according to claim 1, characterized in that: Taking a vertex of the mesh located in the channel as the position of the target, and calculating the target influence value of the vertex according to the target influence values ​​of the mesh surrounding the vertex; A vertex of the mesh located in the channel is used as the position of the robot, and the robot influence value of the vertex is calculated according to the robot influence values ​​of the mesh surrounding the vertex.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the multi-robot multi-area focused continuous monitoring method according to any one of claims 1 to 8 is implemented.

10. An electronic device, characterized in that: The electronic device includes a processor and a memory, the processor and the memory are connected, the memory is used to store a computer program, and when the computer program is executed by the processor, the multi-robot multi-area key continuous monitoring method according to any one of claims 1 to 8 is implemented.

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