CN109460064A - Unmanned plane cluster regions covering method and its device based on virtual potential field function - Google Patents
Unmanned plane cluster regions covering method and its device based on virtual potential field function Download PDFInfo
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Abstract
This application discloses a kind of unmanned plane cluster regions covering method and its device based on virtual potential field function, comprising the following steps: target area Geometric center coordinates are calculated by convex polygon target area apex coordinate first；Then it according to region apex coordinate, Geometric center coordinates, unmanned plane Absolute position measurement value, the relative position measurements of unmanned plane relative proximity unmanned plane, calculates virtual attraction function and repels function；Finally, decision unmanned plane uses different sports rules by judging whether unmanned plane enters target area, lasting covering of the unmanned plane cluster to region is realized.This method can make unmanned plane cluster form lasting covering to any Convex Polygon Domain, and unmanned plane is evenly distributed in region, compared to traditional area coverage method, have the advantages that control calculation amount is small, information processing capacity is few, overlay area various shapes.On the other hand the application additionally provides a kind of device that this method is used.
Description
Technical field
This application involves a kind of unmanned plane cluster regions covering method and its device based on virtual potential field function, belong to nothing
Man-machine clustered control technical field.
Background technique
The covering of unmanned plane cluster regions, refers to that the detectivity of each frame unmanned plane in the cluster can cover certain face
It under the premise of product, is cooperated using multiple UAVs, each point in target area is made at least to detect model by a frame unmanned plane
Enclose covering.Due to the robustness of group system, scale elasticity and flexibility, cluster regions covering extensively, is applied to search
It rescues, transport the fields such as building, landform search, mapping, formation and sensor network disposition.
In summary application scenario is it can be found that the application scenarios of cluster regions covering have the following characteristics that 1) needs are fast
Speed deployment unmanned plane node；2) region shape for needing to cover is irregular；3) not necessarily as the unmanned aerial vehicle platform of clustered node
So has global communication ability；4) environmental hazard, unmanned plane node should have autonomous deployment ability.
With the maturation of unmanned aerial vehicle platform technology, unmanned plane cluster using more and more extensive, to unmanned plane cluster regions
The research of covering problem also becomes the hot spot of unmanned plane industry and educational circles's concern.
Region overlay problem is used as system-level behavior in multiple mobile node system, earliest by scholar Gage in 2005
It proposes, region overlay problem is divided into 3 classes by him: blanket type covering, obstacle type cover and clean formula and cover.Some scholars are by region
Covering problem is divided into: lasting covering and two classes of non-continuous covering.
Non-continuous covering only requires that each point in target area was once inswept by a mobile node, without requiring always
It is capped, it is usually used in area research, searches and rescues generic task, the mobile node negligible amounts being related to, and usually using path planning
Method solve.
Lasting covering refers to that each point moment is in the coverage area of at least one mobile node in region, is suitble to area
Domain persistently monitors and constructing communication network generic task.
Have at present to region overlay solution to the problem: the non-continuous covering scheme of task based access control planning utilizes fixation
The covering scheme of response lag model and applied probability analysis method, is based on cluster grouping and area at distributed collaboration covering scheme
Allocation overlay scheme, the covering scheme using beacon network auxiliary, the covering part management side based on artificial fish-swarm algorithm of domain division
Case, the covering scheme based on particle swarm algorithm and Voronoi diagram, wireless sensor deployment scheme based on cat swarm optimization etc..
But currently based on the document of optimization algorithm there is no research how each mobile node of coordinated control can
The scheme for moving to target position, and considering node motion control does not consider that individual investigative range and communication range are limited
Under the conditions of lasting covering problem, the region covered is also usually regular figure, is not able to satisfy the needs of practical application.
Summary of the invention
According to the one aspect of the application, a kind of unmanned plane cluster regions covering side based on virtual potential field function is provided
Method, this method can make unmanned plane cluster form lasting covering to any Convex Polygon Domain, and unmanned plane is distributed in region
Uniformly, compared to traditional area coverage method, have that control calculation amount is small, information processing capacity is few, overlay area various shapes
Advantage, the engineer application for unmanned plane in area monitoring field provide effective scheme.
The unmanned plane cluster regions covering method based on virtual potential field function, which comprises the following steps:
Step S100: obtaining the relative position of each the unmanned plane real-time absolute position and relative proximity unmanned plane, according to
The geometric center of target area to be covered and the target area, calculate separately the geometric center in real time in cluster it is each nobody
The virtual attraction function F of machineO, the target area boundaries are in real time to the virtual repulsion function F of unmanned planeL, calculate it is each it is described nobody
Virtual repulsion function between machine individual
Step S200: judging whether each real-time absolute position of the unmanned plane is in the target area, is judged
As a result；
Step S300: if the judging result be it is yes, according to the virtual repulsion function FL, the virtual repulsion letter
NumberEach unmanned plane is controlled to be moved by sports rule in the target area, if the judging result be it is no,
According to the virtual attraction function FO, the virtual repulsion functionEach unmanned plane is controlled to transport outward by the target area
Dynamic rule is moved, and judges whether enter stable state after each unmanned aerial vehicle (UAV) control；
Step S400: the finishing control if into stable state；
The return step S100 if not entering into stable state.
Preferably, " control " described in the step S300 is that need to use movement velocity according to unmanned planeIt controls each described
Unmanned plane physical location XiVariation.
Preferably, when " judging result is yes ", then unmanned plane in the target area, which is calculated as follows, need to use movement
Speed
Wherein, M is the quantity of neighbouring unmanned plane around unmanned plane；
Preferably, when " judging result is no ", then unmanned plane outside the target area, which is calculated as follows, need to use movement
Speed
Wherein, M is the quantity of neighbouring unmanned plane around unmanned plane.
Preferably, the target area is convex polygon.
Preferably, in the step S100 the following steps are included:
Step S110: determining the apex coordinate of the target area to be covered, is calculated according to the apex coordinate described several
What centre coordinate；
Step S120: by the Geometric center coordinates P of the target area0(x0,y0) and the target area apex coordinate
Ω={ P1(x1,y1),P2(x2,y2),...,Pn(xn,yn), each unmanned plane being sent to as assignment instructions in cluster.
Preferably, " calculate the Geometric center coordinates " in the step S110 the following steps are included:
Step S111: the geometric area A of the target area is calculated as follows:
Wherein, (xk,yk) be the target area kth apex coordinate, (xk+1,yk+1) be the target area kth+1
Apex coordinate；
Step S112: the geometric center abscissa x of the target area is calculated as follows0With ordinate y0:
Step S113: the Geometric center coordinates P of the target area is calculated as follows0(x0,y0):
P0(x0,y0)=[x0,y0]T (4)。
Preferably, the virtual repulsion function between the unmanned plane is calculated as follows
Wherein, RijFor the relative position coordinates of relative proximity unmanned plane, RmaxIndicate any unmanned plane to other unmanned planes
It is farthest to influence distance, RminIndicate the nearest safe distance of any unmanned plane Yu other unmanned planes, G1To control gain.
Preferably, the geometric center is calculated as follows in real time to the virtual attraction function F of unmanned plane each in clusterO:
Wherein, G2To control gain, P0(x0,y0) be the target area Geometric center coordinates, XiIt is absolute for unmanned plane
Position coordinates.
Preferably, the target area boundaries are calculated in real time to the virtual repulsion function F of unmanned planeLThe following steps are included:
A) calculate separately as the following formula each unmanned plane to each boundary line in the target area intersection point point coordinate
Wherein,Indicate the abscissa of unmanned plane absolute position,Indicate the abscissa of unmanned plane absolute position,Indicate the intersection point abscissa of kth target area boundaries line,Indicate that the intersection point of kth target area boundaries line is vertical
Coordinate is note that (xk,yk) be the target area kth apex coordinate, (xk+1,yk+1) be the target area+1 vertex of kth
Coordinate；
B) be calculated as follows each unmanned plane to target area each boundary line intersection point distance
Wherein, XiFor unmanned plane absolute location coordinates；
Obtain the unmanned plane to the target area boundaries the shortest distanceAnd its corresponding intersection point coordinate
C) the repulsion function F apart from nearest zone boundary to unmanned plane is calculated as followsL:
Wherein, G3To control gain, L is the allowable minimum distance on unmanned plane distance areas boundary.
According to the another aspect of the application, a kind of unmanned plane cluster regions covering based on virtual potential field function is provided
Device, comprising:
Function computation module, for obtaining the opposite position of each unmanned plane real-time absolute position and relative proximity unmanned plane
It sets, according to the geometric center of target area to be covered and the target area, calculates separately the geometric center in real time to cluster
In each unmanned plane virtual attraction function FO, the target area boundaries are in real time to the virtual repulsion function F of unmanned planeL, calculate it is each
Virtual repulsion function between the unmanned plane individual
First judgment module, for judging whether each real-time absolute position of the unmanned plane is in the target area,
Obtain judging result；
Second judgment module, if for the judging result be it is yes, according to the virtual repulsion function FL, the void
It is quasi- to repel functionIt controls each unmanned plane to be moved by sports rule in the target area, if the judgement is tied
Fruit be it is no, then according to the virtual attraction function FO, the virtual repulsion functionEach unmanned plane is controlled by the target
Sports rule is moved outside region, and judges whether enter stable state after each unmanned aerial vehicle (UAV) control；
Steady-state module, for the finishing control if into stable state；The function meter is returned if not entering into stable state
Calculate module.
The beneficial effect that the application can generate includes:
1) the unmanned plane cluster regions covering method provided herein based on virtual potential field function, for it is practical nobody
Machine platform detection range and the limited problem of communication distance, in conjunction with mimicry physics method and Agent system rule of conduct method,
The collision avoidance, region attraction and boundary exclusion rule of multiple no-manned plane system are devised, and attracts and repel virtual potential field function.
2) the unmanned plane cluster regions covering method provided herein based on virtual potential field function, in virtual potential field letter
Under the action of several and sports rule, unmanned plane cluster can be made to enter inside target area by autonomous control, be formed to any
The gapless of convex polygon target area persistently covers, and unmanned plane has uniform pattern inside region.
3) the unmanned plane cluster regions covering method provided herein based on virtual potential field function is applicable not only to each
Class unmanned plane cluster, and particularly suitable for the biggish unmanned plane clustered control of quantity size.
4) the unmanned plane cluster regions covering method provided herein based on virtual potential field function, Zhi Xu earth station to
Unmanned plane cluster broadcast once command, each unmanned aerial vehicle platform can independent calculating need to use movement velocity, realize cluster
Distributed freedom control, avoid the intercommunication occupied bandwidth resource of unmanned plane, the failure of individual unmanned planes in cluster
The function of other unmanned planes will not be influenced with loss, to be able to achieve the scale elasticity of cluster.
5) the unmanned plane cluster regions covering method provided herein based on virtual potential field function, can be to target area
Non-blind area covering is realized in domain, is avoided valuable information in blind area of monitoring and is missed, improves unmanned plane cluster regions monitoring system
Application performance.
6) the unmanned plane cluster regions covering method provided herein based on virtual potential field function, can be in target area
Equally distributed covering configuration is formed in domain, reduces the repeat monitoring degree in target area, it being capable of effectively save unmanned plane
Platform resource reduces unmanned plane quantity needed for completing monitor task.
7) the unmanned plane cluster regions covering method provided herein based on virtual potential field function, can be to any convex
Polygonal region realizes lasting covering, improves the task compatibility of unmanned plane cluster, extends the monitoring of unmanned plane cluster regions
Systematic difference range.
8) the unmanned plane cluster regions covering method provided herein based on virtual potential field function, without in cluster
Unmanned plane be numbered, the movement of unmanned plane individual is only dependent upon assignment instructions and its autonomous exploration to link around, increase
The strong robustness of group system.
Detailed description of the invention
Fig. 1 is the unmanned plane cluster regions covering method process based on virtual potential field function in a kind of embodiment of the application
Schematic diagram；
Fig. 2 is the herein described unmanned plane cluster regions covering method flow chart of steps based on virtual potential field；
Fig. 3 is herein described unmanned plane position coordinates system and target area parameter definition；
Fig. 4 is the schematic diagram of target area in herein described embodiment；
Fig. 5 is the initial deployment figure of unmanned plane cluster in herein described embodiment, wherein the cross mark of label " 0 "
Note represents unmanned plane initial position, divides and is in four vertex；
Fig. 6 be in herein described embodiment unmanned plane cluster to the motion profile figure during region overlay, wherein mark
The cross phenotypic marker of note " 0 " represents unmanned plane initial position, divides and is in four vertex, and the cross phenotypic marker of label " 1 " represents
The cross of " 0 " is marked in convex 5 side shape frame using the first stable position locating for unmanned plane after the control of the application providing method
Line between phenotypic marker and the cross phenotypic marker for marking " 1 " is the motion profile of each unmanned plane；
Fig. 7 is to expect unmanned plane cluster to the stable state configuration picture of region overlay in herein described embodiment, wherein cross
Phenotypic marker represents unmanned plane cluster and reaches each unmanned plane position after the first stable state；
Fig. 8 is the region overlay configuration picture in herein described embodiment after individual unmanned plane losses, wherein label " 1 "
Cross phenotypic marker represent the first stable position of unmanned plane；
Fig. 9 is the motion profile figure that remaining unmanned plane again covers region in herein described embodiment, wherein
The cross phenotypic marker of label " 1 " represents the first stable position of unmanned plane, and the cross phenotypic marker of label " 2 " is represented when 10 framves in cluster
After unmanned plane is fallen, unmanned plane reaches present position after the second stable state after being controlled using the application providing method, marks the ten of " 1 "
The cross line of font and label " 2 " indicates motion profile；
Figure 10 is that remaining unmanned plane carries out covering stable state configuration picture to region again in herein described embodiment, wherein
The cross phenotypic marker of label " 2 " is represented using present position when unmanned plane reaches the second stable state after the control of the application providing method；
Figure 11 be in herein described embodiment in unmanned plane cluster coverage goal region process with neighbouring unmanned plane most
Small spacing average statistical and statistical variance；
Figure 12 be in herein described embodiment unmanned plane cluster again in coverage goal region process with neighbouring unmanned plane
Minimum spacing average statistical and statistical variance；
Figure 13 is the unmanned plane cluster regions cladding system based on virtual potential field function in a kind of embodiment of the application
Structural schematic diagram；
Marginal data:
P1(x1,y1),P2(x2,y2),...,Pn(xn,yn) be convex polygon target area n vertex coordinate；
P0(x0,y0) be convex polygon target area Geometric center coordinates；
FOIt is geometric center to the virtual attraction function of unmanned plane；
FLIt is target area boundaries to the virtual repulsion function of unmanned plane；
For the virtual repulsion function between unmanned plane and neighbouring unmanned plane；
For unmanned plane needed velocity vector；
XiFor unmanned plane absolute location coordinates；
XjFor neighbouring unmanned plane absolute location coordinates；
RijFor the relative position coordinates of unmanned plane relative proximity unmanned plane.
Specific embodiment
The application is described in detail below with reference to embodiment, but the application is not limited to these embodiments.
Referring to Fig. 1, the unmanned plane cluster regions covering method provided by the present application based on virtual potential field function, including it is following
Step:
Step S100: according to given convex polygon target area apex coordinate { P1(x1,y1),P2(x2,y2),...,Pn
(xn,yn) calculate target area Geometric center coordinates P0(x0,y0), then according to target area Geometric center coordinates and nobody
Virtual attraction function F of the machine Absolute position measurement value computational geometry center to unmanned planeO；
Step S200: according to target area apex coordinate and unmanned plane Absolute position measurement value zoning boundary to nobody
The virtual repulsion function F of machineL, virtually repel letter between calculating individual according to the relative position measurements of unmanned plane and neighbour's unmanned plane
Number
Step S300: whether unmanned plane is judged according to target area apex coordinate and the calculating of unmanned plane Absolute position measurement value
Into target area；
Step S400: whether the judging result of target area is entered according to unmanned plane and geometric center attracts function FO, area
Virtually repel function F in domain boundaryL, individual between virtually repel functionCalculate the need movement velocity of unmanned planeAnd according to need
With the physical location X of movement velocity control unmanned aerial vehicle platformi。
Since the unmanned plane cluster of this method control can be under conditions of being not necessarily to centerized fusion, only by each unmanned plane
The autonomous control of itself can be realized and cover to target area duration, and unmanned plane cluster distribution portion inside target area
Administration uniformly, compared to traditional area coverage method, is more suitable for skilled unmanned plane group system in large scale, is unmanned plane
The practical application of cluster provides effective scheme.
Unmanned plane cluster regions covering method of the application based on virtual potential field function:
Target area Geometric center coordinates are calculated by convex polygon target area apex coordinate first；
Then according to region apex coordinate, Geometric center coordinates, unmanned plane Absolute position measurement value, unmanned plane relative proximity
The relative position measurements of unmanned plane calculate virtual attraction function and repel function；
Finally, decision unmanned plane uses different sports rules by judging whether unmanned plane enters target area, realize
Lasting covering of the unmanned plane cluster to region.
In practical application, the Absolute position measurement value of unmanned plane is by global position system GPS location Calculation chip or GPS/
INS positioning system measurement obtains, and can also be determined by other navigation satellite positioning system GNSS location Calculation chips or GNSS/INS
Position systematic survey obtains.Unmanned plane is obtained adjacent to the relative position of unmanned plane by lidar measurement with respect to other, can also be by
Binocular visual positioning systematic survey obtains, and can also can realize that the measuring system of relative positioning obtains by other.Make in cluster
Each frame unmanned plane calculates in the method need to use movement velocity, and need to be transmitted what is be calculated by this method with movement velocity
To the control system of each frame unmanned plane, i.e., the movement of controllable unmanned plane cluster realizes unmanned plane cluster to target area
Covering.
Unmanned plane cluster regions covering method based on virtual potential field function, specific step is as follows, as shown in Figure 2:
Step 1: all apex coordinates of given target region Ω: P1(x1,y1), P2(x2,y2) ... ... Pn(xn,yn)；
The target region Ω is Convex Polygon Domain, as shown in figure 3, polygonal region can be unique with apex coordinate
It indicates, i.e. Ω={ P1(x1,y1),P2(x2,y2),...,Pn(xn,yn), in which: Pk(xk,yk)=[xk,yk]TFor apex coordinate,
xkIndicate k-th of vertex abscissa, ykIndicate k-th of vertex ordinate, n is number of vertices, and n >=3.
Step 2: target area Geometric center coordinates: P are calculated0(x0,y0)；
The calculating step of the target area centre coordinate are as follows:
Step 2.1: calculating target area geometric area A；
The calculation method of the target area geometric area is
Step 2.2: calculating the abscissa x of target area geometric center0With ordinate y0；
The abscissa x at the target area center0With ordinate y0Calculation method be
Step 2.3: calculating target area centre coordinate P0(x0,y0)；
The calculation method of the target area centre coordinate is
P0(x0,y0)=[x0,y0]T (4)
Step 3: by target area centre coordinate P0(x0,y0) and target area apex coordinate Ω={ P1(x1,y1),P2
(x2,y2),...,Pn(xn,yn), each frame unmanned plane being sent to as assignment instructions in cluster；
It is described Step 1: step 2 and step 3 earth station complete calculate, the earth station can be to be connected to number
Pass the computer of transmitter.Assignment instructions described in step 3 pass link by number and are transmitted on unmanned plane from earth station, nobody
It must be according to there is several transmitting/receiving modules on machine.
Step 4: unmanned plane obtains itself absolute location coordinates XiWith the relative position coordinates R of relative proximity unmanned planeij；
The absolute location coordinates X of the unmanned plane itselfiBy on unmanned plane GPS positioning module or GPS/INS positioning system
System provides, and can also be provided by other satellite navigation and positioning modules.
The neighbouring unmanned plane relative position RijIt is provided by lidar measurement or vision positioning system measurement, it can also be by
Other can realize that the measuring system of relative positioning provides.
If neighbouring unmanned plane absolute position is Xj, as shown in figure 3, then adjacent to unmanned plane relative position RijFor
Rij=Xi-Xj (5)
Step 5: the repulsion function between unmanned plane is calculatedRepulsion function F of the zone boundary to unmanned planeL, region it is several
Attraction function F of what center to unmanned planeO；
The calculation method of repulsion function between the unmanned plane is
Wherein, RmaxIndicate unmanned plane on the farthest influence distance of other unmanned planes, RminIndicate unmanned plane and other nobody
The nearest safe distance of machine, G1To control gain, determined by unmanned plane maximum flying speed.
The regional center is to the calculation method of the attraction function of unmanned plane
Wherein, G2To control gain, also determined by unmanned plane maximum flying speed.
The zone boundary calculates step to the repulsion function of unmanned plane are as follows:
Step 5.1: the intersection point point coordinate of calculating unmanned plane to each target area boundaries line
The intersection point coordinate of the target area boundaries lineCalculation method is
Wherein,Indicate the abscissa of unmanned plane absolute position,Indicate the abscissa of unmanned plane absolute position,Indicate the intersection point abscissa of kth target area boundaries line,Indicate that the intersection point of kth target area boundaries line is vertical
Coordinate, i.e. intersection point point coordinateNote that for target area apex coordinate xkAnd ykIf target area
There is n vertex in domain, then has xk+n=xk, yk+n=yk。
Step 5.2: the distance of calculating unmanned plane to each target area boundaries line intersection point
Distance of the unmanned plane to each target area boundaries line intersection pointCalculation method is
Step 5.3: find out unmanned plane to target area boundaries the shortest distanceAnd its corresponding intersection point coordinate
Step 5.4: calculating apart from nearest zone boundary to the repulsion function F of unmanned planeL；
Repulsion function F of the nearest zone boundary of distance to unmanned planeLCalculation method be
Wherein, G3For control gain, determined by unmanned plane maximum flying speed, L be unmanned plane distance areas boundary most
Small allowable distance.
Step 6: judging whether unmanned plane is located inside target area, if unmanned plane is in inside target area, adopts
Step 8 is used if unmanned plane is in outside target area with step 7；
Step 7: movement velocity need to be used by calculating unmanned plane in target area
Unmanned plane movement velocity in the step 7Calculation method be
Step 8: movement velocity need to be used by calculating unmanned plane outside target area
Unmanned plane movement velocity in the step 8Calculation method be
Particularly, in step 7 and step 8 parameter M be neighbouring unmanned plane around unmanned plane quantity, i.e., around unmanned plane
It is less than R with its distancemaxOther unmanned planes quantity.
Step 9: movement velocity need to be used according to unmanned planeControl unmanned plane physical location XiVariation；
It is real that existing unmanned aerial vehicle platform control method can be used in the method that unmanned plane physical location is controlled in the step 9
It is existing.
Step 10: judging whether unmanned plane movement enters stable state, if having entered stable state, otherwise finishing control returns
Step 4.
Particularly, if the monitoring orientation of unmanned aerial vehicle platform is to be farthest to monitor distance R using unmanned aerial vehicle platform as the center of circle
The disc area of radius, then unmanned plane is on the farthest influence distance R of other unmanned planes in step 5maxCalculation method be
The calculation method of the allowable minimum distance L on unmanned plane distance areas boundary is
L=0.5R (15)
Unmanned plane is calculated on the farthest influence distance R of other unmanned planes using formula (13)max, while being calculated using formula (14)
The allowable minimum distance L on unmanned plane distance areas boundary, it can be ensured that the monitoring area non-blind area of the covering of unmanned plane cluster.
Referring to Figure 13, the unmanned plane cluster regions cladding system provided by the present application based on virtual potential field function, comprising:
Function computation module, for obtaining the opposite position of each unmanned plane real-time absolute position and relative proximity unmanned plane
It sets, according to the geometric center of target area to be covered and the target area, calculates separately the geometric center in real time to cluster
In each unmanned plane virtual attraction function FO, the target area boundaries are in real time to the virtual repulsion function F of unmanned planeL, calculate it is each
Virtual repulsion function between the unmanned plane individual
First judgment module, for judging whether each real-time absolute position of the unmanned plane is in the target area,
Obtain judging result；
Second judgment module, if for the judging result be it is yes, according to the virtual repulsion function FL, the void
It is quasi- to repel functionIt controls each unmanned plane to be moved by sports rule in the target area, if the judgement is tied
Fruit be it is no, then according to the virtual attraction function FO, the virtual repulsion functionEach unmanned plane is controlled by the target
Sports rule is moved outside region, and judges whether enter stable state after each unmanned aerial vehicle (UAV) control；
Steady-state module, for the finishing control if into stable state；The function meter is returned if not entering into stable state
Calculate module.
Method provided by the present application is described in detail below in conjunction with specific example.
In embodiment the following steps are included:
Step 1: all apex coordinates of given target region Ω: P1(x1,y1), P2(x2,y2) ... ... Pn(xn,yn)；
The given convex polygon target area for having 5 vertex to constitute, target area apex coordinate are
P1(x1,y1)=[5,20]T, P2(x2,y2)=[8,12]T, P3(x3,y3)=[22,8]T,
P4(x4,y4)=[20,25]T, P5(x5,y5)=[9,30]T,
Target area boundaries surround region as shown in Figure 4, and target region Ω is
Step 2: target area Geometric center coordinates: P are calculated0(x0,y0)；
The calculating step of the target area centre coordinate are as follows:
Step 2.1: calculating target area geometric area A；
The calculated result of target area geometric area is
In the calculating for paying attention to formula (15), equation has been used
Step 2.2: calculating the abscissa x at target area center0With ordinate y0；
The abscissa x at target area center0With ordinate y0Calculated result be
Step 2.3: calculating target area centre coordinate P0(x0,y0)；
The calculated result of target area centre coordinate is
Step 3: by target area centre coordinate P0(x0,y0) and target area apex coordinate Ω={ P1(x1,y1),P2
(x2,y2),...,Pn(xn,yn), each frame unmanned plane being sent to as assignment instructions in cluster；
It is described Step 1: step 2 and step 3 earth station complete calculate, the earth station can be to be connected to number
Pass the computer of transmitter.Assignment instructions described in step 3 pass link by number and are transmitted on unmanned plane from earth station, nobody
Several transmitting/receiving modules are installed on machine.
Step 4: unmanned plane obtains itself absolute location coordinates XiWith the relative position coordinates R of relative proximity unmanned planeij；
The absolute location coordinates X of the unmanned plane itselfiBy on unmanned plane GPS positioning module or GPS/INS positioning system
System provides, and can also be provided by other satellite navigation and positioning modules；The neighbouring unmanned plane relative position RijBy lidar measurement
Or vision positioning system measurement provides, and can also can realize that the measuring system of relative positioning is provided by other.
Step 5: the repulsion function between unmanned plane is calculatedRepulsion function F of the zone boundary to unmanned planeL, region
Attraction function F of the geometric center to unmanned planeO；
The calculation method of repulsion function between unmanned plane is
In the present embodiment, unmanned plane is on the farthest influence distance R of other unmanned planesmax=3, unmanned plane and other unmanned planes
Nearest safe distance Rmin=2, control gain G1=10.
The regional center is to the calculation method of the attraction function of unmanned plane
In the present embodiment, gain G is controlled2=10.
The zone boundary calculates step to the repulsion function of unmanned plane are as follows:
Step 5.1: the intersection point point coordinate of calculating unmanned plane to each target area boundaries line
The intersection point coordinate of the target area boundaries lineCalculation method is
Wherein,Indicate the abscissa of unmanned plane absolute position,Indicate the abscissa of unmanned plane absolute position,Indicate the intersection point abscissa of kth target area boundaries line,Indicate that the intersection point of kth target area boundaries line is vertical
Coordinate, i.e. intersection point point coordinateNote that for target area apex coordinate xkAnd ykIf target area
There is n vertex in domain, then has xk+n=xk, yk+n=yk。
Step 5.2: the distance of calculating unmanned plane to each target area boundaries line intersection point
Distance of the unmanned plane to each target area boundaries line intersection pointCalculation method is
Step 5.3: find out unmanned plane to target area boundaries the shortest distanceAnd its corresponding intersection point coordinate
Step 5.4: calculating apart from nearest zone boundary to the repulsion function F of unmanned planeL；
Repulsion function F of the nearest zone boundary of distance to unmanned planeLCalculation method be
In the present embodiment, gain G is controlled3=10, the allowable minimum distance L=1 on unmanned plane distance areas boundary.
Step 6: judging whether unmanned plane is located inside target area, if unmanned plane is in inside target area, adopts
Step 8 is used if unmanned plane is in outside target area with step 7；
Step 7: movement velocity need to be used by calculating unmanned plane in target area
Unmanned plane movement velocity in the step 7Calculation method be
Step 8: movement velocity need to be used by calculating unmanned plane outside target area
Unmanned plane movement velocity in the step 8Calculation method be
Particularly, in step 7 and step 8 parameter M be neighbouring unmanned plane around unmanned plane quantity, i.e., around unmanned plane
It is less than R with its distancemaxOther unmanned planes quantity.
Step 9: movement velocity need to be used according to unmanned planeControl unmanned plane physical location XiVariation；
It is real that existing unmanned aerial vehicle platform control method can be used in the method that unmanned plane physical location is controlled in the step 9
It is existing.
Step 10: judging whether unmanned plane movement enters stable state, if having entered stable state, otherwise finishing control returns
Step 4.
In this example, it is assumed that unmanned aerial vehicle platform control system can without time delay, error-free control unmanned plane according to
Needed velocityThe actual motion of movement, i.e. hypothesis unmanned plane is determined according to formula (25) or formula (26).
In the present embodiment, unmanned plane cluster scale is 40 framves, is divided into 4 groups, every group of 10 frame unmanned planes, and initial position is random
It is distributed in
In four rectangular areas, as shown in figure 5,4 vertex Relatively centralizeds i.e. in rectangular area.
In the present embodiment, it controls gain and cluster spacing parameter value is shown in Table 1
Table 1 collects swarm parameter
| Parameter | Numerical value | Parameter | Numerical value |
| G1 | 10 | Rmin | 3 |
| G2 | 10 | Rmax | 2 |
| G3 | 10 | L | 1 |
Under the method control that the application proposes, the collective motion track in embodiment is as shown in Figure 6.Fig. 7 is using this
After applying for providing method control, the cluster that is formed covers configuration to target area after unmanned plane collective motion is stablized, at this time nobody
Machine cluster reaches the first stable state.
After considering unmanned plane motion stabilization, the 10 frame unmanned plane abortions in the upper right corner in target area, unmanned plane at this time
The distribution of cluster is as shown in Figure 8.Under the method control that the application proposes, remaining 30 frame unmanned plane restarts from principal part
Administration, collective motion track are as shown in Figure 9.Covering configuration such as Figure 10 institute that target area is formed after collective motion is stable again
Show.
In the present embodiment, during unmanned plane cluster enters target area and forms stable covering configuration, each nothing
The average statistical of minimum range and statistical variance change with time between man-machine, as shown in figure 11.It can be seen that the system of spacing
Convergence in the mean is counted to a fixed value, shows that the movement of unmanned plane cluster gradually tends towards stability；The statistical variance of spacing gradually subtracts
As low as 10-2Magnitude illustrates unmanned plane cluster in mesh hereinafter, illustrate that different unmanned planes are consistent with the pitch area of its neighbour's unmanned plane
Distribution in mark region gradually becomes uniform.
In the present embodiment, remaining unmanned plane autonomous deployment re-forms stabilization after individual unmanned plane losses in target area
During covering configuration, the average statistical of minimum range and statistical variance change with time between each unmanned plane, such as Figure 12
It is shown.It can be seen that the average statistical of spacing converges to a new fixed value again, show that unmanned plane cluster restarts to transport
It moves and is intended to a new stable state；The statistical variance of spacing continues to be decreased to 10-3Magnitude hereinafter, illustrate remaining unmanned plane with
The spacing of its neighbour's unmanned plane restarts to reach unanimity, and illustrates that distribution of the unmanned plane cluster in target area tends to be equal again
It is even.
This example demonstrates that unmanned plane cluster can form target area and uniformly hold using the application providing method
Continuous covering demonstrates the validity, scale elasticity and independence of the cluster regions covering method that the application is proposed.
The above is only several embodiments of the application, not does any type of limitation to the application, although this Shen
Please disclosed as above with preferred embodiment, however not to limit the application, any person skilled in the art is not taking off
In the range of technical scheme, a little variation or modification are made using the technology contents of the disclosure above and is equal to
Case study on implementation is imitated, is belonged in technical proposal scope.
Claims (10)
1. a kind of unmanned plane cluster regions covering method based on virtual potential field function, which comprises the following steps:
Step S100: the relative position of each the unmanned plane real-time absolute position and relative proximity unmanned plane is obtained, according to wait cover
The geometric center of lid target area and the target area calculates separately the geometric center in real time to unmanned plane each in cluster
It is virtual to attract function FO, the target area boundaries are in real time to the virtual repulsion function F of unmanned planeL, calculate each unmanned plane
Virtual repulsion function between body
Step S200: judging whether each real-time absolute position of the unmanned plane is in the target area, obtains judging result；
Step S300: if the judging result be it is yes, according to the virtual repulsion function FL, the virtual repulsion function
It controls each unmanned plane to be moved by sports rule in the target area, if the judging result is no, basis
The virtual attraction function FO, the virtual repulsion functionEach unmanned plane is controlled by moving rule outside the target area
It is then moved, and judges whether enter stable state after each unmanned aerial vehicle (UAV) control；
Step S400: the finishing control if into stable state；
The return step S100 if not entering into stable state.
2. the unmanned plane cluster regions covering method according to claim 1 based on virtual potential field function, which is characterized in that
" control " described in the step S300 is that need to use movement velocity according to unmanned planeControl each unmanned plane physical location Xi
Variation.
3. the unmanned plane cluster regions covering method according to claim 2 based on virtual potential field function, which is characterized in that
When " judging result is yes ", then unmanned plane in the target area, which is calculated as follows, need to use movement velocity
Wherein, M is the quantity of neighbouring unmanned plane around unmanned plane；
Preferably, when " judging result is no ", then unmanned plane outside the target area, which is calculated as follows, need to use movement velocity
Wherein, M is the quantity of neighbouring unmanned plane around unmanned plane.
4. the unmanned plane cluster regions covering method according to claim 1 based on virtual potential field function, which is characterized in that
The target area is convex polygon.
5. the unmanned plane cluster regions covering method according to claim 1 based on virtual potential field function, which is characterized in that
In the step S100 the following steps are included:
Step S110: determining the apex coordinate of the target area to be covered, is calculated in the geometry according to the apex coordinate
Heart coordinate；
Step S120: by the Geometric center coordinates P of the target area0(x0,y0) and the target area apex coordinate Ω=
{P1(x1,y1),P2(x2,y2),...,Pn(xn,yn), each unmanned plane being sent to as assignment instructions in cluster.
6. the unmanned plane cluster regions covering method according to claim 5 based on virtual potential field function, which is characterized in that
" calculate the Geometric center coordinates " in the step S110 the following steps are included:
Step S111: the geometric area A of the target area is calculated as follows:
Wherein, (xk,yk) be the target area kth apex coordinate, (xk+1,yk+1) be the target area+1 vertex of kth
Coordinate；
Step S112: the geometric center abscissa x of the target area is calculated as follows0With ordinate y0:
Step S113: the Geometric center coordinates P of the target area is calculated as follows0(x0,y0):
P0(x0,y0)=[x0,y0]T (4)。
7. the unmanned plane cluster regions covering method according to claim 1 based on virtual potential field function, which is characterized in that
The virtual repulsion function between the unmanned plane is calculated as follows
Wherein, RijFor the relative position coordinates of relative proximity unmanned plane, RmaxIndicate any unmanned plane to the farthest of other unmanned planes
Influence distance, RminIndicate the nearest safe distance of any unmanned plane Yu other unmanned planes, G1To control gain.
8. the unmanned plane cluster regions covering method according to claim 1 based on virtual potential field function, which is characterized in that
The geometric center is calculated as follows in real time to the virtual attraction function F of unmanned plane each in clusterO:
Wherein, G2To control gain, P0(x0,y0) be the target area Geometric center coordinates, XiFor unmanned plane absolute position
Coordinate.
9. the unmanned plane cluster regions covering method according to claim 1 based on virtual potential field function, which is characterized in that
The target area boundaries are calculated in real time to the virtual repulsion function F of unmanned planeLThe following steps are included:
A) calculate separately as the following formula each unmanned plane to each boundary line in the target area intersection point point coordinate
Wherein,Indicate the abscissa of unmanned plane absolute position,Indicate the abscissa of unmanned plane absolute position,Table
Show the intersection point abscissa of kth bar target area boundaries line,Indicate the intersection point ordinate note of kth target area boundaries line
Meaning, (xk,yk) be the target area kth apex coordinate, (xk+1,yk+1) be the target area+1 apex coordinate of kth；
B) be calculated as follows each unmanned plane to target area each boundary line intersection point distance
Wherein, XiFor unmanned plane absolute location coordinates；
Obtain the unmanned plane to the target area boundaries the shortest distanceAnd its corresponding intersection point coordinate
C) the repulsion function F apart from nearest zone boundary to unmanned plane is calculated as followsL:
Wherein, G3To control gain, L is the allowable minimum distance on unmanned plane distance areas boundary.
10. a kind of unmanned plane cluster regions cladding system based on virtual potential field function characterized by comprising
Function computation module, for obtaining the relative position of each unmanned plane real-time absolute position and relative proximity unmanned plane,
According to the geometric center of target area to be covered and the target area, the geometric center is calculated separately in real time to each in cluster
The virtual attraction function F of unmanned planeO, the target area boundaries are in real time to the virtual repulsion function F of unmanned planeL, calculate it is each described
Virtual repulsion function between unmanned plane individual
First judgment module is obtained for judging whether each real-time absolute position of the unmanned plane is in the target area
Judging result；
Second module, if for the judging result be it is yes, according to the virtual repulsion function FL, the virtual repulsion letter
NumberEach unmanned plane is controlled to be moved by sports rule in the target area, if the judging result be it is no,
According to the virtual attraction function FO, the virtual repulsion functionEach unmanned plane is controlled to transport outward by the target area
Dynamic rule is moved, and judges whether enter stable state after each unmanned aerial vehicle (UAV) control；
Steady-state module, for the finishing control if into stable state；The function is returned if not entering into stable state calculates mould
Block.
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