Bird-flock-imitating unmanned aerial vehicle cluster density and area control method and unmanned aerial vehicle

Abstract

The invention discloses a bird flock-imitating unmanned aerial vehicle cluster density and area control method and an unmanned aerial vehicle, and relates to the unmanned aerial vehicle technology, and the method comprises the steps: initializing the position and speed of the unmanned aerial vehicle in an unmanned aerial vehicle cluster; calculating an interaction force applied to the unmanned aerial vehicles in the unmanned aerial vehicle cluster, wherein the interaction force comprises an alignment force and an attraction-repulsive force based on the Lanna-Jones potential; updating the speed and the position of the unmanned aerial vehicle according to the resultant force borne by the unmanned aerial vehicle; and calculating the area of the unmanned aerial vehicle cluster after stabilization, and if the expectation is not met, repeatedly adjusting the rejection distance between the unmanned aerial vehicles until the unmanned aerial vehicle cluster is controlled to reach the expected density and area. According to the method, the effect of coordinated flight of the unmanned aerial vehicle cluster can be achieved by adjusting related parameters in the control model, the density and area of the cluster are flexibly regulated and controlled, and then the purpose of simulating the bird flock form in the flight process of the unmanned aerial vehicle cluster is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of unmanned aerial vehicles, and in particular to a method for controlling the density and area of ​​a cluster of unmanned aerial vehicles (UAVs) that simulates a flock of birds and an unmanned aerial vehicle (UAV). Background Art

[0002] When drone swarms fly densely, they can actively control the density and area of ​​the group to imitate the bird flock, effectively hiding in the natural environment and improving the success rate of the mission. Due to the large number of drone swarms and the complex interactions between drones, it is difficult to effectively control their density and area with existing methods. Summary of the invention

[0003] The embodiment of the present application provides a method for controlling the density and area of ​​a drone cluster that imitates a flock of birds and a drone. The drone cluster adopts a distributed control method, and there is no need to control each drone. The effect of coordinated flight of the drone cluster can be achieved by adjusting the relevant parameters in the control model, and the density and area of ​​the cluster can be flexibly adjusted, thereby achieving the purpose of imitating the morphology of a bird flock during the flight of the drone cluster.

[0004] The present application embodiment provides a method for controlling the density and area of ​​a drone cluster that simulates a bird flock, including:

[0005] Initialize the position and speed of the drones in the drone cluster;

[0006] Calculating the interaction forces on the drones in the drone cluster, wherein the interaction forces include alignment forces and attraction-repulsion forces based on Lanner-Jones potential;

[0007] Update the speed and position of each drone based on the combined force acting on it;

[0008] Calculate the area of ​​the drone cluster after stabilization. If it does not meet expectations, repeatedly adjust the repulsion distance between drones until the drone cluster is controlled to reach the desired density and area.

[0009] Optionally, the interaction forces acting on the drones in the drone cluster include:

[0010] Consider the drone as a point mass in two-dimensional motion, and specify that all drones have the same unit mass, and establish the point mass kinematic equation to satisfy:

[0011]

[0012] in, are the position vector, velocity vector and acceleration vector of UAV i respectively;

[0013] Let the control input at time t be:

[0014]

[0015] in, and are the alignment force and the attraction-repulsion interaction force based on the Lanner-Jones potential, respectively.

[0016] Optionally, the alignment force refers to the velocity alignment force exerted on UAV i by UAVs within the communication range r, which is used to make UAV i move in the same direction, satisfying:

[0017]

[0018] Among them, c v is the alignment force coefficient, where e i (t) is the time t<θ i (t)>unit direction vector;

[0019] <θ i (t)> means that the average motion direction of the neighbors of drone i at time t satisfies:

[0020]

[0021] Where N i ={j||p i -p j ||2<r,j≠i}, represents the neighbor set of drone i at time t.

[0022] Optionally, the attraction-repulsion force of the Lanner-Jones potential is used to maintain a fixed repulsion distance between adjacent drones, and the attraction-repulsion force of the Lanner-Jones potential is in the form of:

[0023]

[0024] Among them, ò represents the depth of the potential well, σ represents the distance between the two bodies when the potential energy of the interaction is exactly zero, and r represents the distance between adjacent drones;

[0025] The corresponding two-body force of the Lanner-Jones potential is:

[0026]

[0027] Among them, r represents the distance vector between the two bodies.

[0028] Optionally, updating the speed and position of each drone according to the resultant force acting on the individual drones includes: evolving the area of ​​the drone cluster based on the attraction-repulsion force form and the corresponding two-body force.

[0029] Optionally, controlling the drone swarm to achieve the desired density and area includes:

[0030] The fixed repulsion distance between adjacent drones is changed from a preset distance range, and the perception distance is always kept greater than the specified value of the repulsion distance, and the drone cluster area is evolved.

[0031] An embodiment of the present application also proposes a drone, which flies within a drone cluster and includes a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, the steps of the drone cluster density and area control method that simulates a bird flock are implemented as described above.

[0032] The drone cluster of the embodiment of the present application adopts a distributed control method. There is no need to control each drone. The coordinated flight of the drone cluster can be achieved by adjusting the relevant parameters in the control model, and the density and area of ​​the cluster can be flexibly adjusted, thereby achieving the purpose of imitating the morphology of a bird flock during the flight of the drone cluster.

[0033] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0035] Figure 1 The flowchart of the method for controlling the density and area of ​​a drone cluster simulating a bird flock according to an embodiment of the present application is shown;

[0036] Figure 2 This is a schematic diagram of the evolution of the drone cluster state in the application example of this application;

[0037] Figure 3 This is the curve showing the change of the drone cluster area with the repulsion distance in the application example of this application. DETAILED DESCRIPTION

[0038] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0039] The present application embodiment provides a method for controlling the density and area of ​​a drone cluster that simulates a bird flock, such as Figure 1 As shown, including:

[0040] In step S101, the positions and velocities of the drones in the drone cluster are initialized, such as Figure 2 As shown, in the specific example of the present application, 40 drones are randomly generated in a two-dimensional area with a side length of 200m. At this time, the cluster is in a completely disordered state, and the speed and position of each drone are completely random.

[0041] In step S102, the interaction forces on the drones in the drone cluster are calculated, wherein the interaction forces include alignment forces and attraction-repulsion forces based on the Lanner-Jones potential. In the specific example, without loss of generality, the shape and dynamic characteristics of the drones themselves are ignored, the drones are abstracted as two-dimensional moving particles, and the particle kinematic equations are established.

[0042] In a specific example, the present application firstly simulates the Brown Swift metric interaction to design a drone speed synchronization control protocol; secondly, the density and area of ​​the cluster are controlled based on the Lanner-Jones potential. The Lanner-Jones potential uses the distance between the two bodies and the depth of the potential well as variables, has the advantages of few parameters and simple design, and can generate a gentle attraction when the distance is far, and a strong repulsion when the distance is close, so as to avoid the splitting and collision of the cluster.

[0043] In step S103, the speed and position of each drone are updated according to the resultant force acting on the drone.

[0044] In step S104, the area of ​​the drone cluster after stabilization is calculated. If it does not meet expectations, the repulsion distance between the drones is repeatedly adjusted until the drone cluster is controlled to reach the desired density and area.

[0045] The drone cluster of the embodiment of the present application adopts a distributed control method. There is no need to control each drone. The coordinated flight of the drone cluster can be achieved by adjusting the relevant parameters in the control model, and the density and area of ​​the cluster can be flexibly adjusted, thereby achieving the purpose of imitating the morphology of a bird flock during the flight of the drone cluster.

[0046] In some embodiments, the interaction forces on the drones in the drone cluster include:

[0047] The drone is considered as a mass point in two-dimensional motion, and all drone masses are assigned the same unit mass to simplify the mathematical representation of kinetic energy and potential energy. Consider a drone working in a two-dimensional Euclidean space, and establish its mass point kinematic equation to satisfy:

[0048]

[0049] in, are the position vector, velocity vector and acceleration vector of UAV i respectively;

[0050] Let the control input at time t be:

[0051]

[0052] in, and are the alignment force and the attraction-repulsion interaction force based on the Lanner-Jones potential, respectively.

[0053] In some embodiments, the alignment force refers to the velocity alignment force exerted on UAV i by UAVs within the communication range r, which is used to make UAV i move in the same direction, satisfying:

[0054]

[0055] Among them, c v is the alignment force coefficient, where e i (t) is the time t<θ i (t)>unit direction vector,<θ i (t)> means that the average motion direction of the neighbors of drone i at time t satisfies:

[0056]

[0057] Where N i ={j||p i -p j ||2<r,j≠i}, represents the neighbor set of UAV i at time t (i.e., the UAVs within the communication range).

[0058] The Lanner-Jones potential is a mathematical model used to simulate the potential energy of interaction between two electrically neutral molecules or atoms. In some embodiments of the present application, the attraction-repulsion force of the Lanner-Jones potential is used to keep a fixed relative distance r between adjacent drones. min (also known as the minimum distance or repulsion distance), and the relative distance between drones is less than r min When the distance is far, a stronger repulsive force can be generated to avoid collision; when the distance is far, a softer attractive force can be generated to avoid cluster splitting. The Lanner-Jones potential energy takes the distance between the two bodies as the only variable and contains two parameters. The attraction-repulsion form of the Lanner-Jones potential is:

[0059]

[0060] in, represents the depth of the potential well, σ represents the distance between the two bodies when the potential energy of the interaction is exactly zero, and r represents the distance between adjacent drones. It can also be written in another form:

[0061]

[0062] r min =2 1 / 6 σ=1.1225σ is the distance between the two bodies at the bottom of the potential energy well.

[0063] In physical terms, the first term 1 / r 12 It can be considered to correspond to the mutual repulsion between two bodies at close distance. The second term 1 / r 6 It corresponds to the effect of two bodies mainly attracting each other at a long distance.

[0064] The corresponding two-body force of the Lanner-Jones potential is:

[0065]

[0066] Among them, r represents the distance vector between the two bodies.

[0067] In some embodiments, updating the speed and position of individual drones based on the combined force acting on them includes: evolving the area of ​​the drone cluster based on the attraction-repulsion force form and the corresponding two-body force.

[0068] In the specific example, suppose the number of individuals in the drone cluster system n = 40, σ = 1, and the drone repulsion distance r min =8, perception radius r sense =13. The initial position of the virtual leader is (25, 25) and the speed is constant at (0.5, 0.5). Under the action of equations (1) and (2), the evolution of the drone cluster area is as follows: Figure 2 shown. Figure 2 In the figure, the virtual navigator is represented by a five-pointed star, the arrow direction is the speed direction of the drone, and the arrow length represents the speed of the drone. It can be seen that the cluster area can converge quickly and eventually stabilize.

[0069] In some embodiments, controlling the drone swarm to achieve a desired density and area includes:

[0070] The fixed repulsion distance between adjacent drones is changed from a preset distance range, and the perception distance is always kept greater than the specified value of the repulsion distance, and the drone cluster area is evolved.

[0071] In the specific example, let the minimum distance r min Change from 1 to 20m while maintaining the perception distance r sense Always 5m greater than the minimum distance.

[0072] r sense =r min +5 (8)

[0073] Finally, the cluster area change curve is obtained as follows: Figure 3 As shown, it can be seen that the cluster area increases exponentially with the increase of the repulsion distance.

[0074] In summary, in the embodiment of the present application, when the drone cluster flies, the interaction between individuals is metric interaction, that is, interaction with other drones within the communication range, and the movement direction of the individual is the average movement direction of all individuals within the communication distance, so as to achieve cluster speed synchronization; secondly, adjacent drones should maintain a fixed relative distance. To avoid collision, when the relative distance between drones is less than the minimum distance, a large repulsive force should be generated. Therefore, when the drone cluster of the present application flies, the designed individuals will be subject to the interaction force based on the Lanner-Jones potential. By adjusting the two-body distance variable value in the Lanner-Jones potential, the cluster density and area can be flexibly controlled.

[0075] The method of the present application is based on the density control method of the Lanner-Jones potential. The Lanner-Jones potential uses the distance between two bodies and the depth of the potential well as variables, and has the advantages of few parameters and simple design. The present application designs a density and area control method based on the Lanner-Jones potential, which can keep a fixed relative distance between adjacent drones. When the relative distance between drones is small, a larger repulsive force can be generated to avoid collision; when the distance is far, a softer attractive force can be generated to avoid cluster splitting. By adjusting the action distance parameter in the Lanner-Jones potential, the density and area of ​​the drone cluster can be effectively controlled.

[0076] An embodiment of the present application also proposes a drone, which flies within a drone cluster and includes a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, the steps of the drone cluster density and area control method that simulates a bird flock are implemented as described above.

[0077] It should be noted that in the various embodiments of the present application, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0078] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0079] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0080] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A method for controlling the density and area of ​​a drone cluster by simulating a flock of birds, characterized in that: include: Initialize the position and speed of the drones in the drone cluster; Calculating the interaction forces on the drones in the drone cluster, wherein the interaction forces include alignment forces and attraction-repulsion forces based on Lanner-Jones potential; Update the speed and position of each drone based on the combined force acting on it; Calculate the area of ​​the drone cluster after stabilization. If it does not meet expectations, repeatedly adjust the repulsion distance between drones until the drone cluster is controlled to reach the desired density and area.

2. The method for controlling the density and area of ​​a drone cluster simulating a bird flock as claimed in claim 1, characterized in that: Calculating the interaction forces on the drones in the drone cluster includes: Consider the drone as a point mass in two-dimensional motion, and specify that all drones have the same unit mass, and establish the point mass kinematic equation to satisfy: Among them, p i ,v i , are the position vector, velocity vector and acceleration vector of UAV i respectively; Let the control input at time t be: in, and are the alignment force and the attraction-repulsion interaction force based on the Lanner-Jones potential, respectively.

3. The method for controlling the density and area of ​​a drone cluster simulating a bird flock as claimed in claim 2, characterized in that: The alignment force refers to the velocity alignment force exerted on UAV i by UAVs within the communication range r, which is used to make UAV i move in the same direction, satisfying: f i v (t+1)=c v ve i (t) Among them, c v is the alignment force coefficient, where e i (t) is the time t<θ i (t)>unit direction vector; <θ i (t)> means that the average motion direction of the neighbors of drone i at time t satisfies: Where N i ={j||p i -p j ||2<r,j≠i}, represents the neighbor set of drone i at time t.

4. The method for controlling the density and area of ​​a drone cluster simulating a bird flock as claimed in claim 3, characterized in that: The attraction-repulsion force of the Lanner-Jones potential is used to keep a fixed repulsion distance between adjacent drones. The attraction-repulsion force of the Lanner-Jones potential is in the form of: Among them, ò represents the depth of the potential well, σ represents the distance between the two bodies when the potential energy of the interaction is exactly zero, and r represents the distance between adjacent drones; The corresponding two-body force of the Lanner-Jones potential is: Among them, r represents the distance vector between the two bodies.

5. The method for controlling the density and area of ​​a drone cluster simulating a bird flock as claimed in claim 4, characterized in that: Updating the speed and position of individual drones according to the resultant force they are subjected to includes: evolving the area of ​​the drone cluster based on the attraction-repulsion force form and the corresponding two-body force.

6. The method for controlling the density and area of ​​a drone cluster simulating a bird flock as claimed in claim 5, characterized in that: Controlling a drone swarm to achieve the desired density and area includes: The fixed repulsion distance between adjacent drones is changed from a preset distance range, and the perception distance is always kept greater than the specified value of the repulsion distance, and the drone cluster area is evolved.

7. A drone, characterized in that: The drone flies within a drone cluster and includes a processor and a memory. A computer program is stored in the memory. When the computer program is executed by the processor, the steps of the method for controlling the density and area of ​​a drone cluster simulating a bird flock are implemented as described in any one of claims 1 to 6.

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