Heterogeneous unmanned swarm collaborative search method based on emergence

Abstract

The present invention discloses a heterogeneous unmanned cluster collaborative search method based on emergence, including: dividing a task area into multiple grid units; constructing the target existence probability of the grid unit and its update mechanism; constructing the digital pheromone of all grid units corresponding to the heterogeneous unmanned cluster and its update mechanism; setting the interaction rules between the cluster monomer and its neighboring same cluster monomers; setting the interaction rules between the cluster monomer and the environment; setting the interaction rules between the cluster monomer and the heterogeneous unmanned cluster; according to the interaction between the cluster monomer and its neighboring same cluster monomer, the interaction between the cluster monomer and the environment, and the interaction between the cluster monomer and the heterogeneous unmanned cluster, the movement direction and speed of the cluster monomer are calculated, and the cluster monomer is controlled to perform mobile search. The present invention can realize complementary collaborative search of heterogeneous unmanned clusters, realize efficient full coverage search of the task area, and improve the efficiency of collaborative target search of heterogeneous unmanned clusters.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned cluster control, and in particular to an emergence-based heterogeneous unmanned cluster collaborative search method. Background Art

[0002] Since the collaborative search of targets in a specific mission area by unmanned swarms is of great significance and value in both theory and engineering practice, studying the collaborative search mechanism of unmanned swarms plays an important role in improving the efficiency and effectiveness of the collaborative search of unmanned swarms.

[0003] Unmanned swarm usually refers to a swarm system composed of unmanned intelligent units such as drones, unmanned vehicles, unmanned ships, unmanned submarines or robots. When the unmanned swarm conducts a collaborative search of the mission area, it usually divides the mission area into grids according to the motion parameters of the unmanned swarm units; then, a unit is assigned to each grid to perform the task, or the units are compared to particles or gene fragments, based on heuristic algorithm mechanisms such as particle swarms or genetic algorithms, to achieve collaborative search of the mission area by unmanned swarms, or the collaborative search method of unmanned swarms based on local rule emergence is used to achieve collaborative search of the mission area by drone swarms.

[0004] However, in the traditional search method based on regional grid segmentation and assigning cluster monomers to search a single grid unit separately, there is no coordination or poor coordination between cluster monomers, and the corresponding search efficiency is not high. Unmanned cluster collaborative search methods based on heuristic algorithms such as particle swarm need to use environmental and target information to continuously optimize and iterate to seek the optimal search track, which has poor timeliness and is only applicable to search tasks that can be pre-planned. It is difficult to achieve fast online track generation. Moreover, the collaborative search method based on heuristic algorithms such as particle swarm increases with the increase in the number of collaborative monomers, and it is easy to lose the possibility of practical execution due to the sharp increase in computational volume. The unmanned cluster collaborative search method based on local rule emergence achieves full regional coverage by setting local rules between cluster monomers and local rules between monomers and the environment. It has limited search capabilities for task areas with high and dense obstacles, and there is no mechanism for targeted search of randomly distributed targets. It cannot cope with the search of complex task areas and target discovery. In addition, the existing unmanned cluster collaborative search method based on local rule emergence only performs collaborative search for a single unmanned cluster, which has certain limitations. Summary of the invention

[0005] In order to solve some or all of the technical problems existing in the above-mentioned prior art, the present invention provides a heterogeneous unmanned cluster collaborative search method based on emergence.

[0006] The technical solution of the present invention is as follows:

[0007] A heterogeneous unmanned cluster collaborative search method based on emergence is provided, including:

[0008] Divide the task area into a plurality of grid units, wherein the area of ​​the grid unit is larger than the target size and smaller than or equal to the search area of ​​a single cluster monomer;

[0009] Based on the probability density function and the sensor detection information of the cluster monomer, the target existence probability of the grid unit and the target existence probability update mechanism are constructed;

[0010] Based on the familiarity of the heterogeneous unmanned clusters with the grid cells, digital pheromones and digital pheromone update mechanisms of all grid cells corresponding to the heterogeneous unmanned clusters are constructed respectively;

[0011] According to the motion parameters of the cluster monomers, the interaction rules between the cluster monomers and their neighboring monomers of the same cluster are set;

[0012] According to the target existence probability of the grid unit, the interaction rules between the cluster monomers and the environment are set;

[0013] According to the digital pheromones corresponding to the heterogeneous unmanned clusters, the interaction rules between the cluster monomers and the heterogeneous unmanned clusters are set;

[0014] Determine the interaction between the cluster monomer at the current moment and its neighboring monomers of the same cluster according to the interaction rules between the cluster monomer and its neighboring monomers of the same cluster; determine the interaction between the cluster monomer and the environment at the current moment according to the interaction rules between the cluster monomer and the environment; determine the interaction between the cluster monomer and the heterogeneous unmanned cluster at the current moment according to the interaction rules between the cluster monomer and the heterogeneous unmanned cluster;

[0015] According to the interaction between the cluster monomer at the current moment and its adjacent monomers of the same cluster, the interaction between the cluster monomer and the environment, and the interaction between the cluster monomer and the heterogeneous unmanned cluster, the movement direction and speed of the cluster monomer at the next moment are calculated, and the cluster monomer is controlled to perform mobile search according to the obtained movement direction and speed.

[0016] In some possible implementations, the initial target existence probability of a grid cell is:

[0017]

[0018] Among them, P represents the initial target existence probability corresponding to the grid cell, f(·) represents the target existence probability density function of the mixed two-dimensional Gaussian probability density function corresponding to the target, s represents the integral differential area corresponding to f(·), and D represents the integral area corresponding to the grid cell.

[0019] In some possible implementations, the target existence probability update mechanism of the grid unit includes:

[0020] If the cluster monomer detects the target in the grid cell at time t, the target existence probability of the grid cell is updated using the following formula to obtain the target existence probability of the grid cell at the next moment;

[0021]

[0022] If the cluster monomer does not detect the target in the grid cell at time t, the target existence probability of the grid cell is updated using the following formula to obtain the target existence probability of the grid cell at the next moment;

[0023]

[0024] Among them, P(t+1) represents the probability of the target existing in the grid cell at time t+1, P d represents the sensor detection probability of the cluster monomer, P(t) represents the target existence probability of the grid unit at time t, and P f Indicates the false alarm rate.

[0025] In some possible implementations, the digital pheromone of the ijth grid cell corresponding to a certain unmanned cluster at time t is set to s a (L ij , t);

[0026] The digital pheromone update mechanism includes:

[0027] The digital pheromone of the ijth grid cell corresponding to a certain unmanned cluster at time t is calculated and updated using the following formula:

[0028] s a (L ij , t) = (1-E a )[(1-G a )(s a (L ij , t-1)+via ij，t ·d a (L ij ,t))+g a (L ij , t)]

[0029] Among them, E a represents the pheromone propagation coefficient, G a represents the pheromone evaporation coefficient, s a (L ij , t-1) represents the digital pheromone of the ijth grid cell corresponding to the current unmanned cluster at time t-1, via ij，trepresents the number of times the cluster monomer of the current unmanned cluster passes through the ijth grid unit at time t, d a (L ij , t) represents the amount of digital pheromone released when the cluster monomer of the current unmanned cluster passes through the ijth grid unit at time t, g a (L ij , t) represents the amount of digital pheromone that penetrates into the ijth grid cell from the adjacent grid cell from time t-1 to time t.

[0030] In some possible implementations, the interaction rule between the cluster monomer and its adjacent monomers of the same cluster is set as:

[0031] When the distance x between cluster monomers satisfies 0≤x≤L, the interaction between cluster monomers is repulsive, and the repulsive force increases as the distance decreases;

[0032] When the distance x between cluster monomers satisfies L<x≤2L, the interaction between cluster monomers is gravitational force, and the gravitational force increases with the increase of the distance;

[0033] When the distance x between cluster monomers satisfies 2L<x≤3L, the interaction between cluster monomers is gravitational force, and the gravitational force decreases as the distance increases;

[0034] When the spacing x between cluster monomers satisfies x>3L, the interaction between cluster monomers is zero;

[0035] The direction of gravity is the direction from the cluster monomer to its neighboring cluster monomer, the direction of repulsion is opposite to the direction of gravity, and L represents the safe movement distance between cluster monomers.

[0036] In some possible implementations, the value of the interaction between a cluster monomer and its neighboring monomers of the same cluster is determined using the following formula:

[0037]

[0038] Among them, |F| represents the value of interaction, α1 represents the maximum value of the force, and β represents the proportional coefficient of the degree of change of the force with the distance between cluster monomers.

[0039] In some possible implementations, the interaction rules between the cluster monomers and the environment are set as follows:

[0040] The interaction between a cluster monomer and the environment is a vector pointing from a cluster monomer to the center of the grid cell with the highest probability of target existence among its neighboring grid cells.

[0041] In some possible implementations, the interaction rules between the cluster monomer and the heterogeneous unmanned cluster are set as follows:

[0042] The interaction between a cluster monomer and the unmanned cluster to which it belongs is the vector of the cluster monomer pointing to the center of the grid unit corresponding to the smallest digital pheromone among the digital pheromones corresponding to the unmanned cluster to which it belongs;

[0043] The interaction between a cluster monomer and an unmanned cluster that it does not belong to is the vector from the center of the grid unit corresponding to the largest digital pheromone among the digital pheromones corresponding to the current unmanned cluster that it does not belong to to the cluster monomer;

[0044] The interaction between a cluster monomer and a heterogeneous unmanned cluster is the sum of the interaction between a cluster monomer and the unmanned cluster to which it belongs and the interaction between a cluster monomer and the unmanned cluster to which it does not belong.

[0045] In some possible implementations, the movement direction and movement speed of the cluster monomer at the next moment are calculated using the following formula:

[0046]

[0047] in, represents the velocity vector of the cluster monomer, represents the interaction between a cluster monomer and its first neighboring monomer of the same cluster, represents the interaction between a cluster monomer and its second neighboring monomer of the same cluster, represents the interaction between a cluster monomer and its g-th neighboring monomer of the same cluster, Represents the interaction between the cluster monomer and the heterogeneous unmanned cluster, and the interaction between the cluster monomer and the environment. represents the interaction between the cluster monomers and the environment, α 11 express The corresponding weight parameter, α 12 express The corresponding weight parameter, α 1g express The corresponding weight parameter, α2 represents the corresponding The weight parameter, α3 corresponds to The weight parameter of .

[0048] In some possible implementations, the method further includes:

[0049] Determine whether the environmental uncertainty is less than a preset uncertainty threshold;

[0050] If not, the target existence probability and digital pheromone of the grid unit are updated according to the target existence probability update mechanism and the digital pheromone update mechanism, the interaction is calculated and updated according to the set interaction rules, the movement direction and movement speed of the cluster monomer at the next moment are calculated based on the updated interaction, and the cluster monomer is controlled to continue the mobile search;

[0051] If so, the collaborative search of the unmanned cluster ends.

[0052] The main advantages of the technical solution of the present invention are as follows:

[0053] The emergence-based heterogeneous unmanned cluster collaborative search method of the present invention can be used for collaborative search of more than two heterogeneous unmanned clusters. By designing the target existence probability and the target existence probability update mechanism, digital pheromones and the digital pheromone update mechanism for the divided grid units, and designing the interaction rules between monomers in the unmanned cluster, the interaction rules between cluster monomers and the environment, and the interaction rules between heterogeneous unmanned clusters, the motion trajectory of the monomers in each unmanned cluster can be planned and generated in real time. It can realize complementary collaborative search of heterogeneous unmanned clusters, realize efficient full coverage search of designated task areas, and targeted search of randomly distributed targets, and can reduce the number of repeated searches of invalid grid cells in the task area, significantly improving the efficiency of collaborative target search of heterogeneous unmanned clusters. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] 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 of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1 A flowchart of a heterogeneous unmanned cluster collaborative search method based on emergence according to an embodiment of the present invention;

[0056] Figure 2 A schematic diagram of a grid layout of a task area according to an embodiment of the present invention;

[0057] Figure 3 The present invention is a flowchart of another emergence-based heterogeneous unmanned cluster collaborative search method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0059] The technical solution provided by the embodiments of the present invention is described in detail below with reference to the accompanying drawings.

[0060] See also Figure 1 An embodiment of the present invention provides a heterogeneous unmanned cluster collaborative search method based on emergence, the method comprising the following steps:

[0061] Step S1, dividing the task area into a plurality of grid units, wherein the area of ​​the grid unit is larger than the target size and smaller than or equal to the search area of ​​a single cluster monomer;

[0062] Step S2, constructing the target existence probability of the grid unit and the target existence probability update mechanism based on the probability density function and the sensor detection information of the cluster monomer;

[0063] Step S3, based on the familiarity of the heterogeneous unmanned clusters with the grid cells, respectively construct digital pheromones and digital pheromone update mechanisms for all grid cells corresponding to the heterogeneous unmanned clusters;

[0064] Step S4, setting the interaction rules between the cluster monomer and its neighboring monomers of the same cluster according to the motion parameters of the cluster monomer;

[0065] Step S5, setting the interaction rules between the cluster monomers and the environment according to the target existence probability of the grid cells;

[0066] Step S6, setting the interaction rules between the cluster monomers and the heterogeneous unmanned clusters according to the digital pheromones corresponding to the heterogeneous unmanned clusters;

[0067] Step S7, determining the interaction between the cluster monomer at the current moment and its neighboring monomers of the same cluster according to the interaction rules between the cluster monomer and its neighboring monomers of the same cluster, determining the interaction between the cluster monomer and the environment at the current moment according to the interaction rules between the cluster monomer and the environment, and determining the interaction between the cluster monomer and the heterogeneous unmanned cluster at the current moment according to the interaction rules between the cluster monomer and the heterogeneous unmanned cluster;

[0068] Step S8, based on the interaction between the cluster monomer at the current moment and its adjacent cluster monomers of the same cluster, the interaction between the cluster monomer and the environment, and the interaction between the cluster monomer and the heterogeneous unmanned cluster, calculate the movement direction and movement speed of the cluster monomer at the next moment, and control the cluster monomer to perform mobile search based on the obtained movement direction and movement speed.

[0069] The emergence-based heterogeneous unmanned cluster collaborative search method provided in one embodiment of the present invention can be used for collaborative search of more than two heterogeneous unmanned clusters. By designing the target existence probability and the target existence probability update mechanism, digital pheromones and the digital pheromone update mechanism for the divided grid units, and designing the interaction rules between monomers in the unmanned cluster, the interaction rules between cluster monomers and the environment, and the interaction rules between heterogeneous unmanned clusters, the motion trajectory of the monomers in each unmanned cluster can be planned and generated in real time. This can realize complementary collaborative search of heterogeneous unmanned clusters, efficient full coverage search of designated task areas, and targeted search of randomly distributed targets. It can reduce the number of repeated searches of invalid grid cells in the task area, and significantly improve the efficiency of collaborative target search of heterogeneous unmanned clusters.

[0070] The following specifically describes the steps and principles of the emergence-based heterogeneous unmanned cluster collaborative search method provided by an embodiment of the present invention:

[0071] Step S1, dividing the task area into a plurality of grid units.

[0072] In one embodiment of the present invention, the task area is rasterized according to the specific structural size of the task area to divide the task area into multiple grid units; at the same time, when performing grid division, the area of ​​each grid unit obtained is controlled to be larger than the target size and less than or equal to the search area of ​​a single cluster monomer, ensuring that the target can exist completely in a grid cell and that a single cluster monomer is capable of completely searching a single grid cell.

[0073] See also Figure 2 For example, when the task area is a rectangular area, the task area can be divided into M×N grid cells A={(i, j)|1≤i≤M, 1≤j≤N}. At the same time, the grid cells can be sorted from left to right and from bottom to top, and the grid cell (i, j) represents the ijth grid cell, that is, the grid cell in the i-th row and j-th column. Figure 2 In the figure, the black area indicates that there is a target in the grid cell.

[0074] Step S2, based on the probability density function and the sensor detection information of the cluster monomers, construct the target existence probability of the grid unit and the target existence probability update mechanism.

[0075] In one embodiment of the present invention, a mixed two-dimensional Gaussian probability density function is used to describe the target distribution in the task area. The mixed two-dimensional Gaussian probability density function used to describe the target distribution is specifically expressed as:

[0076]

[0077] Among them, μ1 and μ2 represent the mean of a certain prior target point distribution in the set x direction and y direction, σ1 and σ2 represent the standard deviation of the target distribution in the x direction and y direction, and ρ represents the covariance, ρ = cov(x, y). Among them, the x direction and y direction of the task area can be set in advance.

[0078] When the mission area contains K targets, the target existence probability density function of the mission area is:

[0079]

[0080] Among them, f k (x, y) represents the mixed two-dimensional Gaussian probability density function corresponding to the kth target, α k represents the weight corresponding to the kth target, α k The specific value can be set according to the importance of different goals.

[0081] Based on the above settings, the initial target existence probability corresponding to the grid cell is expressed as:

[0082]

[0083] Among them, P represents the initial target existence probability corresponding to the grid cell, f(·) represents the mixed two-dimensional Gaussian probability density function corresponding to the target, s represents the integral differential area corresponding to f(·), and D represents the integral area corresponding to the grid cell, which is the area contained in the grid cell.

[0084] Specifically, taking the ijth grid cell (i, j) as an example, the corresponding initial target existence probability can be expressed as:

[0085]

[0086] Among them, P ij represents the initial target existence probability corresponding to the ijth grid cell (i, j), and Dij represents the integral area corresponding to the grid cell (i, j).

[0087] Furthermore, in one embodiment of the present invention, the target existence probability update mechanism of the grid unit includes:

[0088] If the cluster monomer detects the target in the grid cell at time t, the target existence probability of the grid cell is updated using the following formula to obtain the target existence probability of the grid cell at the next moment;

[0089]

[0090] If the cluster monomer does not detect the target in the grid cell at time t, the target existence probability of the grid cell is updated using the following formula to obtain the target existence probability of the grid cell at the next moment;

[0091]

[0092] Among them, P(t+1) represents the probability of the target existing in the grid cell at time t+1, P d represents the sensor detection probability of the cluster monomer, P(t) represents the target existence probability of the grid unit at time t, and P f Indicates the false alarm rate.

[0093] The sensor detection probability of a cluster unit is the probability that a target exists in the grid unit and is detected by the sensor of the cluster unit. Its value is between [0, 1]. The specific value is determined according to the actual performance of the sensor of the cluster unit. The false alarm rate is the probability that a target does not exist in the grid unit but is detected by the sensor of the cluster unit. Its value is between [0, 1]. The specific value is also determined according to the actual performance of the sensor of the cluster unit.

[0094] In one embodiment of the present invention, the larger the value of the target existence probability of the grid cell, the greater the possibility that the target exists in the grid cell. For this purpose, a threshold θ can be set. When the target existence probability of the grid cell is greater than the set threshold θ, it is considered that the target exists in the grid cell.

[0095] Step S3, based on the familiarity of the heterogeneous unmanned clusters with the grid cells, digital pheromones and digital pheromone update mechanisms are constructed for all grid cells corresponding to the heterogeneous unmanned clusters.

[0096] In nature, when ants forage for food, they leave a substance on the path they pass to attract other ants to come for food. This substance increases with the number of times and the number of ants, and also evaporates over time. This substance is called pheromone. In one embodiment of the present invention, digital pheromones are designed to attract and repel heterogeneous unmanned swarms, based on the principle that ants use pheromones to guide ants to forage, thereby guiding heterogeneous unmanned swarms to conduct low-repetition collaborative searches in the task area.

[0097] In one embodiment of the present invention, a scalar defined in a grid unit that has the physical characteristics of propagation and volatilization of biological pheromones and has the ability to attract and repel cluster monomers of adjacent grid units is a digital pheromone. The digital pheromone has three change processes, including release, evaporation, and propagation, wherein the release process indicates that the digital pheromone can be quantitatively released into the grid unit; the evaporation process indicates that the digital pheromone will evaporate to the minimum value over time; and the propagation process indicates that the digital pheromone will be transmitted to adjacent grid units.

[0098] Further, based on the above settings, in one embodiment of the present invention, taking two heterogeneous unmanned clusters including an aerial unmanned cluster composed of multiple drones and a ground unmanned cluster composed of multiple unmanned vehicles as an example, how to construct the digital pheromones of the grid units corresponding to the unmanned clusters and the digital pheromone update mechanism are specifically described.

[0099] Setting: AP and BP represent the digital pheromones corresponding to the aerial unmanned cluster and the ground unmanned cluster, respectively. a (L ij , t) and s b (L ij , t) represent the digital pheromone of the ijth grid unit corresponding to the aerial unmanned cluster at time t and the digital pheromone of the ijth grid unit corresponding to the ground unmanned cluster at time t. Based on the above-divided grid units, AP and BP can be expressed as:

[0100]

[0101]

[0102] In one embodiment of the present invention, the digital pheromone corresponding to the unmanned cluster at the initial moment can be set according to actual needs. For example, it can be set to 0.

[0103] Furthermore, since digital pheromones have the characteristics of spreading and volatilization, the updating of digital pheromones can be carried out according to the principle of spreading first and then evaporating.

[0104] Based on the above settings, in one embodiment of the present invention, taking the above-mentioned unmanned aerial swarm as an example, its digital pheromone update mechanism includes:

[0105] The digital pheromone of the ijth grid cell corresponding to the unmanned cluster at time t is calculated and updated using the following formula:

[0106] s a (L ij , t) = (1-E a )[(1-G a )(s a (L ij , t-1)+viaij，t ·d a (L ij ,t))+g a (L ij , t)]

[0107] Among them, E a represents the pheromone propagation coefficient corresponding to the aerial unmanned cluster, G a represents the pheromone evaporation coefficient corresponding to the unmanned aerial cluster, s a (L ij , t-1) represents the digital pheromone of the ijth grid unit corresponding to the aerial unmanned cluster at time t-1, via ij，t represents the number of times the unmanned aerial cluster passes through the ijth grid unit at time t, d a (L ij , t) represents the amount of digital pheromone released when the cluster monomer of the unmanned cluster in the air passes through the ijth grid unit at time t, g a (L ij , t) represents the amount of digital pheromone transmitted from the adjacent grid cell to the ijth grid cell from time t-1 to time t corresponding to the aerial unmanned cluster.

[0108] The amount of digital pheromone g transmitted from the adjacent grid cell to the ijth grid cell from time t-1 to time t a (L ij , t) can be calculated using the following formula:

[0109]

[0110] Among them, L xy ∈U represents the neighboring grid cells of the ijth grid cell, LIN N(p) represents the total number of neighboring grid cells of the ijth grid cell, s a (L xy , t-1) represents the digital pheromone of the neighboring grid cells of the ijth grid cell corresponding to the aerial unmanned cluster at time t-1, d a (L xy , t) represents the amount of digital pheromone released when the cluster monomer of the unmanned aerial cluster passes through the adjacent grid cell of the ijth grid cell at time t.

[0111] In one embodiment of the present invention, the pheromone propagation coefficient, pheromone evaporation coefficient, and the amount of digital pheromone released when the cluster monomer passes through the grid unit corresponding to the unmanned aerial cluster can be set according to actual conditions.

[0112] Furthermore, for the above-mentioned ground unmanned cluster, its digital pheromone update mechanism includes:

[0113] The digital pheromone of the ijth grid cell corresponding to the unmanned cluster at time t is calculated and updated using the following formula:

[0114] s b (L ij , t) = (1-E b )[(1-G b )(s b (L ij ,t-1)+vib ij，t ·d b (L ij ,t))+g b (L ij , t)]

[0115] Among them, E b represents the pheromone propagation coefficient corresponding to the ground unmanned cluster, G b represents the pheromone evaporation coefficient corresponding to the unmanned ground cluster, s b (L ij ,t-1) represents the digital pheromone of the ijth grid unit corresponding to the unmanned ground cluster at time t-1, vib ij，t represents the number of times the ground unmanned cluster monomer passes through the ijth grid unit at time t, d b (L ij , t) represents the amount of digital pheromone released when the cluster monomer of the ground unmanned cluster passes through the ijth grid unit at time t, g b (L ij , t) represents the amount of digital pheromone transmitted from the adjacent grid cell to the ijth grid cell from time t-1 to time t corresponding to the ground unmanned cluster.

[0116] The amount of digital pheromone g transmitted from the adjacent grid cell to the ijth grid cell from time t-1 to time t b (L ij , t) can be calculated using the following formula:

[0117]

[0118] Among them, L xy ∈U represents the neighboring grid cells of the ijth grid cell, LIN N(p) represents the total number of neighboring grid cells of the ijth grid cell, s b (L xy， t=1) represents the digital pheromone of the neighboring grid cells of the ijth grid cell corresponding to the unmanned ground cluster at time t-1, d b (L xy , t) represents the amount of digital pheromone released when the cluster monomer of the ground unmanned cluster passes through the adjacent grid cell of the ijth grid cell at time t.

[0119] In one embodiment of the present invention, the pheromone propagation coefficient, pheromone evaporation coefficient, and the amount of digital pheromone released when the cluster monomer passes through the grid unit corresponding to the ground unmanned cluster can be set according to actual conditions.

[0120] In one embodiment of the present invention, in order to facilitate determining the number of visits to each grid unit by different unmanned clusters at different times, a grid state matrix can be set for each unmanned cluster to record the number of times the grid unit is visited by the unmanned cluster. Specifically, taking an aerial unmanned cluster as an example, its corresponding grid state matrix at time t can be expressed as:

[0121]

[0122] Among them, via MN，t It indicates the number of times the cluster monomers of the unmanned aerial cluster pass through the MNth grid unit at time t.

[0123] Step S4, setting the interaction rules between the cluster monomer and its adjacent cluster monomers according to the motion parameters of the cluster monomer.

[0124] In one embodiment of the present invention, by designing the interaction between cluster monomers and their adjacent cluster monomers of the same type, cluster monomers belonging to the same unmanned cluster are attracted and repelled, which can better guide the unmanned cluster to conduct efficient, low-repetition collaborative search of the mission area while avoiding collisions between cluster monomers.

[0125] Specifically, in one embodiment of the present invention, the interaction rule between a cluster monomer and its adjacent same cluster monomer is set as:

[0126] When the distance x between cluster monomers satisfies 0≤x≤L, the interaction between cluster monomers is repulsive, and the repulsive force increases as the distance decreases;

[0127] When the distance x between cluster monomers satisfies L<x≤2L, the interaction between cluster monomers is gravitational force, and the gravitational force increases with the increase of the distance;

[0128] When the distance x between cluster monomers satisfies 2L<x≤3L, the interaction between cluster monomers is gravitational force, and the gravitational force decreases as the distance increases;

[0129] When the spacing x between cluster monomers satisfies x>3L, the interaction between cluster monomers is zero;

[0130] The direction of gravity is the direction from the cluster monomer to its neighboring cluster monomer, the direction of repulsion is opposite to the direction of gravity, and L represents the safe movement distance between cluster monomers.

[0131] Since the motion spaces of heterogeneous unmanned clusters are usually different, there is usually no risk of collision between the monomers of heterogeneous unmanned clusters. Therefore, in one embodiment of the present invention, the interaction between cluster monomers is set only between cluster monomers of the same unmanned cluster, and the safe operating distance between cluster monomers can be specifically set according to different unmanned clusters, the motion speed of cluster monomers, and the environment, so as to avoid collision between cluster monomers.

[0132] Based on the interaction rules between a cluster monomer and its neighboring monomers of the same cluster set above, in one embodiment of the present invention, the value of the interaction between a cluster monomer and its neighboring monomers of the same cluster can be determined using the following formula:

[0133]

[0134] Among them, |F| represents the value of interaction, α1 represents the maximum value of the force, and β represents the proportional coefficient of the degree of change of the force with the distance between cluster monomers.

[0135] Among them, the maximum value of the force can be specifically set according to factors such as the movement speed of different unmanned clusters and cluster monomers to avoid collisions between cluster monomers.

[0136] In one embodiment of the present invention, a segmented design is adopted to design the interaction strength between a cluster monomer and its adjacent monomers of the same cluster, so that the interaction between cluster monomers of an unmanned cluster can change with the change of the monomer spacing, thereby ensuring the stability of the monomer spacing in the unmanned cluster and achieving obstacle avoidance between monomers.

[0137] Furthermore, in order to ensure the obstacle avoidance effect and avoid excessive calculation, when the number of cluster monomers in an unmanned cluster is more than 5, the interaction between a cluster monomer and its neighboring same cluster monomers may include: the interaction between a cluster monomer and its first neighboring same cluster monomer, the interaction between a cluster monomer and its second neighboring same cluster monomer, the interaction between a cluster monomer and its third neighboring same cluster monomer, and the interaction between a cluster monomer and its fourth neighboring same cluster monomer. When the number of cluster monomers in an unmanned cluster is less than 5, the interaction between a cluster monomer and its neighboring same cluster monomers includes: the interaction between a cluster monomer and all other cluster monomers in the same unmanned cluster.

[0138] Step S5, setting the interaction rules between the cluster monomers and the environment according to the target existence probability of the grid cells.

[0139] In one embodiment of the present invention, the interaction rules between the cluster monomers and the environment are set as follows:

[0140] The interaction between a cluster monomer and the environment is a vector pointing from a cluster monomer to the center of the grid cell with the highest probability of target existence among its neighboring grid cells.

[0141] Based on the interaction rules between cluster monomers and the environment set above, the movement direction of cluster monomers at the next moment can be made to tend to the adjacent grid cells with the highest probability of target existence around them. In the process of continuous search behavior emergence, grid cells with a higher probability of target existence can be visited and searched multiple times, thereby improving the targeted search for targets.

[0142] Step S6, setting the interaction rules between the cluster monomers and the heterogeneous unmanned clusters according to the digital pheromones corresponding to the heterogeneous unmanned clusters.

[0143] In one embodiment of the present invention, the interaction rules between the cluster monomer and the heterogeneous unmanned cluster are set as follows:

[0144] The interaction between a cluster monomer and the unmanned cluster to which it belongs is the vector of the cluster monomer pointing to the center of the grid unit corresponding to the smallest digital pheromone among the digital pheromones corresponding to the unmanned cluster to which it belongs;

[0145] The interaction between a cluster monomer and an unmanned cluster that it does not belong to is the vector from the center of the grid unit corresponding to the largest digital pheromone among the digital pheromones corresponding to the current unmanned cluster that it does not belong to to the cluster monomer;

[0146] The interaction between a cluster monomer and a heterogeneous unmanned cluster is the sum of the interaction between a cluster monomer and the unmanned cluster to which it belongs and the interaction between a cluster monomer and the unmanned cluster to which it does not belong.

[0147] Specifically, taking the above-mentioned heterogeneous unmanned cluster including an aerial unmanned cluster and a ground unmanned cluster as an example, for a cluster monomer, the interaction between the cluster monomer and the heterogeneous unmanned cluster includes the sum of the interaction between the cluster monomer and the unmanned cluster to which it belongs and the interaction between the cluster monomer and another unmanned cluster.

[0148] Assumptions: represents the interaction between a cluster monomer and the unmanned cluster to which it belongs, represents the interaction between a cluster monomer and another unmanned cluster, then the interaction between a cluster monomer and a heterogeneous unmanned cluster is:

[0149]

[0150] In one embodiment of the present invention, based on the interaction rules between cluster monomers and heterogeneous unmanned clusters set above, the movement of cluster monomers can be guided by utilizing the attraction of digital pheromones corresponding to the unmanned cluster to which it belongs and the repulsion of digital pheromones corresponding to other unmanned clusters that it does not belong to, so that cluster monomers can move to grid cells with small visits to the unmanned cluster to which it belongs and small visits to other unmanned clusters, so as to minimize the duplication of heterogeneous cluster search areas and improve the efficiency of collaborative search. In addition, when there is an area that an unmanned cluster cannot reach, other unmanned clusters can be attracted to search in that area, so as to achieve complementary advantages and realize full coverage of the area and target search.

[0151] Step S7, determining the interaction between the cluster monomer at the current moment and its adjacent same cluster monomers according to the interaction rules between the cluster monomers and their adjacent same cluster monomers, determining the interaction between the cluster monomers and the environment at the current moment according to the interaction rules between the cluster monomers and the environment, and determining the interaction between the cluster monomers and the heterogeneous unmanned clusters at the current moment according to the interaction rules between the cluster monomers and the heterogeneous unmanned clusters.

[0152] In one embodiment of the present invention, based on the above-mentioned specifically set interaction rules between cluster monomers and their adjacent same cluster monomers, interaction rules between cluster monomers and the environment, and interaction rules between cluster monomers and heterogeneous unmanned clusters, according to the specific positions of the cluster monomers at the current moment, the target existence probability of the grid units at the current moment, and the digital pheromones, it is possible to determine the interaction between the cluster monomers at the current moment and their adjacent same cluster monomers, the interaction between the cluster monomers and the environment, and the interaction between the cluster monomers and heterogeneous unmanned clusters.

[0153] Step S8, based on the interaction between the cluster monomer at the current moment and its adjacent cluster monomers of the same cluster, the interaction between the cluster monomer and the environment, and the interaction between the cluster monomer and the heterogeneous unmanned cluster, calculate the movement direction and movement speed of the cluster monomer at the next moment, and control the cluster monomer to perform mobile search based on the obtained movement direction and movement speed.

[0154] In one embodiment of the present invention, the following formula is used to calculate the movement direction and movement speed of the cluster monomer at the next moment:

[0155]

[0156] in, represents the velocity vector of the cluster monomer, represents the interaction between a cluster monomer and its first neighboring monomer of the same cluster, represents the interaction between a cluster monomer and its second neighboring monomer of the same cluster, represents the interaction between a cluster monomer and its g-th neighboring monomer of the same cluster, represents the interaction between the cluster monomer and the heterogeneous unmanned cluster, represents the interaction between the cluster monomers and the environment, α 11 express The corresponding weight parameter, α 12 express The corresponding weight parameter, α 1g express The corresponding weight parameter, α2, represents The corresponding weight parameter, α3, represents The corresponding weight parameter.

[0157] In one embodiment of the present invention, the weight parameter [α 11 , α 12 , …, α 1g , α2, α3] can be adjusted according to the actual situation to achieve a balance between local target search and search for the entire mission area coverage, and to avoid repeated searches of grid cells in the same mission area by heterogeneous unmanned clusters as much as possible, so as to achieve efficient collaborative search of multiple heterogeneous unmanned clusters.

[0158] See also Figure 3 In one embodiment of the present invention, the collaborative search method may further include the following steps:

[0159] Step S9, determining whether the environmental uncertainty is less than a preset uncertainty threshold;

[0160] If not, the target existence probability and digital pheromone of the grid unit are updated according to the target existence probability update mechanism and the digital pheromone update mechanism, the interaction is calculated and updated according to the set interaction rules, the movement direction and movement speed of the cluster monomer at the next moment are calculated based on the updated interaction, and the cluster monomer is controlled to continue the mobile search;

[0161] If so, the collaborative search of the unmanned cluster ends.

[0162] The environmental uncertainty is defined as follows:

[0163]

[0164] Among them, EN represents environmental uncertainty, P ij Represents the probability of the target existing in the ijth grid cell (i, j).

[0165] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, 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 other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In addition, "front", "back", "left", "right", "upper" and "lower" in this article are all referenced to the placement state shown in the accompanying drawings.

[0166] 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 heterogeneous unmanned cluster collaborative search method based on emergence, characterized in that: include: Divide the task area into a plurality of grid units, wherein the area of ​​the grid unit is larger than the target size and smaller than or equal to the search area of ​​a single cluster monomer; Based on the probability density function and the sensor detection information of the cluster monomer, the target existence probability of the grid unit and the target existence probability update mechanism are constructed; Based on the familiarity of the heterogeneous unmanned clusters with the grid cells, digital pheromones and digital pheromone update mechanisms of all grid cells corresponding to the heterogeneous unmanned clusters are constructed respectively; According to the motion parameters of the cluster monomers, the interaction rules between the cluster monomers and their neighboring monomers of the same cluster are set; According to the target existence probability of the grid unit, the interaction rules between the cluster monomers and the environment are set; According to the digital pheromones corresponding to the heterogeneous unmanned clusters, the interaction rules between the cluster monomers and the heterogeneous unmanned clusters are set; Determine the interaction between the cluster monomer at the current moment and its neighboring monomers of the same cluster according to the interaction rules between the cluster monomer and its neighboring monomers of the same cluster; determine the interaction between the cluster monomer and the environment at the current moment according to the interaction rules between the cluster monomer and the environment; determine the interaction between the cluster monomer and the heterogeneous unmanned cluster at the current moment according to the interaction rules between the cluster monomer and the heterogeneous unmanned cluster; According to the interaction between the cluster monomer at the current moment and its adjacent monomers of the same cluster, the interaction between the cluster monomer and the environment, and the interaction between the cluster monomer and the heterogeneous unmanned cluster, the movement direction and speed of the cluster monomer at the next moment are calculated, and the cluster monomer is controlled to perform mobile search according to the obtained movement direction and speed.

2. The emergence-based heterogeneous unmanned cluster collaborative search method according to claim 1, characterized in that: The initial target existence probability of the grid cell is: Among them, P represents the initial target existence probability corresponding to the grid cell, f(·) represents the target existence probability density function of the mixed two-dimensional Gaussian probability density function corresponding to the target, s represents the integral differential area corresponding to f(·), and D represents the integral area corresponding to the grid cell.

3. The emergence-based heterogeneous unmanned cluster collaborative search method according to claim 2, characterized in that: The target existence probability update mechanism of the grid unit includes: If the cluster monomer detects the target in the grid cell at time t, the target existence probability of the grid cell is updated using the following formula to obtain the target existence probability of the grid cell at the next moment; If the cluster monomer does not detect the target in the grid cell at time t, the target existence probability of the grid cell is updated using the following formula to obtain the target existence probability of the grid cell at the next moment; Among them, P(t+1) represents the probability of the target existing in the grid cell at time t+1, P d represents the sensor detection probability of the cluster monomer, P(t) represents the target existence probability of the grid unit at time t, and P f Indicates the false alarm rate.

4. The emergence-based heterogeneous unmanned cluster collaborative search method according to claim 1, characterized in that: Assume that the digital pheromone of the ijth grid cell corresponding to a certain unmanned cluster at time t is s a (L ij , t); The digital pheromone update mechanism includes: The digital pheromone of the ijth grid cell corresponding to a certain unmanned cluster at time t is calculated and updated using the following formula: s a (L ij ,t)=(1-E a )[(1-G a )(s a (L ij ,t-1)+via ij，t ·d a (L ij ,t))+g a (L ij ,t)] Among them, E a represents the pheromone propagation coefficient, G a represents the pheromone evaporation coefficient, s a (L ij , t-1) represents the digital pheromone of the ijth grid cell corresponding to the current unmanned cluster at time t-1, via ij，t represents the number of times the cluster monomer of the current unmanned cluster passes through the ijth grid unit at time t, d a (L ij , t) represents the amount of digital pheromone released when the cluster monomer of the current unmanned cluster passes through the ijth grid unit at time t, g a (L ij , t) represents the amount of digital pheromone that penetrates into the ijth grid cell from the adjacent grid cell from time t-1 to time t.

5. The emergence-based heterogeneous unmanned cluster collaborative search method according to claim 1, characterized in that: The interaction rules between the cluster monomer and its neighboring monomers of the same cluster are set as: When the distance x between cluster monomers satisfies 0≤x≤L, the interaction between cluster monomers is repulsive, and the repulsive force increases as the distance decreases; When the distance x between cluster monomers satisfies L<x≤2L, the interaction between cluster monomers is gravitational force, and the gravitational force increases with the increase of the distance; When the distance x between cluster monomers satisfies 2L<x≤3L, the interaction between cluster monomers is gravitational force, and the gravitational force decreases as the distance increases; When the spacing x between cluster monomers satisfies x>3L, the interaction between cluster monomers is zero; The direction of gravity is the direction from the cluster monomer to its neighboring cluster monomer, the direction of repulsion is opposite to the direction of gravity, and L represents the safe movement distance between cluster monomers.

6. The emergence-based heterogeneous unmanned cluster collaborative search method according to claim 5, characterized in that: The value of the interaction between a cluster monomer and its neighboring monomers of the same cluster is determined using the following formula: Among them, |F| represents the value of interaction, α1 represents the maximum value of the force, and β represents the proportional coefficient of the degree of change of the force with the distance between cluster monomers.

7. The emergence-based heterogeneous unmanned cluster collaborative search method according to any one of claims 1 to 6, characterized in that: The interaction rules between the cluster monomers and the environment are set as follows: The interaction between a cluster monomer and the environment is a vector pointing from a cluster monomer to the center of the grid cell with the highest probability of target existence among its neighboring grid cells.

8. The emergence-based heterogeneous unmanned cluster collaborative search method according to claim 7, characterized in that: The interaction rules between the cluster monomer and the heterogeneous unmanned cluster are set as follows: The interaction between a cluster monomer and the unmanned cluster to which it belongs is the vector of the cluster monomer pointing to the center of the grid unit corresponding to the smallest digital pheromone among the digital pheromones corresponding to the unmanned cluster to which it belongs; The interaction between a cluster monomer and an unmanned cluster that it does not belong to is the vector from the center of the grid unit corresponding to the largest digital pheromone among the digital pheromones corresponding to the current unmanned cluster that it does not belong to to the cluster monomer; The interaction between a cluster monomer and a heterogeneous unmanned cluster is the sum of the interaction between a cluster monomer and the unmanned cluster to which it belongs and the interaction between a cluster monomer and the unmanned cluster to which it does not belong.

9. The emergence-based heterogeneous unmanned cluster collaborative search method according to claim 8, characterized in that: The movement direction and speed of the cluster monomer at the next moment are calculated using the following formula: in, represents the velocity vector of the cluster monomer, represents the interaction between a cluster monomer and its first neighboring monomer of the same cluster, represents the interaction between a cluster monomer and its second neighboring monomer of the same cluster, represents the interaction between a cluster monomer and its g-th neighboring monomer of the same cluster, represents the interaction between the cluster monomer and the heterogeneous unmanned cluster, represents the interaction between the cluster monomers and the environment, α 11 express The corresponding weight parameter, α 12 express The corresponding weight parameter, α 1g express The corresponding weight parameter, α2, represents The corresponding weight parameter, α3, represents The corresponding weight parameter.

10. The emergence-based heterogeneous unmanned cluster collaborative search method according to claim 1, characterized in that: The method further comprises: Determine whether the environmental uncertainty is less than a preset uncertainty threshold; If not, the target existence probability and digital pheromone of the grid unit are updated according to the target existence probability update mechanism and the digital pheromone update mechanism, the interaction is calculated and updated according to the set interaction rules, the movement direction and movement speed of the cluster monomer at the next moment are calculated based on the updated interaction, and the cluster monomer is controlled to continue the mobile search; If so, the collaborative search of the unmanned cluster ends.

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