CN117608318A - Unmanned aerial vehicle formation obstacle avoidance control method and system based on bird-like phototaxis - Google Patents
Unmanned aerial vehicle formation obstacle avoidance control method and system based on bird-like phototaxis Download PDFInfo
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Abstract
The invention provides an unmanned aerial vehicle formation obstacle avoidance control method and system based on bird-like phototaxis, and relates to the technical field of unmanned aerial vehicle cluster control, wherein the method comprises the following steps: acquiring the position and speed of each unmanned aerial vehicle, the position and speed of peripheral obstacles and the position of a target object at the current moment; and obtaining a phototactic obstacle avoidance control law of the unmanned aerial vehicle according to the position and the speed of the unmanned aerial vehicle at the current moment, the position and the speed of each neighbor unmanned aerial vehicle, the position and the speed of each obstacle around and the position of a target object by utilizing a phototactic obstacle avoidance model which is pre-established according to the characteristic of combining the artificial potential field model with the phototactic flight of birds, and updating the control model of the unmanned aerial vehicle according to the phototactic obstacle avoidance control law to obtain the speed and the position of the unmanned aerial vehicle at the next moment. The artificial potential field method based on the bird phototactic characteristic improvement can better ensure that unmanned aerial vehicle formation searches a maneuver flight route, and obviously improves the obstacle avoidance performance of the unmanned aerial vehicle formation in complex and non-deterministic environments.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle cluster control, in particular to an unmanned aerial vehicle formation obstacle avoidance control method and system based on bird-like phototaxis.
Background
The unmanned aerial vehicle cluster obstacle avoidance control is a control method that unmanned aerial vehicles in the unmanned aerial vehicle cluster can safely fly to a target point from a starting point under the action of a designed obstacle avoidance control law; meanwhile, unmanned aerial vehicles in the clusters cannot collide with each other, and further cannot generate a flying process of chain collision. With the development of sensing technology, communication technology and computing technology, research on multi-unmanned aerial vehicle formation has been widely applied to the military and civil fields, and accuracy, comprehensiveness and reliability of system control thereof are gradually increasing. However, the formation faces complex and unknown multi-element flight situations in the actual flight process, namely, the situations of dense obstacle environments, dynamic obstacles, faults of the unmanned aerial vehicle and the like may be encountered in the flight process, and the obstacle avoidance and collision avoidance capabilities of the formation are particularly important.
Meanwhile, in order to further improve the working efficiency of the multiple unmanned aerial vehicles, the number of unmanned aerial vehicles in formation is also continuously increased, at the moment, the control complexity of the formation system and the scale of the control system are correspondingly increased, and the problem of collision of a large-scale system is more likely to occur. Therefore, in order to further improve unmanned aerial vehicle cluster control efficiency, it has important practical meaning to study the collision avoidance and obstacle avoidance problems in unmanned aerial vehicle formation autonomous flight process. In the existing unmanned aerial vehicle obstacle avoidance control method, the research is mainly conducted on the cluster obstacle avoidance based on the potential field method, however, the cluster obstacle avoidance based on the potential field method is simple in calculation and high in real-time performance, but is easy to sink into local minima and has the problem of limitation, so that the research on a more effective unmanned aerial vehicle formation obstacle avoidance control method is needed.
Disclosure of Invention
The invention aims to provide an unmanned aerial vehicle formation obstacle avoidance control method and system based on bird-like phototaxis, which improve the obstacle avoidance performance of unmanned aerial vehicle formation in complex and non-deterministic environments.
In order to achieve the above object, the present invention provides the following.
In one aspect, the invention provides an unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototaxis, wherein the unmanned aerial vehicle formation comprises a plurality of unmanned aerial vehicles, and the unmanned aerial vehicle formation obstacle avoidance control method comprises the following steps of.
The method comprises the steps of obtaining the position of each unmanned aerial vehicle at the current moment, the speed of each unmanned aerial vehicle at the current moment, the position of each obstacle around each unmanned aerial vehicle at the current moment, the speed of each obstacle around each unmanned aerial vehicle at the current moment and the position of a target object.
Aiming at any unmanned aerial vehicle, utilizing a phototactic obstacle avoidance model formed by the unmanned aerial vehicle, and obtaining a phototactic obstacle avoidance control law of the unmanned aerial vehicle according to the position of the unmanned aerial vehicle at the current moment, the speed of the unmanned aerial vehicle at the current moment, the position of each neighbor unmanned aerial vehicle at the current moment, the speed of each obstacle around the unmanned aerial vehicle at the current moment and the position of a target object; the phototactic obstacle avoidance model is a model obtained by combining an artificial potential field model formed by the unmanned aerial vehicle and a phototactic model formed by the unmanned aerial vehicle; the neighbor unmanned aerial vehicle is an unmanned aerial vehicle adjacent to the unmanned aerial vehicle in unmanned aerial vehicle formation; the artificial potential field model is a model constructed according to a control model of each unmanned aerial vehicle in unmanned aerial vehicle formation; the phototactic model is a model which is established by simulating the characteristic of the phototactic flight of birds.
And updating a control model of the unmanned aerial vehicle according to the phototactic obstacle avoidance control law to obtain the speed of the unmanned aerial vehicle at the next moment and the position of the unmanned aerial vehicle at the next moment.
Alternatively, the control model of the unmanned aerial vehicle is shown in the following formula.
。
Wherein n is the number of unmanned aerial vehicles in unmanned aerial vehicle formation, q i Is the position of the drone denoted i,a differential value for the position of the unmanned aerial vehicle denoted i; p is p i Speed of unmanned aerial vehicle denoted by i, < +.>A differential value of the speed of the unmanned aerial vehicle, numbered i; u (u) i Control input for unmanned aerial vehicle with reference number i, < >>Wherein->For the control input component of the linear speed of the unmanned aerial vehicle, numbered i, +.>For the control input component of the heading angle of the drone, denoted by i, T represents the transpose of the matrix.
Optionally, the unmanned aerial vehicle formation comprises a leading unmanned aerial vehicle and a plurality of following unmanned aerial vehicles; the artificial potential field model comprises potential field functions between any two unmanned aerial vehicles, potential field functions between the unmanned aerial vehicle and the obstacle, and potential field functions between the unmanned aerial vehicle and the navigation item; the navigation items are targets followed by the unmanned aerial vehicle, the navigation items leading the unmanned aerial vehicle are targets, and the navigation items following the unmanned aerial vehicle are leading the unmanned aerial vehicle.
Optionally, the potential field function between any two unmanned aerial vehicles is as follows.
。
Wherein,representing a potential field function between the unmanned aerial vehicle and the unmanned aerial vehicle, q i Representing the position, q, of the unmanned aerial vehicle denoted by i j Represents the position, q, of the unmanned aerial vehicle denoted by j ij Distance q between unmanned aerial vehicle with reference number i and unmanned aerial vehicle with reference number j ij =q i -q j (i. Noteq. J), d is the expected distance between the two unmanned aerial vehicles, I.I σ Is sigma norm ++>For the inter-machine obstacle avoidance function, s is an integral variable, ds represents integrating s, r α Is the attractive force distance of the unmanned plane.
The inter-machine obstacle avoidance function is shown in the following formula.
。
Wherein z is a positive constant, eta is E (0, 1), h α Representing the independent variable of the inter-machine obstacle avoidance function.
The potential field function between the drone and the obstacle is shown as follows.
。
Wherein,is a potential field function between the drone and the obstacle, < >>Unmanned aerial vehicle and obstacle o, denoted by reference numeral i k Distance of->Representing obstacle o k Is (are) located>，/>Is a barrier avoiding function of a machine barrier, r o Is the rejection radius of the unmanned aerial vehicle.
The obstacle avoidance function of the machine obstacle is shown in the following formula.
。
Wherein h is o Independent variables representing barrier avoidance functions.
The potential field function between the drone and the navigation term is shown as follows.
。
Wherein,q is a potential field function between the unmanned aerial vehicle and the navigation term it Distance q between unmanned aerial vehicle and navigation item denoted by i t Representing the position of the navigation item, q r Is the desired separation of the drone from the navigation item.
Alternatively, the phototactic model is shown in the following formula.
。
Wherein U is i Denoted by the reference numeral i is a drone,is unmanned plane U i Is transparent to light, A (U) i ) Is unmanned plane U i Selected angle of view, A (U i ) Obtained by the following formula.
A(U i )=…+∠P n-1 +∠P n +∠P n+1 +…。
Wherein, is less than P n-1 、∠P n Sum +.P n+1 Are angles of view having the same number of obstacles and adjacent to each other; angle P n-1 、∠P n Sum +.P n+1 Are all taken from the total field angle range [ -pi/3, 4 pi/3]。
Alternatively, the phototactic model is shown in the following formula.
。
Wherein,is the light transmittance of unmanned aerial vehicle Ui, a (U i ) The angle of view selected for the unmanned aerial vehicle Ui, λ is a distance factor and e is a natural constant.
Unmanned aerial vehicle Ui selected field angle a (U i ) Obtained by the following formula.
A(U i )=…+∠P n-1 +∠P n +∠P n+1 +…。
Wherein, is less than P n-1 、∠P n Sum +.P n+1 Are the angles of view of the same number of obstacles and adjacent to each other; angle P n-1 、∠P n Sum +.P n+1 A split angle of view, which are all the total angle of view; the total angle of view is in the range of [ -pi/3, 4 pi/3]The total angle of view is equally divided into five separate angles of view { angle P 1 ,∠P 2 ,∠P 3 ,∠P 4 ,∠P 5 }。
The distance factor lambda is shown in the following equation.
。
Wherein delta M Representing the distance factor adjustment coefficient, delta, of a drone located in the middle B The distance factor adjusting coefficient of the boundary unmanned aerial vehicle is represented, B is a set of the boundary unmanned aerial vehicle, the boundary unmanned aerial vehicle is an unmanned aerial vehicle with at least one partial view angle being not shielded, and the middle unmanned aerial vehicle is an unmanned aerial vehicle with all the partial view angles being shielded.
Optionally, the phototactic obstacle avoidance model includes an inter-machine phototactic obstacle avoidance sub-model and an machine obstacle phototactic obstacle avoidance sub-model.
The model of the intersymbol phototactic obstacle avoidance is shown in the following formula.
。
Wherein,is the first light transmission control coefficient.
The model of the obstacle-avoiding phototaxis obstacle-avoiding sub-model is shown in the following formula.
。
Wherein,is the second light transmission control coefficient.
Optionally, the phototactic obstacle avoidance control law is as shown in the following formula.
。
Wherein,the unmanned aerial vehicle is marked with i, ∇ is a deviation-solving symbol, a ij Adjacency matrix of communication topology for unmanned aerial vehicle formation, +.>Speed p of obstacle denoted by k j The speed of the unmanned aerial vehicle is denoted by j, and c is a control coefficient; n (N) i (t) neighbor unmanned aerial vehicle set of unmanned aerial vehicles denoted by i, < ->A set of obstacles for the drone denoted i.
On the other hand, the invention also provides an unmanned aerial vehicle formation obstacle avoidance control system based on bird-like phototaxis, and the unmanned aerial vehicle formation obstacle avoidance control system based on bird-like phototaxis executes the unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototaxis when the unmanned aerial vehicle formation obstacle avoidance control system is operated by a computer.
According to the specific scheme provided by the invention, the following technical effects are disclosed.
The invention provides an unmanned aerial vehicle formation obstacle avoidance control method and system based on bird-like phototaxis, wherein the method comprises the following steps: acquiring the position and speed of each unmanned aerial vehicle, the position and speed of the surrounding barrier of each unmanned aerial vehicle and the position of the target object at the current moment; aiming at any unmanned aerial vehicle, a phototactic obstacle avoidance model which is pre-established according to the characteristic of combining the artificial potential field model with the phototactic flight of birds is utilized, and according to the current time, the position and the speed of the unmanned aerial vehicle, the position and the speed of each unmanned aerial vehicle adjacent to the unmanned aerial vehicle, the position and the speed of each obstacle around the unmanned aerial vehicle and the position of a target object, the phototactic obstacle avoidance control law of the unmanned aerial vehicle is obtained; and then updating a control model of the unmanned aerial vehicle according to a phototactic obstacle avoidance control law to obtain the speed and the position of the unmanned aerial vehicle at the next moment. Compared with the means for cluster control based on the traditional potential field method, the artificial potential field method based on the bird phototactic characteristic improvement can better ensure that unmanned aerial vehicle formation can find a maneuver flight route and can not collide in the flight process, effectively overcomes the limitation of the traditional potential field method, and remarkably improves the obstacle avoidance performance of the unmanned aerial vehicle formation in complex and nondeterministic environments; the unmanned aerial vehicle formation controlled by the control method can effectively avoid obstacles in the flight process, realizes safe and reliable stable flight, provides reliable theoretical support for the actual flight of the large-scale unmanned aerial vehicle formation, and has wide application prospect.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of an unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototaxis provided in embodiment 1 of the invention.
Fig. 2 is a flowchart of constructing a phototactic obstacle avoidance model of unmanned aerial vehicle formation in the method provided in embodiment 1 of the present invention.
Fig. 3 is a schematic view angle diagram of the unmanned aerial vehicle in the method provided in embodiment 1 of the present invention.
Fig. 4 is a schematic diagram of distinguishing a boundary unmanned aerial vehicle from an intermediate unmanned aerial vehicle in the method provided in embodiment 1 of the present invention.
Fig. 5 is a schematic diagram of an unmanned aerial vehicle formation obstacle avoidance flight path in the method provided in embodiment 1 of the present invention.
Fig. 6 is a schematic diagram of the consistency of the unmanned aerial vehicle formation obstacle avoidance flight state in the method provided in embodiment 1 of the present invention.
Fig. 7 is a schematic structural diagram of an unmanned aerial vehicle formation obstacle avoidance control system based on bird-like phototaxis according to embodiment 2 of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide an unmanned aerial vehicle formation obstacle avoidance control method and system based on bird-like phototaxis, which improve the obstacle avoidance performance of unmanned aerial vehicle formation in complex and non-deterministic environments.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1.
The embodiment provides an unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototaxis, which can be applied to fixed-wing unmanned aerial vehicle formation, wherein the unmanned aerial vehicle formation comprises a plurality of unmanned aerial vehicles, and the method comprises the following steps of.
A1, acquiring the position and the speed of each unmanned aerial vehicle at the current moment, the position and the speed of each peripheral obstacle of each unmanned aerial vehicle at the current moment and the position of a target object.
A2, aiming at any unmanned aerial vehicle, utilizing a phototactic obstacle avoidance model formed by the unmanned aerial vehicle to obtain a phototactic obstacle avoidance control law of the unmanned aerial vehicle; the method specifically comprises the following steps: according to the position of the current moment of the unmanned aerial vehicle, the speed of the current moment of the unmanned aerial vehicle, the position of the current moment of each neighbor unmanned aerial vehicle of the unmanned aerial vehicle, the speed of each neighbor unmanned aerial vehicle of the unmanned aerial vehicle, the position of each obstacle around the unmanned aerial vehicle, the speed of each obstacle around the unmanned aerial vehicle and the position of a target object, combining the phototactic obstacle avoidance model of the unmanned aerial vehicle formation to obtain the phototactic obstacle avoidance control law of the unmanned aerial vehicle; the neighbor unmanned aerial vehicle is an unmanned aerial vehicle adjacent to the unmanned aerial vehicle in unmanned aerial vehicle formation.
Specifically, the phototactic obstacle avoidance model used in step A2 is a model obtained by combining an artificial potential field model of unmanned aerial vehicle formation with a phototactic model of unmanned aerial vehicle formation; the artificial potential field model is constructed according to the control model of each unmanned aerial vehicle in unmanned aerial vehicle formation; the phototactic model is a model which is established by simulating the characteristic of the bird phototactic flight.
A3, updating a control model of the unmanned aerial vehicle according to the phototactic obstacle avoidance control law to obtain the speed of the unmanned aerial vehicle at the next moment and the position of the unmanned aerial vehicle at the next moment. In this embodiment, the control model of the unmanned aerial vehicle is shown in formula (1).
（1）。
In the formula (1), n is the number of unmanned aerial vehicles in unmanned aerial vehicle formation, q i Is the position of the drone denoted i,a differential value for the position of the unmanned aerial vehicle denoted i; p is p i Speed of unmanned aerial vehicle denoted by i, < +.>A differential value of the speed of the unmanned aerial vehicle, numbered i; u (u) i Control input for unmanned aerial vehicle with reference number i, < >>Wherein->For the control input component of the linear speed of the unmanned aerial vehicle, numbered i, +.>For the control input component of the heading angle of the drone, denoted by i, T represents the transpose of the matrix.
The control model of the unmanned aerial vehicle is actually a second-order model based on speed and position control, and is obtained by performing model conversion on a two-dimensional simplified dynamic model of the unmanned aerial vehicle. The two-dimensional simplified dynamic model of the unmanned aerial vehicle is shown in a formula (2).
（2）。
In the formula (2), (x) i ,y i ) Is unmanned plane U i Position in inertial coordinate system, U i A drone denoted by reference numeral i;the course angle of the unmanned aerial vehicle; />And->The control vector is the unmanned plane control vector in the system plane; v i The linear speed of the unmanned aerial vehicle is represented by adding points to each parameter as differential values of the original parameter values.
It can be appreciated that, before step A2, the unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototactic provided in this embodiment further includes a process of constructing a phototactic obstacle avoidance model of unmanned aerial vehicle formation, such as a flowchart shown in fig. 2, and the process includes the following steps.
B1, constructing an artificial potential field model of unmanned aerial vehicle formation according to a control model of each unmanned aerial vehicle in the unmanned aerial vehicle formation; specifically, the unmanned aerial vehicle formation comprises a leading unmanned aerial vehicle and a plurality of following unmanned aerial vehicles; the artificial potential field model comprises potential field functions between any two unmanned aerial vehicles, potential field functions between the unmanned aerial vehicle and the obstacle, and potential field functions between the unmanned aerial vehicle and the navigation item; the navigation items are targets followed by the unmanned aerial vehicle, the navigation items leading the unmanned aerial vehicle are targets, and the navigation items following the unmanned aerial vehicle are leading the unmanned aerial vehicle.
The potential field function between any two unmanned aerial vehicles is shown as a formula (3).
（3）。
In the formula (3), the amino acid sequence of the compound,representing a potential field function between the unmanned aerial vehicle and the unmanned aerial vehicle, wherein alpha has no specific meaning, and only represents the potential field function to be the potential field function between the unmanned aerial vehicle and the unmanned aerial vehicle, and q i Representing the position, q, of the unmanned aerial vehicle denoted by i j Represents the position, q, of the unmanned aerial vehicle denoted by j ij Distance q between unmanned aerial vehicle with reference number i and unmanned aerial vehicle with reference number j ij =q i -q j (i. Noteq. J), d is the expected distance between the two unmanned aerial vehicles, I.I σ Is a non-negative smooth potential energy function used for constructing a space between two unmanned aerial vehicles, and the sigma norm is specifically expressed as +.>(κ>0) Kappa is a positive constant, w denotes the argument of sigma norm; />For the inter-machine obstacle avoidance function, s is an integral variable, ds represents integrating s, r α Is the attractive force distance of the unmanned plane. I d i σ In order to achieve the expected distance between any two unmanned aerial vehicles after non-negative smoothness, when the distance between the two unmanned aerial vehicles is kept as d|| σ The potential field function value of the term will tend to be minimal.
The inter-machine obstacle avoidance function is shown in formula (4).
（4）。
In the formula (4), z is a normal number, h α Independent variables representing the inter-machine obstacle avoidance function, eta epsilon (0, 1), and the value of eta determines the size of the obstacle avoidance function, and the value can be customized after comprehensive measurement according to the actual obstacle environment and the formation system.
The potential energy function designed by the formula (3) is satisfied.
When q ij || σ <And r, the potential field function value is a constant.
When q ij || σ <||d|| σ During the process, unmanned plane U is described i Unmanned plane U j 。
When d σ <||q ij || σ <r, description unmanned plane U i Suction unmanned plane U j 。
The potential field function between the drone and the obstacle is shown in equation (5).
（5）。
In the formula (5), the amino acid sequence of the compound,is a potential field function between the unmanned aerial vehicle and the obstacle, beta has no specific meaning, and only characterizes the potential field function as the potential field function between the unmanned aerial vehicle and the obstacle, < + >>Unmanned aerial vehicle and obstacle o, denoted by reference numeral i k Distance of->Representing obstacle o k K is the subscript of the obstacle, < ->，/>Is a barrier avoiding function of a machine barrier, r o As the rejection radius of the unmanned aerial vehicle, when the obstacle o k Outside the rejection radius of the drone, the potential field function value of this term will tend to be minimal.
The obstacle avoidance function of the machine is shown in a formula (6).
（6）。
In formula (6), h o Independent variables representing barrier avoidance functions.
The potential energy function designed by the formula (5) is satisfied.
When (when)At this time, the potential field function value tends to ≡.
When (when)During the time, unmanned aerial vehicle U i Away from the obstacle under the repulsive force.
The potential field function between the drone and the navigational terms is shown in equation (7).
（7）。
In the formula (7), the amino acid sequence of the compound,for the potential field function between the unmanned aerial vehicle and the navigation item, gamma has no specific meaning, and only characterizes the potential field function as the potential field function between the unmanned aerial vehicle and the navigation item, q it =q i -q t -q r ，q it Distance q between unmanned aerial vehicle and navigation item denoted by i t Representing the position of the navigation item, q r The expected distance between the unmanned aerial vehicle and the navigation item is set; when->The potential field function tends to 0 at this time.
B2, combining the characteristics of bird phototactic flight to establish a phototactic model of unmanned aerial vehicle formation; in this embodiment, the total angle of view is defined to be within the range of [ -pi/3, 4 pi/3]Uniformly dividing the angle of view into five divided angles of view { angle P with pi/3 as interval 1 ,∠P 2 ,∠P 3 ,∠P 4 ,∠P 5 See fig. 3. And (3) judging the light transmittance intensity in each divided view angle, and selecting the view angle direction with the strongest light transmittance to fly.When the flight path has a plurality of field angles with the same light transmission intensity, the field angle direction with the smallest included angle with the speed direction is selected for flight, so that the aim of minimizing the flight path cost is fulfilled.
The phototactic model is shown in formula (8) without considering the distance factor.
（8）。
In the formula (8), the amino acid sequence of the compound,is unmanned plane U i Is the light transmission of unmanned plane U i The probability falling into each of the divided angles of view is [ -pi/3, 4 pi/3]Is uniformly distributed over the interval, A (U) i ) Is unmanned plane U i Selected angle of view, a (U i ) Obtained by the formula (9).
A(U i )=…+∠P n-1 +∠P n +∠P n+1 +… （9）。
In formula (9), the angle P n-1 、∠P n Sum +.P n+1 Are the angles of view of the same number of obstacles and adjacent to each other.
And the phototactic model is shown in formula (10) after the distance factor is considered.
（10）。
In the formula (10), λ is a distance factor, e is a natural constant, and the distance factor λ is represented by the formula (11).
（11）。
In the formula (11), delta M Representing the distance factor adjustment coefficient, delta, of a drone located in the middle B Representing a distance factor adjustment coefficient of a boundary unmanned aerial vehicle, wherein B is a set of the boundary unmanned aerial vehicle, and is a boundary unmanned aerial vehicle clusterThe unmanned aerial vehicle is an unmanned aerial vehicle with at least one partial angle of view not being blocked, the unmanned aerial vehicle in the middle is an unmanned aerial vehicle with all partial angles of view being blocked, see fig. 4, in which +.P 1 ,∠P 2 ,∠P 3 ,∠P 4 ,∠P 5 Respectively representing 5 sub-field angles of the boundary unmanned plane; angle P 1 ’,∠P 2 ’,∠P 3 ’,∠P 4 ’,∠P 5 ' respectively denote the 5 split angles of view of the intermediate drone.
And B3, establishing a phototactic obstacle avoidance model of unmanned aerial vehicle formation based on the artificial potential field model and the phototactic model. In this embodiment, the phototactic obstacle avoidance model includes an inter-plane phototactic obstacle avoidance sub-model and an inter-plane obstacle avoidance sub-model, where only the potential field function between any two unmanned aerial vehicles, the potential field function between the unmanned aerial vehicle and the obstacle are combined with the phototactic model, since the phototactic model is mainly used for obstacle avoidance. The navigation item is used for guiding the unmanned aerial vehicle to fly to the target point, so that the potential field function between the unmanned aerial vehicle and the navigation item is not adjusted.
The intersymbol phototactic obstacle avoidance sub-model is shown in a formula (12).
（12）。
In the formula (12), the amino acid sequence of the compound,is the first light transmission control coefficient.
The machine obstacle phototaxis obstacle avoidance sub-model is shown in a formula (13).
（13）。
In the formula (13), the amino acid sequence of the compound,is a second light transmission control coefficient; through the combination of the phototactic models, the improved artificial potential field is directly related to the light transmittance of the unmanned aerial vehicle.
In step A2, the phototactic obstacle avoidance control law of the unmanned aerial vehicle obtained by using the phototactic obstacle avoidance model formed by the unmanned aerial vehicle is shown as formula (14).
（14）。
In the formula (14), the amino acid sequence of the compound,the unmanned aerial vehicle is marked with i, ∇ is a deviation-solving symbol, a ij Adjacency matrix of communication topology for unmanned aerial vehicle formation, +.>Speed p of obstacle denoted by k j Speed of unmanned aerial vehicle with reference number j, c is control coefficient, N i (t) neighbor unmanned aerial vehicle set of unmanned aerial vehicles denoted by i, < ->A set of obstacles for the drone denoted i.
Next, the unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototaxis provided by the embodiment is verified in a MATLAB environment, and the unmanned aerial vehicle safely and collision-free reaches a target point under the action of a designed control law by setting an obstacle environment and a target object position, so that the validity of a designed algorithm is verified, and the verification process is as follows.
And (3) verifying by adopting a formation system consisting of 5 unmanned aerial vehicles, wherein the communication topological structure of the formation system is shown as a formula (15).
（15）。
Matrix L 1 The numerical value of (2) is determined by the communication relation of unmanned aerial vehicle formation, wherein the element values on the diagonal line represent the communication entrance degree of unmanned aerial vehicles, the other non-diagonal line element values represent the communication condition between two unmanned aerial vehicles,this value is set to-1 when the ith unmanned aerial vehicle and the jth unmanned aerial vehicle are in communication.
Under the above communication relationship, the desired position distance between the first follower and the leader is set asSetting the distance between the expected positions of the second follower and the leader to be +.>Setting the distance between the expected positions of the third follower and the leader to be +.>Setting the desired position distance between the fourth follower and the leader to be +.>The method comprises the steps of carrying out a first treatment on the surface of the Control coefficient c=0.45. The simulation results are shown in fig. 5 and 6. In fig. 5, black circles are obstacles, five-pointed stars are formed flight target points, each line represents a flight path of a corresponding unmanned aerial vehicle, and the end points of each path are the starting point and the end point of the unmanned aerial vehicle respectively. Based on simulation results, under the action of the proposed phototactic model, unmanned aerial vehicles in formation can effectively avoid obstacles in the flight process, and safe and reliable stable flight is realized.
According to the unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototaxis, the traditional artificial potential field method is improved based on bird phototaxis, light transmittance is introduced into the artificial potential field method, and compared with the means of cluster control based on the traditional potential field method, the unmanned aerial vehicle formation obstacle avoidance control method can better ensure that unmanned aerial vehicle formation can find a movable flight route, collision can not occur in the flight process, and obstacle avoidance performance of unmanned aerial vehicle formation in complex and non-deterministic environments is remarkably improved; the unmanned aerial vehicle formation controlled by the control method provided by the embodiment can effectively avoid the obstacle in the flight process, realizes safe and reliable stable flight, provides reliable theoretical support for the actual flight of the large-scale unmanned aerial vehicle formation, and has wide application prospect.
Example 2.
In addition, the method of embodiment 1 of the present invention may also be implemented by means of the architecture of the unmanned aerial vehicle formation obstacle avoidance control system based on bird-like phototaxis shown in fig. 7. As shown in fig. 7, the unmanned aerial vehicle formation obstacle avoidance control system based on bird-like phototactic may include a data acquisition module M1, a control model construction module M2, a phototactic obstacle avoidance model construction module M3, a control law generation module M4, and an unmanned aerial vehicle control module M5; some modules may also have subunits for performing their functions, for example, an artificial potential field construction unit, a phototactic model construction unit, and a phototactic obstacle avoidance model construction unit are also included in phototactic obstacle avoidance model construction module M3. Of course, the architecture shown in fig. 7 is merely exemplary, and one or at least two components of the system shown in fig. 7 may be omitted as actually needed when implementing different functions.
Specific examples are employed herein, but the above description is merely illustrative of the principles and embodiments of the present invention, which are presented solely to aid in the understanding of the method of the present invention and its core ideas; it will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented by general-purpose computer means, alternatively they may be implemented by program code executable by computing means, whereby they may be stored in storage means for execution by computing means, or they may be made into individual integrated circuit modules separately, or a plurality of modules or steps in them may be made into a single integrated circuit module. The present invention is not limited to any specific combination of hardware and software.
Also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (9)
1. An unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototaxis comprises a plurality of unmanned aerial vehicles; the unmanned aerial vehicle formation obstacle avoidance control method is characterized by comprising the following steps of:
acquiring the position of each unmanned aerial vehicle at the current moment, the speed of each unmanned aerial vehicle at the current moment, the position of each obstacle around each unmanned aerial vehicle at the current moment, the speed of each obstacle around each unmanned aerial vehicle at the current moment and the position of a target object;
aiming at any unmanned aerial vehicle, utilizing a phototactic obstacle avoidance model formed by the unmanned aerial vehicle, and obtaining a phototactic obstacle avoidance control law of the unmanned aerial vehicle according to the position of the unmanned aerial vehicle at the current moment, the speed of the unmanned aerial vehicle at the current moment, the position of each neighbor unmanned aerial vehicle at the current moment, the speed of each obstacle around the unmanned aerial vehicle at the current moment and the position of a target object; the phototactic obstacle avoidance model is a model obtained by combining an artificial potential field model formed by the unmanned aerial vehicle and a phototactic model formed by the unmanned aerial vehicle; the neighbor unmanned aerial vehicle is an unmanned aerial vehicle adjacent to the unmanned aerial vehicle in unmanned aerial vehicle formation; the artificial potential field model is a model constructed according to a control model of each unmanned aerial vehicle in unmanned aerial vehicle formation; the phototactic model is a model which is built by simulating the characteristic of the phototactic flight of birds;
and updating the control model of the unmanned aerial vehicle according to the phototactic obstacle avoidance control law to obtain the speed of the unmanned aerial vehicle at the next moment and the position of the unmanned aerial vehicle at the next moment.
2. The unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototaxis according to claim 1, wherein the unmanned aerial vehicle control model is shown as follows:
；
wherein n is the number of unmanned aerial vehicles in unmanned aerial vehicle formation, q i Is the position of the drone denoted i,a differential value for the position of the unmanned aerial vehicle denoted i; p is p i Speed of unmanned aerial vehicle denoted by i, < +.>A differential value of the speed of the unmanned aerial vehicle, numbered i; u (u) i Control input for unmanned aerial vehicle with reference number i, < >>Wherein->For the control input component of the linear speed of the unmanned aerial vehicle, numbered i, +.>For the control input component of the heading angle of the drone, denoted by i, T represents the transpose of the matrix.
3. The unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototaxis according to claim 1, wherein the unmanned aerial vehicle formation comprises a leading unmanned aerial vehicle and a plurality of following unmanned aerial vehicles; the artificial potential field model comprises potential field functions between any two unmanned aerial vehicles, potential field functions between the unmanned aerial vehicle and an obstacle, and potential field functions between the unmanned aerial vehicle and a navigation item; the navigation items are targets followed by the unmanned aerial vehicle, the navigation items of the leading unmanned aerial vehicle are targets, and the navigation items of the following unmanned aerial vehicle are the leading unmanned aerial vehicle.
4. The unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototaxis according to claim 3, wherein a potential field function between any two unmanned aerial vehicles is shown as follows:
；
wherein,representing a potential field function between the unmanned aerial vehicle and the unmanned aerial vehicle, q i Representing the position, q, of the unmanned aerial vehicle denoted by i j Represents the position, q, of the unmanned aerial vehicle denoted by j ij Distance q between unmanned aerial vehicle with reference number i and unmanned aerial vehicle with reference number j ij =q i -q j (i. Noteq. J), d is the expected distance between the two unmanned aerial vehicles, I.I σ Is sigma norm ++>For the inter-machine obstacle avoidance function, s is an integral variable, ds represents integrating s, r α Is the attractive force distance of the unmanned plane;
the inter-machine obstacle avoidance function is shown in the following formula:
；
wherein z is a positive constant, eta is E (0, 1), h α Independent variables representing inter-machine obstacle avoidance functions;
the potential field function between the drone and the obstacle is shown as follows:
；
wherein,is a potential field function between the drone and the obstacle, < >>Unmanned aerial vehicle and obstacle o, denoted by reference numeral i k Distance of->Representing obstacle o k Is (are) located>，/>Is a barrier avoiding function of a machine barrier, r o Is the rejection radius of the unmanned aerial vehicle;
the obstacle avoidance function of the machine is shown as follows:
；
wherein h is o Independent variables representing barrier avoidance functions of the machine barrier;
the potential field function between the drone and the navigation term is shown as follows:
；
wherein,q is a potential field function between the unmanned aerial vehicle and the navigation term it Distance q between unmanned aerial vehicle and navigation item denoted by i t Representing the position of the navigation item, q r Is the desired separation of the drone from the navigation item.
5. The unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototactic according to claim 4, wherein the phototactic model is represented by the following formula:
；
wherein U is i Denoted by the reference numeral i is a drone,is unmanned plane U i Is transparent to light, A (U) i ) Is unmanned plane U i Selected angle of view, A (U i ) Obtained by the following formula:
A(U i )=…+∠P n-1 +∠P n +∠P n+1 +…；
wherein, is less than P n-1 、∠P n Sum +.P n+1 Are angles of view having the same number of obstacles and adjacent to each other; angle P n-1 、∠P n Sum +.P n+1 Are all taken from the total field angle range [ -pi/3, 4 pi/3]。
6. The unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototactic according to claim 4, wherein the phototactic model is represented by the following formula:
；
wherein,is the light transmittance of unmanned aerial vehicle Ui, a (U i ) The method comprises the steps that a field angle is selected for an unmanned aerial vehicle Ui, lambda is a distance factor, and e is a natural constant;
unmanned aerial vehicle Ui selected field angle a (U i ) Obtained by the following formula:
A(U i )=…+∠P n-1 +∠P n +∠P n+1 +…；
wherein, is less than P n-1 、∠P n Sum +.P n+1 Are the angles of view of the same number of obstacles and adjacent to each other; angle P n-1 、∠P n Sum +.P n+1 A split angle of view, which are all the total angle of view; the total angle of view is in the range of [ -pi/3, 4 pi/3]The total view angle is equally divided into five divided view angles { angle P 1 ,∠P 2 ,∠P 3 ,∠P 4 ,∠P 5 }；
The distance factor λ is shown as follows:
；
wherein delta M The representation is located inDistance factor adjustment coefficient delta of unmanned aerial vehicle B The distance factor adjusting coefficient of the boundary unmanned aerial vehicle is represented, B is a set of the boundary unmanned aerial vehicle, the boundary unmanned aerial vehicle is an unmanned aerial vehicle with at least one partial view angle being not shielded, and the middle unmanned aerial vehicle is an unmanned aerial vehicle with all the partial view angles being shielded.
7. The unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototactic according to any one of claims 5 to 6, wherein the phototactic obstacle avoidance model comprises an inter-aircraft phototactic obstacle avoidance model and an aircraft obstacle phototactic obstacle avoidance model;
the intersymbol phototactic obstacle avoidance sub-model is shown in the following formula:
；
wherein,is a first light transmission control coefficient;
the machine obstacle phototaxis obstacle avoidance sub-model is shown in the following formula:
；
wherein,is the second light transmission control coefficient.
8. The unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototaxis according to claim 7, wherein the phototaxis obstacle avoidance control law is represented by the following formula:
；
wherein,the unmanned aerial vehicle is marked with i, ∇ is a deviation-solving symbol, a ij Adjacency matrix of communication topology for unmanned aerial vehicle formation, +.>Speed p of obstacle denoted by k j The speed of the unmanned aerial vehicle is denoted by j, and c is a control coefficient; n (N) i (t) neighbor unmanned aerial vehicle set of unmanned aerial vehicles denoted by i, < ->A set of obstacles for the drone denoted i.
9. An unmanned aerial vehicle formation obstacle avoidance control system based on bird-like phototaxis, wherein the unmanned aerial vehicle formation obstacle avoidance control system based on bird-like phototaxis performs the unmanned aerial vehicle formation obstacle avoidance control method based on bird-like phototaxis as set forth in any one of claims 1-8 when operated by a computer.
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