CN108733074A - A kind of multiple no-manned plane formation path planning method based on Hungary Algorithm - Google Patents
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Abstract
The purpose of the present invention is to provide a kind of multiple no-manned plane formation path planning method based on Hungary Algorithm, unmanned plane initial position form distance matrix at a distance from target point；Transformed distances matrix is chosen neutral element and is marked, counts the number of neutral element, the optimal solution for whether meeting assignment problem seen, to neutral element minimum vertex-covering in matrix；The minimum value in all elements for removing minimum vertex-covering is found out, all elements that do not cover subtract the value, and element adds the value in the markd row of institute, ensures that the position of former neutral element is constant；It is performed repeatedly until and can be derived that the corresponding matrix of consequence of optimal solution；Transformation obtains optimal solution, after distribution, carries out simulated flight and otherwise needs avoidance with this to determine whether there is the possibility of collision.The beneficial effects of the invention are as follows highly practical, model is simple, and calculation amount is small, and the time to configuration design and trajectory planning is short and efficient.
Description
Technical field
The invention belongs to air vehicle technique fields, are related to a kind of multiple no-manned plane formation trajectory planning based on Hungary Algorithm
Method.
Background technology
Along with the continuous increase of the development and military political requirement of modern science and technology, single rack unmanned plane in many cases
Mission requirements are can no longer meet, therefore multiple no-manned plane Formation Technology just becomes the hot spot of research.For civilian, nothing
Man-machine formation flight display be also in recent years since hot issue, the unmanned plane quantity of formation flight by most tens
Frame has developed to present thousands of framves.The key technical problem of UAV Formation Flight include mainly configuration design, pneumatic coupling,
The adjustment of formation dynamic, trajectory planning and formation flight control strategy etc..Hungary Algorithm is a kind of combinatorial optimization algorithm, is used for
Assignment problem is solved, is mainly used in bipartite graph, core is exactly to find augmenting path.Unmanned plane is formed into columns：It is assisted according to pre-determined route
With the multiple UAVs combination of flight.Trajectory planning：The trajectory planning of unmanned plane is to consider unmanned plane arrival time, electricity
Under the premise of the factors such as pond electricity and flight range, flight track that is optimal, or being satisfied with is cooked up for aircraft, from
And ensure satisfactorily to complete aerial mission.The trajectory planning of quadrotor (more rotors) UAV Formation Flight it is existing substantially by
Mission Planner etc. increase income unmanned aerial vehicle station software realization.When the quantity of unmanned plane is excessive, artificially go to set
The course line for setting each frame unmanned plane can have heavy workload, it is possible to occur that phase occurs when unmanned plane during flying in planning process
It hits.The present invention can distribute its terminal, and the knot of this distribution for every frame unmanned plane automatically after setting unmanned plane formation
Fruit makes the total distance of whole unmanned plane during flyings most short.On this basis, it is proposed that a kind of avoidance mode based on the time difference has
Effect prevents unmanned plane from colliding in flight course.The basic characteristics of the prior art be model it is more complex, it is computationally intensive, planning
Time is long and is easily trapped into dead state, and configuration design and trajectory planning all individually carry out substantially, and the design cycle is very long.
Invention content
The purpose of the present invention is to provide a kind of multiple no-manned plane formation path planning method based on Hungary Algorithm, this hair
Bright advantageous effect is highly practical, and model is simple, and calculation amount is small, and the time to configuration design and trajectory planning is short and imitates
Rate is high.
The technical solution adopted in the present invention is to follow the steps below：
Step 1：Quantity, the opposite initial coordinate of unmanned plane and the final unmanned plane of input formation unmanned plane will form team
The terminal point coordinate of shape；
Step 2：N frame unmanned plane initial positions are calculated at a distance from n target point, form the distance matrix A of a n*n；
Step 3：Transformed distances matrix A so that neutral element all occur in matrix each row and column, this matrix is denoted as A1；
(1) each row all elements in A are all first subtracted into a constant；
(2) to respectively row are similarly handled in A；
Step 4：Carry out examination appointment；
(1) A is counted1Each ranks in neutral element number, choose the correspondence row of minimum number
Or row, and choose a neutral element and mark zero, if neutral element number is more than 1,
Random labelling one of them, the row and column where subsequently temporarily scratching zero element obtains sub- square
Battle array reprocesses remaining submatrix, until neutral element is not present in submatrix, this
When matrix be denoted as A2；
(2) A is counted2In zero element number, if number is equal to n, and n zero elements
Distribution meet the form of different lines of not going together, then A2Meet the optimal solution of assignment problem,
Algorithm stops；Otherwise next step is executed；
Step 5：A2The minimum vertex-covering of middle neutral element；
(1) to the line flag √ without zero element；
(2) √ is marked to the row belonging to all neutral elements in the row that is marked there are √；
(3) again to the line flag √ belonging to all "○" elements in the row of marked √；
(4) step (2) (3) is repeated, until all ranks can not all mark √；
Using horizontal line label, there is no the rows of √ labels, and ordinate, these transverse and longitudinals are marked to the row of all existing √ labels
Line together constitutes the minimum vertex-covering of all neutral elements；
Step 6：Adjustment of matrix；
(1) minimum value in all elements for removing minimum vertex-covering is found out first, all elements that do not cover subtract the value, and
Element adds the value in the row of all label √, and matrix at this time is A3, can ensure that the position of former neutral element is constant in this way；
(2) it is back to step 2 processing A3, it is performed repeatedly until and can be derived that the corresponding matrix of consequence of optimal solution；
Step 7：Transformation obtains optimal solution, after distribution, carries out simulated flight, with this to determine whether have a collision can
Can, otherwise need avoidance.
Further, each row all elements all subtract a constant in step 3, this constant is least member in the row.
Further, the matrix of consequence obtained in step 6 needs to be transformed to dematrix, first by all zero yuan in optimal solution
Element becomes 1, and other elements become 0, and such 0-1 matrixes are exactly the dematrix of allocation problem.
Further, barrier-avoiding method is as follows in step 7：
1) assume that all unmanned planes take off simultaneously, using 0.1s as time interval, calculate the position of unmanned plane after often crossing 0.1s
It sets；
2) it calculates and has two framves before all unmanned planes reach terminal per the mutual distance between moment unmanned plane
Unmanned plane is not up to its terminal and at a distance of 0.5m is less than, then judges have collision possible, carry out in next step, and otherwise algorithm terminates,
Record flight setting at this time；
3) the unmanned plane delay 1s of number rearward is allowed to take off again, if delayed mistake, delay time add this unmanned plane again
1s；Entire flight course simulates calculating, return to step 2 again)；If appearance has had a frame unmanned plane to have arrived at its terminal,
And another frame unmanned plane is excessively close apart from this unmanned plane in flight course, program can show its distance, and remind user, can be with
The resolution ratio of formation is formed by modification to solve；So far, multiple no-manned plane trajectory planning is completed with avoidance.
Specific implementation mode
The present invention is described in detail With reference to embodiment.
The present invention is based on the multiple no-manned plane formation path planning method of Hungary Algorithm, steps are as follows：
Step 1：The quantity of formation unmanned plane, the opposite initial coordinate of unmanned plane and finally are inputted in matlab softwares
Unmanned plane will form the terminal point coordinate of formation；
Step 2：N frame unmanned plane initial positions are calculated at a distance from n target point, form the distance matrix A of a n*n；
In unmanned plane assignment problem, the variation of row or column is carried out to its distance matrix so that all occur in each row and column
Neutral element finally obtains a null element prime matrix for including n different lines of not going together by corresponding adjustable strategies, thus real
Show and be fully allocated, and the total distance of unmanned plane during flying is most short.
Step 3：Transformed distances matrix A so that neutral element all occur in matrix each row and column, this matrix is denoted as A1
(1) each row all elements in A are all first subtracted into a constant, this constant is generally least member in the row；
(2) to respectively row are similarly handled in A.
Step 4：Carry out examination appointment
(1) A is counted1Each ranks in neutral element number, choose the correspondence row or column of minimum number, and choose one zero
Element mark "○" (if neutral element number be more than 1, random labelling one of them).Subsequently temporarily scratch "○" element institute
Row and column obtain submatrix.Remaining submatrix is reprocessed according to corresponding mode, until null element is not present in submatrix
Until element, matrix at this time is denoted as A2；
(2) A is counted2The number of middle "○" element, if number is exactly equal to n, and the distribution of n "○" element meets not
The form for different lines of going together, then A2Meet the optimal solution of assignment problem, algorithm stops；Otherwise next step is executed.
Step 5：A2The minimum vertex-covering of middle neutral element
(1) to the line flag √ of no "○" element；
(2) √ is marked to the row belonging to all neutral elements in the row that is marked there are √；
(3) again to the line flag √ belonging to all "○" elements in the row of marked √；
(4) above-mentioned (2) (3) are repeated, until all ranks can not all mark √.
Using horizontal line label, there is no the rows of √ labels, and ordinate, these transverse and longitudinals are marked to the row of all existing √ labels
Line together constitutes the minimum vertex-covering of all neutral elements.
Step 6：Adjustment of matrix
(1) minimum value in all elements for removing minimum vertex-covering is found out first, all elements that do not cover subtract the value, and
Element adds the value in the row of all label √, and matrix at this time is A3.It can ensure that the position of former neutral element is constant in this way；
(2) it is back to step 2 processing A3, it is performed repeatedly until and can be derived that the corresponding matrix of consequence of optimal solution.
Step 7：Transformation obtains optimal solution
It needs to be transformed to dematrix in the matrix of consequence that step 6 obtains, first becomes all "○" elements in optimal solution
1, other elements become 0, and such 0-1 matrixes are exactly the dematrix of allocation problem.
After distribution, simulated flight is carried out, with this to determine whether there is the possibility of collision.Assuming that two frame unmanned planes are apart
0.5m may collide.Assuming that unmanned plane cruising speed is 2m/s can ignore nobody because when flying distance is long
Acceleration time when machine takes off and deceleration time when arrival target point.It is therefore assumed that unmanned plane is even in entire flight course
Speed flight.
Avoidance mode is realized as follows：
1) assume that all unmanned planes take off simultaneously, using 0.1s as time interval, calculate the position of unmanned plane after often crossing 0.1s
It sets.
2) it calculates and has two framves before all unmanned planes reach terminal per the mutual distance between moment unmanned plane
Unmanned plane is not up to its terminal and at a distance of 0.5m is less than, then judges have collision possible, carry out in next step.Otherwise algorithm terminates,
Record flight setting at this time.
3) the unmanned plane delay 1s of number rearward is allowed to take off again, if delayed mistake, delay time add this unmanned plane again
1s.Entire flight course simulates calculating again.Return to step 2).
If appearance has had a frame unmanned plane to have arrived at its terminal, and another frame unmanned plane in flight course apart from this
Frame unmanned plane is excessively close, and program can show its distance, and remind user.The resolution ratio of formation can be formed by modification to solve.
So far, multiple no-manned plane trajectory planning is completed with avoidance.
The present invention is that each frame unmanned plane distributes task, nothing automatically according to the initial coordinate and terminal point coordinate of unmanned aerial vehicle group
It need to artificially plan, model is simple, and planning time is short.Creatively two key technologies of configuration design and trajectory planning are mixed,
It can be carried out at the same time, therefore substantially reduce the design cycle, be effectively improved the design of unmanned plane flight pattern and trajectory planning
Efficiency.A kind of avoidance mode based on the time difference is proposed simultaneously, effectively unmanned plane is avoided to collide in flight course.
The above is only the better embodiment to the present invention, not makees limit in any form to the present invention
System, every any simple modification that embodiment of above is made according to the technical essence of the invention, equivalent variations and modification,
Belong in the range of technical solution of the present invention.
Claims (4)
1. a kind of multiple no-manned plane formation path planning method based on Hungary Algorithm, it is characterised in that according to the following steps into
Row：
Step 1：Quantity, the opposite initial coordinate of unmanned plane and the final unmanned plane of input formation unmanned plane will form formation
Terminal point coordinate；
Step 2：N frame unmanned plane initial positions are calculated at a distance from n target point, form the distance matrix A of a n*n；
Step 3：Transformed distances matrix A so that neutral element all occur in matrix each row and column, this matrix is denoted as A1；
(1) each row all elements in A are all first subtracted into a constant；
(2) to respectively row are similarly handled in A；
Step 4：Carry out examination appointment；
(1) A is counted1Each ranks in neutral element number, choose the correspondence row or column of minimum number, and choose a neutral element
Mark zero, if neutral element number is more than 1, random labelling one of them, subsequently temporarily scratch row where zero element and
Row obtain submatrix, reprocess remaining submatrix, until neutral element is not present in submatrix, matrix at this time is denoted as
A2；
(2) A is counted2In zero element number, if number is equal to n, and the distribution of n zero elements meets different lines of not going together
Form, then A2Meet the optimal solution of assignment problem, algorithm stops；Otherwise next step is executed；
Step 5：A2The minimum vertex-covering of middle neutral element；
(1) to the line flag √ without zero element；
(2) √ is marked to the row belonging to all neutral elements in the row that is marked there are √；
(3) again to the line flag √ belonging to all "○" elements in the row of marked √；
(4) step (2) (3) is repeated, until all ranks can not all mark √；
Using horizontal line label, there is no the rows of √ labels, mark ordinate, these transverse and longitudinal lines total the row of all existing √ labels
With the minimum vertex-covering for constituting all neutral elements；
Step 6：Adjustment of matrix；
(1) minimum value in all elements for removing minimum vertex-covering is found out first, and all elements that do not cover subtract the value, and own
Element in the row of √ is marked to add the value, matrix at this time is A3, can ensure that the position of former neutral element is constant in this way；
(2) it is back to step 2 processing A3, it is performed repeatedly until and can be derived that the corresponding matrix of consequence of optimal solution；
Step 7：Transformation obtains optimal solution, after distribution, carries out simulated flight, with this to determine whether there is the possibility of collision,
Otherwise avoidance is needed.
2. existing according to a kind of multiple no-manned plane formation path planning method based on Hungary Algorithm, feature described in claim 1
In：Each row all elements all subtract a constant in the step 3, this constant is least member in the row.
3. existing according to a kind of multiple no-manned plane formation path planning method based on Hungary Algorithm, feature described in claim 1
In：The matrix of consequence obtained in step 6 needs to be transformed to dematrix, and all zero elements in optimal solution are become 1 first,
Other elements become 0, and such 0-1 matrixes are exactly the dematrix of allocation problem.
4. existing according to a kind of multiple no-manned plane formation path planning method based on Hungary Algorithm, feature described in claim 1
In：Barrier-avoiding method is as follows in the step 7：
1) assume that all unmanned planes take off simultaneously, using 0.1s as time interval, calculate the position of unmanned plane after often crossing 0.1s；
2) mutual distance between calculating per moment unmanned plane, before all unmanned planes reach terminal, have two framves nobody
Machine is not up to its terminal and at a distance of 0.5m is less than, then judges have collision possible, carry out in next step, otherwise algorithm terminates, record
Flight setting at this time；
3) the unmanned plane delay 1s of number rearward is allowed to take off again, if delayed mistake, delay time add 1s to this unmanned plane again；It is whole
A flight course simulates calculating, return to step 2 again)；If appearance has had a frame unmanned plane to have arrived at its terminal, and another
Frame unmanned plane is excessively close apart from this unmanned plane in flight course, and program can show its distance, and remind user, can be by repairing
Reorganize into the resolution ratio of formation to solve；So far, multiple no-manned plane trajectory planning is completed with avoidance.
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Cited By (13)
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| CN109557939A (en) * | 2019-01-07 | 2019-04-02 | 上海交通大学 | A kind of quick approach to formation control based on pseudo- distributed unmanned plane cluster |
| CN110262543A (en) * | 2019-05-23 | 2019-09-20 | 北京航空航天大学 | Multiple target point reaches the cluster 4 D trajectory planning and designing method under constraint simultaneously |
| CN110347180A (en) * | 2019-08-12 | 2019-10-18 | 南京邮电大学 | The method for calculating the most short tail clearance that unmanned plane cluster is formed into columns again |
| CN110515391A (en) * | 2019-08-20 | 2019-11-29 | 西南石油大学 | A kind of three-dimensional barrier-avoiding method of unmanned plane formation based on gradient function |
| CN110687917A (en) * | 2019-09-06 | 2020-01-14 | 哈尔滨工程大学 | Multi-unmanned-boat distributed formation reconfiguration formation control method |
| CN111474539A (en) * | 2020-04-22 | 2020-07-31 | 上海海事大学 | Radar and AIS track association method based on improved grey association |
| WO2020186919A1 (en) * | 2019-03-18 | 2020-09-24 | 北京京东尚科信息技术有限公司 | Unmanned aerial vehicle cluster system, take-off control method, apparatus and system, and readable medium |
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| CN112362061A (en) * | 2020-10-21 | 2021-02-12 | 一飞(海南)科技有限公司 | Cluster unmanned aerial vehicle path assignment method, control system, storage medium and unmanned aerial vehicle |
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| CN110262543A (en) * | 2019-05-23 | 2019-09-20 | 北京航空航天大学 | Multiple target point reaches the cluster 4 D trajectory planning and designing method under constraint simultaneously |
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| CN110515391B (en) * | 2019-08-20 | 2022-04-15 | 西南石油大学 | Unmanned aerial vehicle formation three-dimensional obstacle avoidance method based on gradient function |
| CN110515391A (en) * | 2019-08-20 | 2019-11-29 | 西南石油大学 | A kind of three-dimensional barrier-avoiding method of unmanned plane formation based on gradient function |
| CN110687917A (en) * | 2019-09-06 | 2020-01-14 | 哈尔滨工程大学 | Multi-unmanned-boat distributed formation reconfiguration formation control method |
| CN111474539A (en) * | 2020-04-22 | 2020-07-31 | 上海海事大学 | Radar and AIS track association method based on improved grey association |
| CN111781927A (en) * | 2020-06-28 | 2020-10-16 | 上海运晓机器人有限公司 | Scheduling and distributing method for multi-robot cooperative transportation task |
| CN112362061A (en) * | 2020-10-21 | 2021-02-12 | 一飞(海南)科技有限公司 | Cluster unmanned aerial vehicle path assignment method, control system, storage medium and unmanned aerial vehicle |
| CN112631323A (en) * | 2020-11-19 | 2021-04-09 | 一飞(海南)科技有限公司 | Cluster unmanned aerial vehicle grouping assignment method, system, controller, medium and terminal |
| CN112631323B (en) * | 2020-11-19 | 2023-10-31 | 一飞(海南)科技有限公司 | Cluster unmanned aerial vehicle grouping assignment method, system, controller, medium and terminal |
| CN114518771A (en) * | 2022-02-23 | 2022-05-20 | 深圳大漠大智控技术有限公司 | Multi-unmanned aerial vehicle path planning method and device and related components |
| CN115629600A (en) * | 2022-08-01 | 2023-01-20 | 北方工业大学 | Multi-machine cooperative trapping method in complex dynamic security environment based on buffer voronoi diagram |
| CN115629600B (en) * | 2022-08-01 | 2023-12-12 | 北方工业大学 | Multi-machine collaborative trapping method based on buffer Wino diagram in complex dynamic security environment |
| CN116088585A (en) * | 2023-04-07 | 2023-05-09 | 中国民用航空飞行学院 | Multi-unmanned aerial vehicle take-off and landing sequence planning system and method based on Hungary algorithm |
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