CN104536454A - Space-time synchronization matching method used for double unmanned aerial vehicle cooperation - Google Patents

Abstract

The invention discloses a space-time synchronization matching method used for double unmanned aerial vehicle cooperation. According to the method, cooperation costs from the current node to all expandable nodes of each unmanned aerial vehicle are calculated according to a defined double unmanned aerial vehicle cooperation cost function, the expandable node with the lowest cooperation cost is selected as an expandable flight track node, and therefore current flight track sections of double unmanned aerial vehicles are obtained. The double unmanned aerial vehicle cooperation cost function overcomes the defect that in an existing method, a cost function only considers flight track planning constrain conditions of a single unmanned aerial vehicle, in this way, double unmanned aerial vehicle synchronization is added in the process of generating flight track points, and the method is closer to the real process. Flight tracks of the double unmanned aerial vehicles are divided into flight track sections, time cooperation is converted into a flight track cost which is embedded into the cost function of flight track section planning of each unmanned aerial vehicle, time deviation and flight track conflicts when the double unmanned aerial vehicles reach flight track section nodes are eliminated, and the problem that in the prior art, flight track planning and task cooperation are separated, and influences on flight track planning by space-time synchronization are not considered is solved.

Description

A kind of space-time synchronous matching process collaborative for two unmanned plane

Technical field

The present invention relates to unmanned systems field, specifically described is a kind of space-time synchronous matching process collaborative for two unmanned plane.

Background technology

Unmanned plane is as a kind of emerging reconnaissance means, important supplement is provided for having people's reconnaissance plane and reconnaissance satellite, in execution reconnaissance mission process, unmanned plane has unique advantage: (1) unmanned plane can be detained in overhead, appointed area, carries out long-term continuing scouting of spiraling.(2) unmanned plane during flying track is changeable, and not easily tracked, viability is strong.(3) high-altitude flight unmanned plane is less by the impact of physical environment etc., and detection accuracy is high, information transmission time delay is little.(4) unmanned plane tasks carrying advantage of lower cost, and can higher information be obtained, efficiency-cost ratio is high.Therefore, the demand adopting single rack and multiple UAVs lift-launch different task load to perform the tasks such as scouting, supervision and earth observation constantly increases.Under more and more higher mission requirements, the effect of multiple no-manned plane mission planning also shows especially day by day.

The object of multiple no-manned plane mission planning is according to unmanned plane load performance and mission requirements, reasonably distributes, play the effect of useful load to greatest extent to unmanned plane, and the overall efficiency guaranteed to fulfil a task is optimum.For multiple no-manned plane mission planning problem, expand a lot of relevant research both at home and abroad.The autonomy of ARPA (DARPA) mixing ACTIVE CONTROL project of forming into columns explores new monitoring and controlling means to realize the control that relatively less operating personnel form into columns to extensive unmanned battle platform, emphasis solution multitask decomposition and assignment problem.Multiple no-manned plane coordinated investigation mission planning problem is considered as the multiple traveling salesmen problem with time window by the people such as Ryan in the literature, and gives the method for solving of tabu search algorithm.The researchist of the colleges and universities such as the National University of Defense technology, Northwestern Polytechnical University establishes unmanned plane cotasking plan model respectively, and proposes corresponding optimization method.But, in above-mentioned research, all simplification process is carried out to the constraint condition of unmanned plane practical flight and planning tasks target, avoid the complicacy of real problems, the applicability of method and validity is caused to decline, theoretically modeling and analysis are carried out to collaborative task in addition, lack analysis probabilistic in cotasking.In the tasks carrying of unmanned plane reality, be subject to the impact of the factor such as meteorological condition, UAV Flight Control condition, the spatio-temporal synergy of multiple UAVs exists uncertain, namely the time and space Complete Synchronization accomplishing multiple UAVs is difficult to, bring very large difficulty therefore to multiple UAVs formation control and tight coupling tasks carrying, also become the difficulties of multiple no-manned plane task cooperation.

Summary of the invention

Technical matters to be solved by this invention is: provide a kind of space-time synchronous matching process collaborative for two unmanned plane, time deviation and flight path conflict that two unmanned plane arrives flight path section node can be cleared up, arrive impact point, for two unmanned plane formation control and two unmanned plane tight coupling tasks carryings with strong space constraint requirement provide space-time synchronous means within the time interval short as far as possible simultaneously.

Technical scheme of the present invention is:

For the space-time synchronous matching process that two unmanned plane is collaborative, described pair of unmanned plane comprises unmanned plane UAV-A and unmanned plane UAV-B, it is characterized in that, definition unmanned aerial vehicle flight path section (T _i, T _i+1) corresponding two unmanned planes work in coordination with cost function: cost (T _i, T _i+1) be collaborative cost, T _ifor present node, T _i+1for expanding node; C _p, p=1,2 ..., 7 is current flight path section (T _i, T _i+1) minimum flight path cost function, λ _p, p=1,2 ..., 7 is the cost coefficient that each minimum flight path cost function is corresponding, L (T _i, T _i+1) be current flight path section (T _i, T _i+1) collaborative voyage cost function, α is the cost coefficient of collaborative voyage cost;

The concrete steps of the space-time synchronous matching process of working in coordination with for two unmanned plane are as follows:

(1) the flight path section starting point A of unmanned plane UAV-A is obtained ₁, terminal A _kand constraint condition needed for trajectory planning, obtain the flight path section starting point B of unmanned plane UAV-B ₁, terminal B _kand constraint condition needed for trajectory planning, make loop variable i=1;

(2) unmanned plane UAV-A current flight path node A is calculated _iextended node (X ₁, X ₂..., X _n); Calculate the current flight path Node B of unmanned plane UAV-B _iextended node (Y ₁, Y ₂..., Y _m);

(3) cost function calculation unmanned plane UAV-A current flight path node A is worked in coordination with according to two unmanned planes of definition _ito all extended node (X ₁, X ₂..., X _n) collaborative cost cost (A _i, X ₁), cost (A _i, X ₂) ..., cost (A _i, X _n); The extended node of selecting coordinated Least-cost is as unmanned plane UAV-A current flight path node A _iexpansion flight path node A _i+1; Corresponding collaborative cost is cost (A _i, A _i+1), obtain the current flight path section of unmanned plane UAV-A for (A _i, A _i+1);

Work in coordination with cost function calculation according to two unmanned planes of definition and calculate the current flight path Node B of unmanned plane UAV-B _ito all extended node (Y ₁, Y ₂..., Y _m) collaborative cost cost (B _i, Y ₁), cost (B _i, Y ₂) ..., cost (B _i, Y _m); The extended node of selecting coordinated Least-cost is as the current flight path Node B of unmanned plane UAV-B _iexpansion flight path Node B _i+1, corresponding collaborative cost is cost (B _i, B _i+1), obtain the current flight path section of unmanned plane UAV-B for (B _i, B _i+1);

(4) judging whether the current flight path section of unmanned plane UAV-A and unmanned plane UAV-B meets safe distance with non-crossing constraint condition, if do not met safe distance with non-crossing constraint condition, proceeding to step (5); If meet safe distance with non-crossing constraint condition, proceed to step (6);

(5) the current flight path section of unmanned plane UAV-A (A is compared _i, A _i+1) and the current flight path section of unmanned plane UAV-B (B _i, B _i+1) collaborative cost size;

If the current flight path section of unmanned plane UAV-B (B _i, B _i+1) collaborative cost comparatively large, retain unmanned plane UAV-A current flight path node A _iexpansion flight path node A _i+1, add the list of unmanned plane UAV-A flight path; Reselect the extended node of the secondary little unmanned plane UAV-B of collaborative cost as expansion flight path Node B _i+1, obtain the current flight path section of unmanned plane UAV-B for (B _i, B _i+1), then proceed to step (4);

If unmanned plane UAV-A is current flight path (A _i, A _i+1) collaborative cost comparatively large, retain the current flight path Node B of unmanned plane UAV-B _iexpansion track points B _i+1, add the list of unmanned plane UAV-B flight path; Reselect the extended node of the secondary little unmanned plane UAV-A of collaborative cost as expansion flight path node A _i+1, obtain the current flight path section of unmanned plane UAV-A for (A _i, A _i+1), proceed to step (4);

(6) the current expansion flight path node A of UAV-A is retained _i+1, add the list of UAV-A flight path; Retain the expansion flight path Node B that UAV-B is current _i+1, add the list of UAV-B flight path; Be current flight path node by expansion flight path node updates, even i increases by 1;

(7) judging whether to meet trajectory planning termination condition, if do not met, proceeding to step (2); If meet, then terminate.

It is as follows with the method for non-crossing constraint condition that described step (4) judges whether unmanned plane UAV-A and unmanned plane UAV-B current flight path section meet safe distance:

Calculate track intersection parameter R,

$R=(\stackrel{\→}{(A_i,A_{i+1})}\×\stackrel{\→}{(B_i,B_{i+1})})\·(\stackrel{\→}{(A_i,B_{i+1})}\×\stackrel{\→}{(B_i,A_{i+1})})$

Calculate flight path safe distance parameter Q,

$Q=(\stackrel{\→}{(A_i+\mathrm{Ds},A_{i+1}+\mathrm{Ds})}\×\stackrel{\→}{(B_i,B_{i+1})})\·(\stackrel{\→}{(A_i+\mathrm{Ds},B_{i+1})}\×\stackrel{\→}{(B_i,A_{i+1}+\mathrm{Ds})})$

If RQ<0, then think and meet safe distance with non-crossing constraint condition, if RQ >=0, then not think and meet safe distance with non-crossing constraint condition.

This trajectory planning termination condition is for arriving flight path segment endpoint.

C ₁for minimum flight path segment length cost:

C ₁＝min(l _j)

L _j, j=1 ..., N ₁for a jth optional flight path segment length, N ₁for optional flight path section number; l _j>=l _min, l _minfor minimum flight path segment length;

C ₂for maximum turning angle cost:

$C_2=\frac{\mathrm{\&pi;}}{2}-\arccos \left(\frac{a_i^T{a}_{i+1}}{\left|\right|a_i\left|\right|\left|\right|a_{i+1}\left|\right|}\right)$

A _i=(Tx _i+1-Tx _i, Ty _i+1-Ty _i) ^t, (Tx _i, Ty _i) be present node T _iprojected position coordinate, (Tx _i+1, Ty _i+1) be expanding node projected position coordinate, || a _i|| be vector a _imould; And meet for the maximum permission turning angle of unmanned plane;

C ₃for target approach axis cost:

C ₃＝min(η _j)

η _j, j=1 ..., N ₃for a jth optional approach axis angle, N ₃for the sum at optional approach axis angle; η _j≤ Φ, Φ are maximum permission approach axis angle.

C ₄for maximum/dive angle cost of climbing:

$C_4=\arctan \left(\frac{|{\mathrm{Tz}}_{i+1}-{\mathrm{Tz}}_i|}{\left|\right|a_i\left|\right|}\right)$

Tz _ifor present node T _ielevation, Tz _i+1for expanding node T _i+1elevation; And meet θ is the maximum permission underriding/angle of climb of unmanned plane;

C ₅for the longest voyage cost:

C ₅＝min(∑d _j)

D _j, j=1 ..., N ₅for from starting point to present node T _ijth optional voyage, N ₅for optional voyage sum; And meet ∑ d _j≤ D _mzx, D _mzxfor the longest distance;

C ₆for flying height cost:

C ₆＝min(H _j)

H _j, j=1 ..., N ₆for a jth optional minimum terrain clearance altitude, N ₆for optional minimum terrain clearance altitude sum; And meet H _min≤ H _j≤ H _max, H _minfor minimum flight altitude restriction, H _maxfor the highest flying height restriction;

C ₇for distance threatens district's cost:

C ₇＝min(W _j)

W _j, j=1 ..., N ₇threaten offset from, N recently for jth is optional ₇for optional threaten recently offset from sum.

L(T _i,T _i+1)＝|(L _Ti+L _Ti+1)-L _q|

L _tifor present node T _ithe voyage of reaching home, L _ti+1for expanding node T _i+1the voyage of reaching home, L _qfor collaborative voyage.

Collaborative voyage L _qdifferent according to the formula that the difference of unmanned plane during flying flight path dimension adopts.Voyage is worked in coordination with for one dimension, L _q=k ₁.max{D ₁, D ₂, k ₁for air line distance coefficient, max{D ₁, D ₂be the maximum linear distance of two unmanned plane apart from terminal.Voyage is worked in coordination with for two dimension, L _q=k ₂.max{D ₁, D ₂, k ₂for two-dimentional Euclidean distance coefficient; Max{D ₁, D ₂be the maximum two-dimentional Euclidean distance of two unmanned plane apart from terminal.Voyage is worked in coordination with for three-dimensional, L _q=k ₃.max{D ₁, D ₂, k ₃for three-dimensional Euclidean distance coefficient, max{D ₁, D ₂be the maximum three-dimensional Euclidean distance of two unmanned plane apart from terminal.

Voyage is worked in coordination with for one dimension, L _q=k ₁.max{D ₁, D ₂, k ₁for air line distance coefficient, max{D ₁, D ₂be the maximum linear distance of two unmanned plane apart from terminal.

Voyage is worked in coordination with for two dimension, L _q=k ₂.max{D ₁, D ₂, k ₂for two-dimentional Euclidean distance coefficient; Max{D ₁, D ₂be the maximum two-dimentional Euclidean distance of two unmanned plane apart from terminal.

Voyage is worked in coordination with for three-dimensional, L _q=k ₃.max{D ₁, D ₂, k ₃for three-dimensional Euclidean distance coefficient, max{D ₁, D ₂be the maximum three-dimensional Euclidean distance of two unmanned plane apart from terminal.

The required constraint condition of described unmanned aerial vehicle flight path planning comprises the minimum flight path segment length l of unmanned plane _min, maximum permission turning angle maximum permission underriding/angle of climb θ, the longest track distance D _mzx, minimum flight altitude restriction H _min, the highest flying height restriction H _maxwith flight safety distance Ds.

The present invention's advantage is compared with prior art:

(1) the present invention works in coordination with on the basis of track distance at two unmanned plane, propose two unmanned plane space-time synchronous and work in coordination with cost function, work in coordination with flight path point spread for two unmanned plane and provide foundation, compensate for the deficiency that cost function in existing method only considers single unmanned aerial vehicle flight path plan constraint condition, track points generative process is made to add the synchronous of two unmanned plane, closer to real processes.

(2) two unmanned plane flight path is separately divided into flight path section by the present invention; time coordination being converted into flight path cost is embedded in the cost function of single unmanned aerial vehicle flight path section planning; achieve time deviation and flight path conflict resolution that two unmanned plane arrives flight path section node; solve trajectory planning and task cooperation in prior art to be separated, do not consider that space-time synchronous is on problems such as the impacts of trajectory planning.The present invention provides space-time synchronous means for two unmanned plane formation control and the two unmanned plane tight coupling tasks carryings with strong space constraint requirement.

Accompanying drawing explanation

Fig. 1 is a kind of space-time synchronous matching process process flow diagram collaborative for two unmanned plane of the present invention;

Fig. 2 is the present invention's many flight paths section space-time synchronous schematic diagram.

Embodiment

The present invention proposes the collaborative cost function of two unmanned plane present node to expanding node first, and the collaborative cost function defined both had needed the constraint condition containing the planning of single unmanned aerial vehicle flight path, the two synchronous requirement of unmanned plane of demand fulfillment again.The judgement of two unmanned plane being worked in coordination with to cost is increased in expanding node selection course, time deviation and flight path conflict resolution that two unmanned plane arrives flight path section node can be realized, solve trajectory planning and task cooperation in prior art to be separated, do not consider that space-time synchronous is on problems such as the impacts of trajectory planning.

Definition unmanned aerial vehicle flight path section (T _i, T _i+1) corresponding two unmanned planes work in coordination with cost function and be

$\cos t(T_i,T_{i+1})=\underset{p=1}{\overset{7}{\mathrm{\&Sigma;}}}{\mathrm{\&lambda;}}_p{C}_p+\mathrm{\&alpha;L}(T_i,T_{i+1})---\left(1\right)$

Cost (T _i, T _i+1) be collaborative cost, T _ifor present node, T _i+1for expanding node;

The definition of the collaborative cost function in formula (1) comprises unmanned plane minimum flight path cost and collaborative voyage cost two parts.Minimum flight path cost mainly contains the constraint condition of single unmanned aerial vehicle flight path planning, and collaborative voyage cost mainly meets two synchronous requirement of unmanned plane.C _p(p=1,2 ..., 7) and be current flight path (T _i, T _i+1) minimum flight path cost function, λ _p, p=1,2 ..., 7 is the cost coefficient of each cost, L (T _i, T _i+1) be current flight path (T _i, T _i+1) collaborative voyage cost function, α is the cost coefficient of collaborative voyage cost.Such as, for specific unmanned plane, each coefficient can get following value, (λ ₁, λ ₂..., λ ₇, α)=(0.5,0.7,0.2,0.5,0.7,0.3,0.2,0.6).

Concrete cost function is as follows:

C ₁for minimum flight path segment length cost:

C ₁＝min(l _j) (2)

In formula (2), l _j, j=1 ..., N ₁for a jth optional flight path segment length, N ₁for optional flight path section number; l _j>=l _min, l _minfor minimum flight path segment length.

C ₂for maximum turning angle cost:

$C_2=\frac{\mathrm{\&pi;}}{2}-\arccos \left(\frac{a_i^T{a}_{i+1}}{\left|\right|a_i\left|\right|\left|\right|a_{i+1}\left|\right|}\right)---\left(3\right)$

In formula (3), a _i=(Tx _i+1-Tx _i, Ty _i+1-Ty _i) ^t, (Tx _i, Ty _i) be present node T _iprojected position coordinate, (Tx _i+1, Ty _i+1) be expanding node projected position coordinate, || a _i|| be vector a _imould.And meet for the maximum permission turning angle of unmanned plane.

C ₃for target approach axis cost:

C ₃＝min(η _j) (4)

In formula (4), η _j, j=1 ..., N ₃for a jth optional approach axis angle, N ₃for the sum at optional approach axis angle; η _j≤ Φ, Φ are maximum permission approach axis angle.

C ₄for maximum/dive angle cost of climbing:

$C_4=\arctan \left(\frac{|{\mathrm{Tz}}_{i+1}-{\mathrm{Tz}}_i|}{\left|\right|a_i\left|\right|}\right)---\left(5\right)$

In formula (5), Tz _ifor present node T _ielevation, Tz _i+1for expanding node T _i+1elevation.And meet θ is the maximum permission underriding/angle of climb of unmanned plane.

C ₅for the longest voyage cost:

C ₅＝min(∑d _j) (6)

In formula (6), d _j, j=1 ..., N ₅for from starting point to present node T _ijth optional voyage, N ₅for optional voyage sum.And meet ∑ d _j≤ D _mzx, D _mzxfor the longest distance, calculated by unmanned plane safe flight fuel load and determine or limit tasks carrying time of arrival to determine.

C ₆for flying height cost:

C ₆＝min(H _j) (7)

In formula (7), H _j, j=1 ..., N ₆for a jth optional minimum terrain clearance altitude, N ₆for optional minimum terrain clearance altitude sum.And meet H _min≤ H _j≤ H _max, H _minfor minimum flight altitude restriction, H _maxfor the highest flying height restriction.

C ₇for distance threatens district's cost:

C ₇＝min(W _j) (8)

In formula (8), W _j, j=1 ..., N ₇threaten offset from, N recently for jth is optional ₇for optional threaten recently offset from sum.

L (T _i, T _i+1) be collaborative voyage cost:

L(T _i,T _i+1)＝|(L _Ti+L _Ti+1)-L _q| (9)

In formula (9), L _tifor present node T _ithe voyage of reaching home, L _ti+1for expanding node T _i+1the voyage of reaching home, L _qfor collaborative voyage.

Collaborative voyage L _qdifferent according to the formula that the difference of unmanned plane during flying flight path dimension adopts.Voyage is worked in coordination with for one dimension, L _q=k ₁.max{D ₁, D ₂, k ₁for air line distance coefficient, max{D ₁, D ₂be the maximum linear distance of two unmanned plane apart from terminal.Voyage is worked in coordination with for two dimension, L _q=k ₂.max{D ₁, D ₂, k ₂for two-dimentional Euclidean distance coefficient; Max{D ₁, D ₂be the maximum two-dimentional Euclidean distance of two unmanned plane apart from terminal.Voyage is worked in coordination with for three-dimensional, L _q=k ₃.max{D ₁, D ₂, k ₃for three-dimensional Euclidean distance coefficient, max{D ₁, D ₂be the maximum three-dimensional Euclidean distance of two unmanned plane apart from terminal.

Wherein, one dimension works in coordination with Modeling for Distance Calculation of Airline speed, but precision is on the low side; The collaborative Modeling for Distance Calculation of Airline speed of two dimension is slower than one dimension, but precision is higher, is applicable to the level altitude unmanned plane that cruises and calculates; Three-dimensional collaborative Modeling for Distance Calculation of Airline speed is slower than two dimension, but precision is the highest, is applicable to complicated air environment And of Varying Depth unmanned plane and calculates.

As shown in Figure 1, a kind of space-time synchronous matching process collaborative for two unmanned plane of the present invention, concrete steps are as follows:

(1) initiation parameter of unmanned plane is obtained.

Before two unmanned plane takes off, initialized object is for the enforcement of method prepares.Obtain the flight path section starting point A of unmanned plane UAV-A ₁, terminal A _kand constraint condition needed for trajectory planning; Obtain the flight path section starting point B of unmanned plane UAV-B ₁, terminal B _kand constraint condition needed for trajectory planning.

The required constraint condition of described unmanned aerial vehicle flight path planning comprises the minimum flight path segment length l of unmanned plane _min, maximum permission turning angle maximum permission underriding/angle of climb θ, the longest track distance D _mzx, minimum flight altitude restriction H _min, the highest flying height restriction H _max, flight safety distance Ds etc.

(2) determine two unmanned plane current flight path node separately, calculate the extended node of current flight path node.

Determine unmanned plane UAV-A current flight path node A _i, calculate whole extended node (X of current flight path node ₁, X ₂..., X _n); Determine the current flight path Node B of unmanned plane UAV-B _i, calculate the extended node (Y of current flight path node ₁, Y ₂..., Y _m).

When not considering impassability region, in 8 neighborhood grids, n, m are all less than or equal to 8; In 24 neighborhood grids, n, m are all less than or equal to 24.

Determine that the method for extended node is including, but not limited to A* algorithm, sparse A* algorithm, the pseudo-spectrometry of Gauss, the pseudo-spectrometry of adaptive Gauss etc., see document " unmanned flight's control technology and engineering ", (Zeng Qinghua, Guo Zhenyun compile, National Defense Industry Press publishes, and 2011.8).

(3) work in coordination with the collaborative cost of cost function calculation each unmanned plane present node to all extended nodes according to two unmanned planes of definition, the extended node of selecting coordinated Least-cost, as expansion flight path node, obtains two current flight path section of unmanned plane.

Calculate unmanned plane UAV-A present node A _ito whole n extended node (X ₁, X ₂..., X _n) collaborative cost function cost (A _i, X ₁) ..., cost (A _i, X _j) ..., cost (A _i, X _n), the extended node of selecting coordinated Least-cost is as expansion flight path node A _i+1; Corresponding collaborative cost is cost (A _i, A _i+1), obtain the current flight path section of unmanned plane UAV-A for (A _i, A _i+1) _.

Calculate unmanned plane UAV-B current node B _ito whole m extended node (Y ₁, Y ₂..., Y _m) collaborative cost function cost (B _i, Y ₁) ..., cost (B _i, Y _k) ..., cost (B _i, Y _m), the extended node of selecting coordinated Least-cost is as expansion flight path Node B _i+1, corresponding collaborative cost is cost (B _i, B _i+1), obtain the current flight path section of unmanned plane UAV-B for (B _i, B _i+1).

(4) judge whether two current flight path of unmanned plane meets safe distance with non-crossing constraint condition, if do not met constraint condition, proceeds to step (5), otherwise proceeds to step (6);

As shown in Figure 2, be the present invention's many flight paths section space-time synchronous schematic diagram.Judge the current flight path (A of UAV-A _i, A _i+1) and the current flight path (B of UAV-B _i, B _i+1) nearest safe distance and track intersection; Ds is flight safety distance.

Calculate track intersection parameter R, then

$R=(\stackrel{\&RightArrow;}{(A_i,A_{i+1})}\&times;\stackrel{\&RightArrow;}{(B_i,B_{i+1})})\&CenterDot;(\stackrel{\&RightArrow;}{(A_i,B_{i+1})}\&times;\stackrel{\&RightArrow;}{(B_i,A_{i+1})})---\left(11\right)$

Calculate flight path safe distance parameter Q, then

$Q=(\stackrel{\&RightArrow;}{(A_i+\mathrm{Ds},A_{i+1}+\mathrm{Ds})}\&times;\stackrel{\&RightArrow;}{(B_i,B_{i+1})})\&CenterDot;(\stackrel{\&RightArrow;}{(A_i+\mathrm{Ds},B_{i+1})}\&times;\stackrel{\&RightArrow;}{(B_i,A_{i+1}+\mathrm{Ds})})---\left(12\right)$

In formula (11), (12), → be vector from flight path section origin-to-destination.If RQ<0, then two flight paths meet safe distance with non-crossing constraint, otherwise do not meet constraint.

(5) retain the less expansion flight path node of collaborative cost, delete the expansion flight path node that collaborative cost is larger, reselect corresponding expansion node as expansion flight path node, proceed to step (4).

The relatively current flight path section of unmanned plane UAV-A (A _i, A _i+1) and the current flight path section of unmanned plane UAV-B (B _i, B _i+1) collaborative cost size;

If the current flight path section of unmanned plane UAV-B (B _i, B _i+1) collaborative cost comparatively large, retain unmanned plane UAV-A current flight path node A _iexpansion flight path node A _i+1; Reselect the extended node of the secondary little unmanned plane UAV-B of collaborative cost as expansion flight path Node B _i+1, obtain the current flight path section of unmanned plane UAV-B for (B _i, B _i+1), then proceed to step (4);

If unmanned plane UAV-A is current flight path (A _i, A _i+1) collaborative cost comparatively large, retain the current flight path Node B of unmanned plane UAV-B _iexpansion track points B _i+1; Reselect the extended node of the secondary little unmanned plane UAV-A of collaborative cost as expansion flight path node A _i+1, obtain the current flight path section of unmanned plane UAV-A for (A _i, A _i+1), proceed to step (4);

(6) preserve two unmanned plane current flight path section separately, expanding node is updated to present node.

Retain the expansion flight path node A that UAV-A is current _i+1, add the list of UAV-A flight path; Retain the expansion flight path Node B that UAV-B is current _i+1, add the list of UAV-B flight path; Be current flight path node by expansion flight path node updates, even i increases by 1;

(7) judging whether to meet trajectory planning termination condition, if do not met, proceeding to step (2), otherwise terminate simultaneously match process.

Judge whether UAV-A and UAV-B meets trajectory planning termination condition, this condition is generally and arrives flight path segment endpoint or provided separately by unmanned plane cotasking, as trajectory planning termination condition is satisfied, export the collaborative flight path of UAV-A and UAV-B, simultaneously match process terminates.

The above; be only the embodiment of the best of the present invention, but protection scope of the present invention is not limited thereto, is anyly familiar with those skilled in the art in the technical scope that the present invention discloses; the change that can expect easily or replacement, all should be encompassed within protection scope of the present invention.

The content that instructions of the present invention is not described in detail belongs to professional and technical personnel in the field's known technology.

Claims (9)

1. for the space-time synchronous matching process that two unmanned plane is collaborative, described pair of unmanned plane comprises unmanned plane UAV-A and unmanned plane UAV-B, it is characterized in that, definition unmanned aerial vehicle flight path section (T _i, T _i+1) corresponding two unmanned planes work in coordination with cost function: cost (T _i, T _i+1) be collaborative cost, T _ifor present node, T _i+1for expanding node; C _p, p=1,2 ..., 7 is current flight path section (T _i, T _i+1) minimum flight path cost function, λ _p, p=1,2 ..., 7 is the cost coefficient that each minimum flight path cost function is corresponding, L (T _i, T _i+1) be current flight path section (T _i, T _i+1) collaborative voyage cost function, α is the cost coefficient of collaborative voyage cost;

The concrete steps of the space-time synchronous matching process of working in coordination with for two unmanned plane are as follows:

(1) the flight path section starting point A of unmanned plane UAV-A is obtained ₁, terminal A _kand constraint condition needed for trajectory planning, obtain the flight path section starting point B of unmanned plane UAV-B ₁, terminal B _kand constraint condition needed for trajectory planning, make loop variable i=1;

(2) unmanned plane UAV-A current flight path node A is calculated _iextended node (X ₁, X ₂..., X _n); Calculate the current flight path Node B of unmanned plane UAV-B _iextended node (Y ₁, Y ₂..., Y _m);

(3) cost function calculation unmanned plane UAV-A current flight path node A is worked in coordination with according to two unmanned planes of definition _ito all extended node (X ₁, X ₂..., X _n) collaborative cost cost (A _i, X ₁), cost (A _i, X ₂) ..., cost (A _i, X _n); The extended node of selecting coordinated Least-cost is as unmanned plane UAV-A current flight path node A _iexpansion flight path node A _i+1; Corresponding collaborative cost is cost (A _i, A _i+1), obtain the current flight path section of unmanned plane UAV-A for (A _i, A _i+1);

Work in coordination with cost function calculation according to two unmanned planes of definition and calculate the current flight path Node B of unmanned plane UAV-B _ito all extended node (Y ₁, Y ₂..., Y _m) collaborative cost cost (B _i, Y ₁), cost (B _i, Y ₂) ..., cost (B _i, Y _m); The extended node of selecting coordinated Least-cost is as the current flight path Node B of unmanned plane UAV-B _iexpansion flight path Node B _i+1, corresponding collaborative cost is cost (B _i, B _i+1), obtain the current flight path section of unmanned plane UAV-B for (B _i, B _i+1);

(4) judging whether the current flight path section of unmanned plane UAV-A and unmanned plane UAV-B meets safe distance with non-crossing constraint condition, if do not met safe distance with non-crossing constraint condition, proceeding to step (5); If meet safe distance with non-crossing constraint condition, proceed to step (6);

(5) the current flight path section of unmanned plane UAV-A (A is compared _i, A _i+1) and the current flight path section of unmanned plane UAV-B (B _i, B _i+1) collaborative cost size;

If the current flight path section of unmanned plane UAV-B (B _i, B _i+1) collaborative cost comparatively large, retain unmanned plane UAV-A current flight path node A _iexpansion flight path node A _i+1, add the list of unmanned plane UAV-A flight path; Reselect the extended node of the secondary little unmanned plane UAV-B of collaborative cost as expansion flight path Node B _i+1, obtain the current flight path section of unmanned plane UAV-B for (B _i, B _i+1), then proceed to step (4);

If unmanned plane UAV-A is current flight path (A _i, A _i+1) collaborative cost comparatively large, retain the current flight path Node B of unmanned plane UAV-B _iexpansion track points B _i+1, add the list of unmanned plane UAV-B flight path; Reselect the extended node of the secondary little unmanned plane UAV-A of collaborative cost as expansion flight path node A _i+1, obtain the current flight path section of unmanned plane UAV-A for (A _i, A _i+1), proceed to step (4);

(6) the current expansion flight path node A of UAV-A is retained _i+1, add the list of UAV-A flight path; Retain the expansion flight path Node B that UAV-B is current _i+1, add the list of UAV-B flight path; Be current flight path node by expansion flight path node updates, even i increases by 1;

(7) judging whether to meet trajectory planning termination condition, if do not met, proceeding to step (2); If meet, then terminate.

2. a kind of space-time synchronous matching process collaborative for two unmanned plane according to claim 1, it is characterized in that, it is as follows with the method for non-crossing constraint condition that described step (4) judges whether unmanned plane UAV-A and unmanned plane UAV-B current flight path section meet safe distance:

Calculate track intersection parameter R,

$R=(\stackrel{\&RightArrow;}{(A_i,A_{i+1})}\&times;\stackrel{\&RightArrow;}{(B_i,B_{i+1})})\&CenterDot;(\stackrel{\&RightArrow;}{(A_i,B_{i+1})}\&times;\stackrel{\&RightArrow;}{(B_i,A_{i+1})})$

Calculate flight path safe distance parameter Q,

$Q=(\stackrel{\&RightArrow;}{(A_i+\mathrm{Ds},A_{i+1}+\mathrm{Ds})}\&times;\stackrel{\&RightArrow;}{(B_i,B_{i+1})})\&CenterDot;(\stackrel{\&RightArrow;}{(A_i+\mathrm{Ds},B_{i+1})}\&times;\stackrel{\&RightArrow;}{(B_i,A_{i+1}+\mathrm{Ds})})$

If RQ<0, then think and meet safe distance with non-crossing constraint condition, if RQ >=0, then not think and meet safe distance with non-crossing constraint condition.

3. a kind of space-time synchronous matching process collaborative for two unmanned plane according to claim 1, is characterized in that, this trajectory planning termination condition is for arriving flight path segment endpoint.

4. a kind of space-time synchronous matching process collaborative for two unmanned plane according to claim 1, is characterized in that, C ₁for minimum flight path segment length cost:

C ₁＝min(l _j)

L _j, j=1 ..., N ₁for a jth optional flight path segment length, N ₁for optional flight path section number; l _j>=l _min, l _minfor minimum flight path segment length;

C ₂for maximum turning angle cost:

$C_2=\frac{\mathrm{\&pi;}}{2}-\arccos \left(\frac{a_i^T{a}_{i+1}}{\left|\right|a_i\left|\right|\left|\right|a_{i+1}\left|\right|}\right)$

A _i=(Tx _i+1-Tx _i, Ty _i+1-Ty _i) ^t, (Tx _i, Ty _i) be present node T _iprojected position coordinate, (Tx _i+1, Ty _i+1) be expanding node projected position coordinate, || a _i|| be vector a _imould; And meet for the maximum permission turning angle of unmanned plane;

C ₃for target approach axis cost:

C ₃＝min(η _j)

η _j, j=1 ..., N ₃for a jth optional approach axis angle, N ₃for the sum at optional approach axis angle; η _j≤ Φ, Φ are maximum permission approach axis angle.

C ₄for maximum/dive angle cost of climbing:

$C_4=\arctan \left(\frac{|{\mathrm{Tz}}_{i+1}-{\mathrm{Tz}}_i|}{\left|\right|a_i\left|\right|}\right)$

Tz _ifor present node T _ielevation, Tz _i+1for expanding node T _i+1elevation; And meet θ is the maximum permission underriding/angle of climb of unmanned plane;

C ₅for the longest voyage cost:

C ₅＝min(∑d _j)

D _j, j=1 ..., N ₅for from starting point to present node T _ijth optional voyage, N ₅for optional voyage sum; And meet d _mzxfor the longest distance;

C ₆for flying height cost:

C ₆＝min(H _j)

H _j, j=1 ..., N ₆for a jth optional minimum terrain clearance altitude, N ₆for optional minimum terrain clearance altitude sum; And meet H _min≤ H _j≤ H _max, H _minfor minimum flight altitude restriction, H _maxfor the highest flying height restriction;

C ₇for distance threatens district's cost:

C ₇＝min(W _j)

W _j, j=1 ..., N ₇threaten offset from, N recently for jth is optional ₇for optional threaten recently offset from sum.

5. a kind of space-time synchronous matching process collaborative for two unmanned plane according to claim 1, is characterized in that,

L(T _i,T _i+1)＝|(L _Ti+L _Ti+1)-L _q|

L _tifor present node T _ithe voyage of reaching home, L _ti+1for expanding node T _i+1the voyage of reaching home, L _qfor collaborative voyage.

Collaborative voyage L _qdifferent according to the formula that the difference of unmanned plane during flying flight path dimension adopts.Voyage is worked in coordination with for one dimension, L _q=k ₁.max{D ₁, D ₂, k ₁for air line distance coefficient, max{D ₁, D ₂be the maximum linear distance of two unmanned plane apart from terminal.Voyage is worked in coordination with for two dimension, L _q=k ₂.max{D ₁, D ₂, k ₂for two-dimentional Euclidean distance coefficient; Max{D ₁, D ₂be the maximum two-dimentional Euclidean distance of two unmanned plane apart from terminal.Voyage is worked in coordination with for three-dimensional, L _q=k ₃.max{D ₁, D ₂, k ₃for three-dimensional Euclidean distance coefficient, max{D ₁, D ₂be the maximum three-dimensional Euclidean distance of two unmanned plane apart from terminal.

6. a kind of space-time synchronous matching process collaborative for two unmanned plane according to claim 5, is characterized in that, work in coordination with voyage for one dimension, L _q=k ₁.max{D ₁, D ₂, k ₁for air line distance coefficient, max{D ₁, D ₂be the maximum linear distance of two unmanned plane apart from terminal.

7. a kind of space-time synchronous matching process collaborative for two unmanned plane according to claim 5, is characterized in that, work in coordination with voyage for two dimension, L _q=k ₂.max{D ₁, D ₂, k ₂for two-dimentional Euclidean distance coefficient; Max{D ₁, D ₂be the maximum two-dimentional Euclidean distance of two unmanned plane apart from terminal.

8. a kind of space-time synchronous matching process collaborative for two unmanned plane according to claim 5, is characterized in that, work in coordination with voyage for three-dimensional, L _q=k ₃.max{D ₁, D ₂, k ₃for three-dimensional Euclidean distance coefficient, max{D ₁, D ₂be the maximum three-dimensional Euclidean distance of two unmanned plane apart from terminal.

9. a kind of space-time synchronous matching process collaborative for two unmanned plane according to claim 5, is characterized in that, the required constraint condition of described unmanned aerial vehicle flight path planning comprises the minimum flight path segment length l of unmanned plane _min, maximum permission turning angle , maximum permission underriding/angle of climb θ, the longest track distance D _mzx, minimum flight altitude restriction H _min, the highest flying height restriction H _maxwith flight safety distance Ds.