A method for monitoring and controlling the area of ​​drone clusters based on ant colony pheromones

Abstract

The present invention discloses a method for monitoring and controlling a cluster area of ​​unmanned aerial vehicles based on ant colony pheromones, the method comprising: initializing a preset monitoring area as a grid unit, and setting the monitoring priority and initial attraction pheromone value of the grid unit; updating the initial attraction pheromone value according to the monitoring time of the grid unit and the monitoring priority to obtain a real-time attraction pheromone value; determining the resultant force exerted on the unmanned aerial vehicle according to the real-time attraction pheromone value and the distance vector between the unmanned aerial vehicles; and determining the flight speed of the unmanned aerial vehicle according to the resultant force exerted on the unmanned aerial vehicle. The present invention uses ant colony pheromones to quantify the monitoring status of the monitoring area to guide the unmanned aerial vehicle to search for unknown areas, guides the unmanned aerial vehicle to focus on monitoring important areas through monitoring priorities, and establishes a pheromone potential field between individual unmanned aerial vehicles in the cluster to achieve adaptive trajectory planning of the unmanned aerial vehicle.

Description

Technical Field

[0001] The present invention relates to the field of drone cluster control, and in particular to a drone cluster area monitoring and control method based on ant colony pheromones. Background Art

[0002] Drones have the advantages of small size, high mobility, free module configuration, and low cost, and can be widely used in regional surveillance scenarios. However, with the complexity of the surveillance environment, a single drone is unable to meet the mission requirements. On the one hand, for large surveillance areas, a single drone has a limited perception range, often losing sight of one thing while focusing on another, and the surveillance efficiency is low; on the other hand, a single drone cannot achieve multi-machine disaster recovery backup. The emergence of drone clusters makes up for the above shortcomings. By controlling multiple drones to collaboratively perform surveillance tasks, the surveillance efficiency is improved and the robustness of the system is enhanced.

[0003] Traditional drone swarm control is a top-down mode, which controls the flight of the swarm by presetting the flight trajectory of each drone. Although this method is simple and easy to operate, it is not adaptive and cannot achieve coordinated scheduling between individual drones in the swarm. It is only suitable for relatively fixed flight scenarios such as drone flight shows.

[0004] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0005] The technical problem to be solved by the present invention is that, in view of the above-mentioned defects of the prior art, a method for regional monitoring and control of drone clusters based on ant colony pheromones is provided, aiming to solve the problem that the methods for controlling the flight of drone clusters in the prior art are not adaptive and cannot achieve coordinated scheduling between individual drones in the cluster.

[0006] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0007] In a first aspect, an embodiment of the present invention provides a method for monitoring and controlling a drone cluster area based on ant colony pheromones, wherein the method comprises:

[0008] Initializing a preset monitoring area as a grid unit, and setting the monitoring priority and initial attraction pheromone value of the grid unit; wherein the initial attraction pheromone value is an initial value of the attraction pheromone used to drive the drone to search the monitoring area;

[0009] The initial attraction pheromone value is updated according to the monitoring time of the grid unit and the monitoring priority to obtain a real-time attraction pheromone value; wherein the monitoring time is the time during which the grid unit is not visited by the drone;

[0010] Determine the resultant force on the drone according to the real-time attraction pheromone value and the distance vector between the drones;

[0011] The flight speed of the UAV is determined according to the resultant force applied to the UAV.

[0012] In one implementation, the initializing the preset monitoring area into a grid unit and setting the monitoring priority and initial attraction pheromone value of the grid unit includes:

[0013] According to a preset monitoring accuracy, the monitoring area is divided into M×N grid units, where M is the number of grid rows and N is the number of grid columns;

[0014] Setting the monitoring priority for each grid unit respectively;

[0015] The same initial attraction pheromone value is set for all the grid cells.

[0016] In one implementation, the updating of the initial attraction pheromone value according to the out-of-monitoring duration of the grid unit and the monitoring priority to obtain the real-time attraction pheromone value includes:

[0017] The pheromone switch of the grid unit is obtained according to the out-of-monitoring time of the grid unit, wherein the pheromone switch is

[0018] Wherein, T0 represents the preset revisit time limit, t represents the time at which the grid unit is located, and t ij represents the time when the grid cell was last visited by the drone;

[0019] The initial attraction pheromone value is updated according to the pheromone switch of the grid unit and the monitoring priority to obtain the real-time attraction pheromone value, wherein the real-time attraction pheromone value is

[0020] s(p ij ,t)=(1-E)[(1-G)s(p ij ,t-1)+λ ij k ij d(p ij ,t)+g(p ij ,t)],

[0021] Among them, p ij is the grid unit of the i-th row and j-th column, i=1,...,M, j=1,...,N, E is the evaporation coefficient of the attraction pheromone value, G is the propagation coefficient of the attraction pheromone value, s(p ij ,t-1) is the grid unit p ij The pheromone value at time t-1, when t = 1, s(pij ,0) is the grid unit p ij The initial attraction pheromone value, λ ij is the grid unit p ij The monitoring priority, k ij is the grid unit p ij The pheromone switch, d(p ij ,t) is the grid unit p ij Actively released attraction pheromone value, g(p ij ,t) is the grid cell p ij All grid cells other than p are propagated to the grid cell p ij The attraction pheromone value.

[0022] In one implementation, the determining the resultant force on the drone according to the real-time attraction pheromone value and the distance vector between the drones includes:

[0023] determining a resultant force of the potential field according to the real-time attraction pheromone value;

[0024] Determine the repulsive force between the drones according to the distance vector between the drones;

[0025] The resultant force acting on the UAV is obtained according to the resultant force of the potential field and the repulsive force between the UAVs.

[0026] In one implementation, determining the resultant force of the potential field according to the real-time attraction pheromone value includes:

[0027] Obtaining a first geographic coordinate of a first drone, and selecting a grid unit to be measured;

[0028] Obtaining a first vector according to the first geographic coordinates and the center coordinates of the grid unit to be measured;

[0029] Obtaining the pheromone potential field of the first UAV according to the real-time attraction pheromone value of the grid unit to be tested and the first vector;

[0030] The resultant force of the pheromone potential field is obtained according to the pheromone potential field of the first UAV.

[0031] In one implementation, determining the repulsive force between drones according to the distance vector between drones includes:

[0032] Acquire a plurality of second drones in the monitoring area that have a positional relationship with the first drone;

[0033] Obtaining second geographic coordinates of the second drone;

[0034] Obtain a second vector according to the first geographic coordinates and the second geographic coordinates;

[0035] The repulsive force between the drones is obtained according to the second vector.

[0036] In one implementation, determining the flight speed of the drone according to the resultant force acting on the drone includes:

[0037] Set the maximum flight speed of the drone;

[0038] The flight speed of the UAV is determined according to the maximum flight speed of the UAV and the resultant force acting on the UAV.

[0039] In a second aspect, an embodiment of the present invention further provides a drone cluster area monitoring and control device based on ant colony pheromones, wherein the device comprises:

[0040] An initialization module, used to initialize the preset monitoring area into a grid unit, and set the monitoring priority and initial attraction pheromone value of the grid unit;

[0041] A real-time attraction pheromone value acquisition module, used to update the initial attraction pheromone value according to the idle time of the grid unit and the monitoring priority to obtain a real-time attraction pheromone value;

[0042] A resultant force determination module, used to determine the resultant force exerted on the drone according to the real-time attraction pheromone value and the distance vector between the drones;

[0043] The flight speed determination module is used to determine the flight speed of the UAV according to the resultant force acting on the UAV.

[0044] In a third aspect, the present invention further provides a drone, wherein the drone includes a memory, a processor, and a drone cluster area monitoring and control program based on ant colony pheromones stored in the memory and executable on the processor, and when the processor executes the drone cluster area monitoring and control program based on ant colony pheromones, the steps of the drone cluster area monitoring and control method based on ant colony pheromones as described in any one of claims 1 to 7 are implemented.

[0045] In a fourth aspect, an embodiment of the present invention further provides a non-temporary computer-readable storage medium, wherein the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of the drone cluster area monitoring and control method based on ant colony pheromones as described in any one of claims 1 to 7 above.

[0046] Beneficial effects: The embodiment of the present invention first initializes the preset monitoring area as a grid unit, and sets the monitoring priority and initial attraction pheromone value of the grid unit; then, sets the monitoring priority for the grid unit to drive the drone to focus on monitoring the key area. In addition, in order to drive the drone to monitor the area that has been out of monitoring for a long time, the real-time attraction pheromone value is obtained by integrating the monitoring time and monitoring priority of the grid unit to attract the drone to search the monitoring area. Taking into account the distribution density of the drone, the resultant force on the drone is determined according to the real-time attraction pheromone value and the distance vector between the drones; finally, the flight speed of the drone can be determined according to the resultant force on the drone. It can be seen that the method in this embodiment achieves effective improvement in the adaptability of drone flight and the coordinated scheduling between individual drones in the cluster by establishing a pheromone potential field between individual drones in the cluster to realize adaptive trajectory planning of the drone. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] Figure 1 It is a flow chart of a method for monitoring and controlling a drone cluster area based on ant colony pheromones provided in an embodiment of the present invention.

[0049] Figure 2 It is a schematic diagram of grid unit monitoring priority provided by an embodiment of the present invention.

[0050] Figure 3 It is a schematic diagram of the track points of the drone cluster provided by an embodiment of the present invention.

[0051] Figure 4 It is a schematic diagram of the real-time attraction pheromone value distribution of the grid unit provided by an embodiment of the present invention.

[0052] Figure 5 It is a schematic diagram of the flight trajectory of a drone cluster provided by an embodiment of the present invention.

[0053] Figure 6 This is a schematic diagram of the shortest distance between drone clusters provided by an embodiment of the present invention.

[0054] Figure 7 It is a schematic diagram of the number of unknown points in the monitoring area provided by an embodiment of the present invention.

[0055] Figure 8It is a principle block diagram of a drone cluster area monitoring and control device based on ant colony pheromones provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and effect of the present invention clearer and more specific, the present invention is further described in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0057] In the prior art, the control of drone clusters is a top-down mode, in which the flight of the cluster is controlled by presetting the flight trajectory of each drone. Although this method is simple and easy to operate, it is not adaptive and cannot achieve coordinated scheduling between individual drones in the cluster. It is only suitable for relatively fixed flight scenarios such as drone flight performances.

[0058] In order to solve the problems of the prior art, this embodiment provides a method for monitoring and controlling the area of ​​a drone cluster based on ant colony pheromones, which uses pheromones to quantify the monitoring state of the monitoring area to guide the drone to search for unknown areas, guides the drone to focus on monitoring important areas through monitoring priorities, and establishes a pheromone potential field between individual drones in the cluster to achieve adaptive trajectory planning of the drone. In specific implementation, the preset monitoring area is first initialized as a grid unit, and the monitoring priority and initial attraction pheromone value of the grid unit are set; then, the monitoring priority is set for the grid unit to drive the drone to focus on monitoring the key area. In addition, in order to drive the drone to monitor the area where it has been out of monitoring for a long time, the real-time attraction pheromone value is obtained by integrating the out-of-monitoring time and monitoring priority of the grid unit to attract the drone to search the monitoring area. Considering the distribution density of the drone, the resultant force on the drone is determined according to the real-time attraction pheromone value and the distance vector between the drones; finally, the flight speed of the drone can be determined according to the resultant force on the drone. Therefore, the method in this embodiment effectively improves the adaptability of drone flight and the coordinated scheduling between individual drones in the cluster.

[0059] Exemplary Methods

[0060] This embodiment provides a method for monitoring and controlling a drone cluster area based on ant colony pheromones, and this embodiment can be applied to drone clusters. Figure 1 As shown, the method comprises the following steps:

[0061] Step S100, initializing a preset monitoring area as a grid unit, and setting the monitoring priority and initial attraction pheromone value of the grid unit; wherein the initial attraction pheromone value is the initial value of the attraction pheromone used to drive the drone to search the monitoring area;

[0062] The attraction pheromone value refers to a digital quantity that imitates the biological pheromone mechanism in the grid unit and has the ability to attract and repel the surrounding grid drones. The attraction pheromone can be inserted or removed from a local area, and evaporates or spreads to the neighboring area over time and decays. Through the attraction pheromone value, a distributed control strategy can be adopted to make the drone cluster more distributed and intelligent.

[0063] Specifically, the surveillance area is initialized as grid units to obtain a surveillance space model, so that an entire surveillance area can be subdivided into several grid units for fine control and precise positioning. The importance of different grid units is distinguished by setting the surveillance priority for each grid unit, and the initial attraction pheromone value is set to drive the drone to search the subdivided surveillance area.

[0064] In one implementation, step S100 in this embodiment includes the following steps:

[0065] S101. Divide the monitoring area into M×N grid units according to a preset monitoring accuracy, where M is the number of grid rows and N is the number of grid columns.

[0066] Specifically, assume that the monitoring area is a rectangular area with a length of L and a width of W. The rectangular monitoring area is divided into M×N areas with a side length of r s The grid cells, where r s That is the preset monitoring accuracy, expressed as p ij Represents the grid cell at row i and column j. During mission execution, the drone coordinates can be mapped to the grid cell to get the grid cell where the drone is located, as shown below:

[0067] i = ceil(x / r s ),0<i≤M,

[0068] j = ceil(y / r s ),0<j≤N,

[0069] Where (x, y) is the geographic coordinates of the drone, and ceil() is the upward rounding function.

[0070] For example, suppose that the drones numbered 1-5 are performing surveillance tasks, the surveillance area is 200m×200m, and the preset surveillance accuracy is the grid unit side length r s =10m, then the surveillance area can be divided into 20 rows and 20 columns of grid cells, each grid cell is 10m×10m in size. If the geographic coordinates of UAV 1 are (105,81), then UAV 1 will land in the grid cell p in the 10th row and 8th column of the grid. 10,8 middle.

[0071] S102: Set the monitoring priority for each grid unit.

[0072] Specifically, considering that the UAV needs to focus on monitoring a specific area, in order to distinguish the importance of different grid cells and to ij Define monitoring priority as λ ij , the grid cells that obtain higher monitoring priority will be monitored intensively, and the grid cells that obtain lower monitoring priority will be monitored less frequently.

[0073] For example, to set the monitoring priority of all grid cells in the monitoring area, Figure 2 As shown, it can be seen that the grid unit p 10,8 Set the monitoring priority to 1, for grid cell p 5,14 Set the monitoring priority to 2, then the grid cell p 10,8 will have a lower priority than grid cell p 5,14 , which means that the grid cell p 5,14 Compared to the grid cell p 10,8 Will be monitored more closely. Figure 3 The monitoring priority is Figure 2 The drone cluster track points shown here show that through the priority setting, drones will intensively monitor key areas.

[0074] S103: Setting the same initial attraction pheromone value for all the grid units.

[0075] Specifically, during initialization, the initial pheromone value of all grids is set to s0. In this way, in the absence of prior information, setting the same initial pheromone value can drive the drone to perform a random search of the surveillance area. ij ,t) represents the grid cell p at time t ij The pheromone strength in , i=1,...,M, j=1,...,N.

[0076] For example, if the initial pheromone value s(p ij ,0)=10, which means that at the initial moment, all grid cells p ij , i=1,...,M, j=1,...,N are all 10, and the drones in each grid unit pair release the same attraction pheromone.

[0077] Step S200, updating the initial attraction pheromone value according to the monitoring-out-of-monitoring time of the grid unit and the monitoring priority to obtain a real-time attraction pheromone value; wherein the monitoring-out-of-monitoring time is the time during which the grid unit is not visited by the drone.

[0078] Specifically, the out-of-monitoring duration indicates the length of time that a grid cell has not been visited by a drone. If the out-of-monitoring duration of a grid cell is too long, it means that the drone monitoring of the grid cell is insufficient and a drone needs to be dispatched to monitor it. If the priority of a grid cell is high, it means that the grid cell is important and will also affect the real-time pheromone value of the grid cell. The real-time pheromone value is obtained by updating the initial pheromone value based on the out-of-monitoring duration and the monitoring priority. The real-time pheromone value can then comprehensively reflect the out-of-monitoring duration of the grid cell at the current moment and the intensity of the released pheromones, so that the drone can be adaptively attracted to the grid cell.

[0079] In one implementation, step S200 in this embodiment includes the following steps:

[0080] S201, obtaining the pheromone switch of the grid unit according to the out-of-monitoring duration of the grid unit, wherein the pheromone switch is

[0081] Wherein, T0 represents the preset revisit time limit, t represents the time at which the grid unit is located, and t ij Represents the time when the grid cell was last visited by the drone.

[0082] Specifically, get the grid cell p ij The time of the last visit by a drone is t ij , i = 1, ..., M, j = 1, ..., N, by defining the pheromone switch

[0083] It can be seen that when the current time t of the grid cell is t away from the time t when the grid cell was last visited by the drone ij If the time difference is greater than or equal to the preset revisit time limit T0, it means that the grid unit has been out of surveillance for too long, then the pheromone switch will be turned on, and when the current time t of the grid unit is t from the time when the grid unit was last visited by the drone ij If the time difference is less than the preset revisit time limit T0, it means that the grid unit is out of monitoring for a short time, and the pheromone switch will be turned off.

[0084] For example, assuming that the revisit time limit T0 = 80s, grid cell p 3,6 The last time a drone visited the grid cell was 120 seconds ago. 3,6 The pheromone switch of the grid cell p is 1. 7,6 The last time a drone visited the grid cell was 20 seconds ago. 3,6 The pheromone switch is 0.

[0085] S202, updating the initial attraction pheromone value according to the pheromone switch of the grid unit and the monitoring priority to obtain the real-time attraction pheromone value, wherein the real-time attraction pheromone value is

[0086] s(p ij ,t)=(1-E)[(1-G)s(p ij ,t-1)+λ ij k ij d(p ij ,t)+g(p ij ,t)],

[0087] Among them, p ij is the grid unit of the i-th row and j-th column, i=1,...,M, j=1,...,N, E is the evaporation coefficient of the attraction pheromone value, G is the propagation coefficient of the attraction pheromone value, s(p ij ,t-1) is the grid unit p ij The pheromone value at time t-1, when t = 1, s(p ij ,0) is the grid unit p ij The initial attraction pheromone value, λ ij is the grid unit p ij The monitoring priority, k ij is the grid unit p ij The pheromone switch, d(p ij ,t) is the grid unit p ij Actively released attraction pheromone value,

[0088] g(p ij ,t) is the grid cell p ij All grid cells other than p are propagated to the grid cell p ij The attraction pheromone value of

[0089] Specifically, the method in this embodiment divides the grid into visited grid units and unvisited grid units. The release change of the unvisited grid unit is dominant, so that its real-time attraction pheromone value increases with time, so as to attract the drone to the unvisited grid unit. The evaporation change of the visited grid unit is dominant, so that its real-time attraction pheromone value decreases with time, reducing the degree of attraction to the drone. When the grid unit is visited within the revisit time limit through pheromone switch control, the attraction pheromone will not be actively released.

[0090] For example, assume that 5 drones are performing spectrum monitoring tasks. In the monitoring area described in the above example, the evaporation coefficient of the attraction pheromone value E = 0.65, the propagation coefficient of the attraction pheromone value G = 0.4, the revisit time limit T0 = 80s, and the monitoring priority is as follows: Figure 2 As shown, after calculation, the real-time attraction pheromone value distribution at time t is as follows Figure 4 As shown, it can be seen that the overall real-time attraction pheromone value is distributed between 5 and 15. The real-time attraction pheromone value of the grid unit in the area just passed by the drone is lower, while the real-time attraction pheromone value of the grid unit that has not been explored is higher. Therefore, in the next flight cycle, the drone will have a greater probability of going to the unmonitored area. Figure 5 This is the trajectory of the drone cluster flying for 100 seconds when all monitoring priorities are 1. It can be seen that drones generally tend to fly to areas that have not been monitored. After a grid cell has been visited for a period of time, the grid cell will release pheromones again, which makes it possible for drones to visit repeatedly to achieve regional monitoring.

[0091] Step S300: determining the resultant force on the drone according to the real-time attraction pheromone value and the distance vector between the drones.

[0092] Specifically, by calculating the distance between drones, the collision problem caused by the dense distribution of drones can be effectively avoided. The grid unit releases attractive pheromones to drones in real time to drive the drones to come for monitoring, and then the flight of the drone can be controlled by finally obtaining the combined force exerted on the drone.

[0093] In one implementation, step S300 in this embodiment includes the following steps:

[0094] S301, determining the resultant force of the potential field according to the real-time attraction pheromone value;

[0095] S302, determining the repulsive force between the drones according to the distance vector between the drones;

[0096] S303: Obtain the resultant force acting on the UAV according to the resultant force of the potential field and the repulsive force between the UAVs.

[0097] Specifically, the real-time attraction pheromone value is used to describe the unknown degree of the grid unit, and the distance vector between drones is used to describe the distribution density of drones. The potential field function is constructed inside the drone to obtain the resultant force acting on the drone to control the flight of the drone. On the one hand, the drone can actively jump out of the searched area, and on the other hand, collisions caused by close distances between drones can be avoided, so as to achieve better safety monitoring effects.

[0098] This embodiment defines the resultant force of the pheromone potential field as The repulsive force between drones is Then the net force on the drone is:

[0099] In one implementation, step S301 in this embodiment includes the following steps:

[0100] S3011, obtaining the first geographic coordinates of the first drone, and selecting a grid unit to be measured;

[0101] S3012, obtaining a first vector according to the first geographic coordinates and the center coordinates of the grid unit to be measured;

[0102] S3013, obtaining the pheromone potential field of the first drone according to the real-time attraction pheromone value of the grid unit to be tested and the first vector;

[0103] S3014. Obtain a resultant force of the pheromone potential field according to the pheromone potential field of the first UAV.

[0104] Specifically, the first drone n obtains the coordinates of the grid unit where it is currently located as the first geographic coordinates. A grid unit to be tested is selected, and the attraction to the drone is reflected according to the real-time attraction pheromone value of the grid unit to be tested. In this embodiment, the 10 grid units with the highest real-time attraction pheromone values ​​in the pheromone matrix are selected as the grid units to be tested, marked as A. i , i∈[1,10] as the source of the potential field, set the pheromone potential field coefficient to Q1, grid unit A i The real-time attraction pheromone value is s i , the coordinates of the first drone to grid cell A i The first vector of the center coordinates is Where i∈[1,10], n is the serial number of the first UAV. The pheromone potential field of the first UAV is obtained based on the real-time attraction pheromone value and the first vector. as follows:

[0105]

[0106] During the UAV cluster's surveillance mission, due to the grid unit A i The real-time attraction pheromone value is the highest, so grid unit A i They are all important grid units that need to be monitored. They will all have an attraction to the first drone, so the resultant force of the pheromone potential field on the first drone is calculated. as follows:

[0107]

[0108] In one implementation, step S302 in this embodiment includes the following steps:

[0109] S3021, acquiring a plurality of second drones in the monitoring area that have a positional relationship with the first drone;

[0110] S3022. Acquire the second geographic coordinates of the second UAV;

[0111] S3023. Obtain a second vector according to the first geographic coordinates and the second geographic coordinates;

[0112] S3024. Obtain the repulsive force between the drones according to the second vector.

[0113] Specifically, in this embodiment, all drones except the first drone n in the monitoring area are obtained as the second drone j, where j∈N / n, and N is all drones in the monitoring area. The second geographic coordinates of the second drone j are obtained according to the coordinates of the grid unit where the second drone j is located. The second vector is obtained according to the second geographic coordinates of the second drone j and the first geographic coordinates of the first drone n, and then the repulsive force between drones on the first drone n is obtained. As follows:

[0114]

[0115] Where Q2 is the coefficient of the inter-machine repulsive potential field, A second vector from the first geographic coordinate to the second geographic coordinate.

[0116] It can be seen from the formula of the repulsive force between drones that the closer the geographical coordinates between drones, the greater the repulsive force between drones, and the farther the geographical coordinates of drones, the smaller the repulsive force between drones. By calculating the distance vector between the first drone and other drones in the surveillance area, the repulsive force between drones acting on the first drone n can be obtained, thereby realizing the adaptive adjustment of the drone's track.

[0117] For example, Figure 6 This is the curve of the shortest distance between drones during the flight of the drone swarm. It can be seen that during the entire flight, the shortest distance between drones is almost always maintained outside the warning distance. When the distance is close to the warning distance, the repulsive force between drones for collision avoidance will play a dominant role, pulling the swarm to move to prevent collisions between drones.

[0118] Step S400: determining the flight speed of the UAV according to the resultant force acting on the UAV.

[0119] In one implementation, step S400 in this embodiment includes the following steps:

[0120] S401, set the maximum flight speed of the drone;

[0121] S402: Determine the flight speed of the UAV according to the maximum flight speed of the UAV and the resultant force acting on the UAV.

[0122] In this embodiment, the flight speed of the first UAV is defined as:

[0123]

[0124] Among them, v max The maximum speed of the drone.

[0125] In this embodiment, the first drone is controlled at a speed of Fly, and update the attraction pheromone value in real time by obtaining the current grid coordinates, broadcasting its own geographic coordinates, and updating the geographic coordinates of other drones, that is, repeatedly iteratively executing step S202, and then updating the resultant force of the potential field and the repulsive force between drones, and finally updating the resultant force on the drone in real time, and obtaining the updated flight speed of the drone to control the flight until the regional monitoring task is completed.

[0126] In this embodiment, in order to quantitatively compare the regional monitoring effects of this method and the traditional pheromone decision-making method, the grid cells in the monitoring area whose real-time attraction pheromone values ​​exceed the preset threshold are defined as unknown points, and 100 flight iterations are defined as a monitoring cycle. After each round of monitoring task is executed, the monitoring effect of the cluster can be evaluated by calculating the number of unknown points. The fewer unknown points, the better the coverage effect of the cluster. Figure 7 The change in the number of unknown points of the method of this embodiment and the traditional method over time is shown. It can be seen that with the increase of the iteration cycle, the number of unknown points of the method of this embodiment is less than that of the traditional method, and a better monitoring effect is achieved.

[0127] Exemplary Devices

[0128] Furthermore, the present invention also provides a drone cluster area monitoring and control device based on ant colony pheromones, and its principle block diagram is as follows: Figure 8 As shown, the device comprises:

[0129] Initialization module 10, used to initialize the preset monitoring area into a grid unit, and set the monitoring priority and initial attraction pheromone value of the grid unit;

[0130] A real-time attraction pheromone value acquisition module 20, used to update the initial attraction pheromone value according to the idle time of the grid unit and the monitoring priority to obtain a real-time attraction pheromone value;

[0131] A resultant force determination module 30, configured to determine the resultant force exerted on the drone according to the real-time attraction pheromone value and the distance vector between the drones;

[0132] The flight speed determination module 40 is used to determine the flight speed of the UAV according to the resultant force acting on the UAV.

[0133] In one implementation, the initialization module 10 in this embodiment includes:

[0134] A grid unit division unit, used to divide the monitoring area into M×N grid units according to a preset monitoring accuracy, where M is the number of grid rows and N is the number of grid columns;

[0135] A monitoring priority setting unit, used to set the monitoring priority for each grid unit respectively;

[0136] The initial attraction pheromone value setting unit is used to set the same initial attraction pheromone value for all the grid units.

[0137] In one implementation, the real-time attraction pheromone value acquisition module 20 in this embodiment includes:

[0138] A pheromone switch acquisition unit is used to obtain the pheromone switch of the grid unit according to the out-of-monitoring time of the grid unit, wherein the pheromone switch is

[0139] Wherein, T0 represents the preset revisit time limit, t represents the time at which the grid unit is located, and t ij represents the time when the grid cell was last visited by the drone;

[0140] A real-time attraction pheromone value acquisition unit is used to update the initial attraction pheromone value according to the pheromone switch of the grid unit and the monitoring priority to obtain the real-time attraction pheromone value.

[0141] s(p ij ,t)=(1-E)[(1-G)s(p ij ,t-1)+λ ij k ij d(p ij ,t)+g(p ij ,t)],

[0142] Among them, p ij is the grid unit of the i-th row and j-th column, i=1,...,M, j=1,...,N, E is the evaporation coefficient of the attraction pheromone value, G is the propagation coefficient of the attraction pheromone value, s(p ij ,t-1) is the grid unit p ij The pheromone value at time t-1, when t = 1, s(p ij ,0) is the grid unit p ijThe initial attraction pheromone value, λ ij is the grid unit p ij The monitoring priority, k ij is the grid unit p ij The pheromone switch, d(p ij ,t) is the grid unit p ij Actively released attraction pheromone value, g(p ij ,t) is the grid cell p ij All grid cells other than p are propagated to the grid cell p ij The attraction pheromone value.

[0143] In one implementation, the combined force determination module 30 in this embodiment includes:

[0144] A potential field force determination unit, used to determine the resultant force of the potential field according to the real-time attraction pheromone value;

[0145] an inter-drone repulsion force determination unit, configured to determine the inter-drone repulsion force according to the inter-drone distance vector;

[0146] The resultant force determination unit is used to obtain the resultant force acting on the UAV according to the resultant force of the potential field and the repulsive force between the UAVs.

[0147] In one implementation, the potential force determining unit in this embodiment includes:

[0148] A first geographic coordinate acquisition subunit is used to acquire the first geographic coordinates of the first drone and select a grid unit to be measured;

[0149] A first vector acquisition subunit, configured to obtain a first vector according to the first geographic coordinates and the center coordinates of the grid unit to be measured;

[0150] a pheromone potential field acquisition subunit, configured to obtain the pheromone potential field of the first UAV according to the real-time attraction pheromone value of the grid unit to be measured and the first vector;

[0151] The potential field force acquisition subunit is used to obtain the resultant force of the pheromone potential field according to the pheromone potential field of the first UAV.

[0152] In one implementation, the inter-drone repulsion force determination unit in this embodiment includes:

[0153] A second drone acquisition subunit, configured to acquire a plurality of second drones in the surveillance area that have a positional relationship with the first drone;

[0154] A second geographic coordinate acquisition subunit, configured to acquire second geographic coordinates of the second UAV;

[0155] A second vector acquisition subunit, configured to obtain a second vector according to the first geographic coordinates and the second geographic coordinates;

[0156] The repulsive force acquisition subunit between drones is used to obtain the repulsive force between drones according to the second vector.

[0157] In one implementation, the flight speed determination module 40 in this embodiment includes:

[0158] Maximum flight speed setting unit, used to set the maximum flight speed of the drone;

[0159] The flight speed acquisition unit is used to determine the flight speed of the drone according to the maximum flight speed of the drone and the resultant force acting on the drone.

[0160] Based on the above embodiments, the present invention also provides a drone, wherein the drone includes a memory, a processor, and a drone cluster area monitoring and control program based on ant colony pheromones stored in the memory and executable on the processor, and when the processor executes the drone cluster area monitoring and control program based on ant colony pheromones, the steps of the drone cluster area monitoring and control method based on ant colony pheromones as described in any one of the above items are implemented.

[0161] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, operating database or other media used in the embodiments provided by the present invention may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double operational data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0162] In summary, the present invention discloses a method for monitoring and controlling a cluster area of ​​a drone based on ant colony pheromones, the method comprising: initializing a preset monitoring area as a grid unit, and setting the monitoring priority and initial attraction pheromone value of the grid unit; updating the initial attraction pheromone value according to the monitoring separation time of the grid unit and the monitoring priority to obtain a real-time attraction pheromone value; determining the resultant force exerted on the drone according to the real-time attraction pheromone value and the distance vector between the drones; and determining the flight speed of the drone according to the resultant force exerted on the drone. The present invention uses pheromones to quantify the monitoring status of the monitoring area to guide the drone to search for unknown areas, guides the drone to focus on monitoring important areas through monitoring priorities, and establishes a pheromone potential field between individual drones in the cluster to achieve adaptive trajectory planning of the drone.

[0163] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring and controlling a drone cluster area based on ant colony pheromones, characterized in that: The method comprises: Initializing a preset monitoring area as a grid unit, and setting the monitoring priority and initial attraction pheromone value of the grid unit; wherein the initial attraction pheromone value is an initial value of the attraction pheromone used to drive the drone to search the monitoring area; The initial attraction pheromone value is updated according to the monitoring time of the grid unit and the monitoring priority to obtain a real-time attraction pheromone value; wherein the monitoring time is the time during which the grid unit is not visited by the drone; Determine the resultant force on the drone according to the real-time attraction pheromone value and the distance vector between the drones; Determining a flight speed of the UAV according to the resultant force acting on the UAV; The updating of the initial attraction pheromone value according to the monitoring time of the grid unit and the monitoring priority to obtain the real-time attraction pheromone value includes: The pheromone switch of the grid unit is obtained according to the out-of-monitoring time of the grid unit, wherein the pheromone switch is ,in, T 0 represents the preset revisit time limit, represents the time at which the grid cell is located, represents the time when the grid cell was last visited by the drone; The initial attraction pheromone value is updated according to the pheromone switch of the grid unit and the monitoring priority to obtain the real-time attraction pheromone value, wherein the real-time attraction pheromone value is in, is the grid cell at the i-th row and j-th column, , , To attract the pheromone value evaporation coefficient, To attract pheromone value propagation coefficient, For the grid unit exist t-1 The attraction pheromone value at the moment, when t=1 hour, That is, the grid unit The initial attraction pheromone value of For the grid unit The monitoring priority of For the grid unit The pheromone switch, For the grid unit Actively released attraction pheromone value, To remove the grid cells All grid cells outside the The attraction pheromone value.

2. The method for monitoring and controlling a drone cluster area based on ant colony pheromones according to claim 1 is characterized in that: The step of initializing the preset monitoring area as a grid unit and setting the monitoring priority and initial attracting pheromone value of the grid unit includes: According to the preset monitoring accuracy, the monitoring area is divided into said grid cells, wherein M is the number of grid rows, N is the number of grid columns; Setting the monitoring priority for each grid unit respectively; The same initial attraction pheromone value is set for all the grid cells.

3. The method for monitoring and controlling a drone cluster area based on ant colony pheromones according to claim 1 is characterized in that: The determining the resultant force exerted on the drone according to the real-time attraction pheromone value and the distance vector between the drones includes: determining a resultant force of the potential field according to the real-time attraction pheromone value; Determine the repulsive force between the drones according to the distance vector between the drones; The resultant force acting on the UAV is obtained according to the resultant force of the potential field and the repulsive force between the UAVs.

4. The method for monitoring and controlling a drone cluster area based on ant colony pheromones according to claim 3 is characterized in that: Determining the resultant force of the potential field according to the real-time attraction pheromone value includes: Obtaining a first geographic coordinate of a first drone, and selecting a grid unit to be measured; Obtaining a first vector according to the first geographic coordinates and the center coordinates of the grid unit to be measured; Obtaining the pheromone potential field of the first UAV according to the real-time attraction pheromone value of the grid unit to be tested and the first vector; The resultant force of the pheromone potential field is obtained according to the pheromone potential field of the first UAV.

5. The method for monitoring and controlling a drone cluster area based on ant colony pheromones according to claim 4 is characterized in that: The determining the repulsive force between the drones according to the distance vector between the drones includes: Acquire a plurality of second drones in the monitoring area that have a positional relationship with the first drone; Obtaining second geographic coordinates of the second drone; Obtain a second vector according to the first geographic coordinates and the second geographic coordinates; The repulsive force between the drones is obtained according to the second vector.

6. The method for monitoring and controlling a drone cluster area based on ant colony pheromones according to claim 1 is characterized in that: Determining the flight speed of the drone according to the resultant force applied to the drone includes: Set the maximum flight speed of the drone; The flight speed of the UAV is determined according to the maximum flight speed of the UAV and the resultant force acting on the UAV.

7. A drone cluster area monitoring and control device based on ant colony pheromones, characterized in that: The device comprises: An initialization module, used to initialize the preset monitoring area into a grid unit, and set the monitoring priority and initial attraction pheromone value of the grid unit; A real-time attraction pheromone value acquisition module, used to update the initial attraction pheromone value according to the idle time of the grid unit and the monitoring priority to obtain a real-time attraction pheromone value; A resultant force determination module, used to determine the resultant force exerted on the drone according to the real-time attraction pheromone value and the distance vector between the drones; A flight speed determination module, used to determine the flight speed of the UAV according to the resultant force applied to the UAV; The real-time attraction pheromone value acquisition module includes: A pheromone switch acquisition unit is used to obtain the pheromone switch of the grid unit according to the time period during which the grid unit is out of monitoring, wherein the pheromone switch is ,in, T 0 represents the preset revisit time limit, represents the time at which the grid cell is located, represents the time when the grid cell was last visited by the drone; A real-time attraction pheromone value acquisition unit is used to update the initial attraction pheromone value according to the pheromone switch of the grid unit and the monitoring priority to obtain the real-time attraction pheromone value. in, is the grid cell at the i-th row and j-th column, , , To attract the pheromone value evaporation coefficient, To attract pheromone value propagation coefficient, For the grid unit exist t-1 The attraction pheromone value at the moment, when t=1 hour, That is, the grid unit The initial attraction pheromone value of For the grid unit The monitoring priority of For the grid unit The pheromone switch, For the grid unit Actively released attraction pheromone value, To remove the grid cells All grid cells outside the The attraction pheromone value.

8. A drone, characterized in that: The drone includes a memory, a processor, and a drone cluster area monitoring and control program based on ant colony pheromones stored in the memory and executable on the processor. When the processor executes the drone cluster area monitoring and control program based on ant colony pheromones, the steps of the drone cluster area monitoring and control method based on ant colony pheromones as described in any one of claims 1 to 6 are implemented.

9. A storage medium, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of the drone cluster area monitoring and control method based on ant colony pheromones as described in any one of claims 1 to 6 above.

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