CN108613676A - A kind of unmanned plane and there is the multimachine multiple target emergency rescue path planning method under Mechanism of Human-Computer Cooperation - Google Patents
A kind of unmanned plane and there is the multimachine multiple target emergency rescue path planning method under Mechanism of Human-Computer Cooperation Download PDFInfo
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- G—PHYSICS
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
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- 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
Present invention firstly discloses a kind of unmanned plane and there is the multimachine multiple target emergency rescue path planning method under Mechanism of Human-Computer Cooperation：S1：Multiple no-manned plane is carried out to disaster area and cooperates with cover type search, and obtains the geographical location of the doubtful point of disaster affected people；S2：Geographical location according to the doubtful point of disaster affected people, cook up the optimal trajectory that multiple no-manned plane cooperates with doubtful point to search, and implement the doubtful point of multiple no-manned plane collaboration according to the optimal trajectory and search prediction scheme, obtain geographical location and the disaster affected people quantity situation of disaster affected people key point；S3：According to disaster affected people key point geographical location and disaster affected people quantity situation, planning is had the optimal trajectory of man-machine coordination key point emergency management and rescue more, and has man-machine search and rescue optimal trajectory to implement have man-machine coordination key point emergency rescue prediction scheme according to described more more.This method can effectively improve emergency management and rescue efficiency and safety under the conditions of China mountain area, flexibly cope with different mountain area flight environment of vehicle, to ensure that rescue flight carries out safely sufficient preparation.
Description
Technical field
The present invention relates under the environment of mountain area technical field of aviation emergency rescue more particularly to major natural disasters (as
Shake, mud-rock flow etc.) the aviation emergency rescue flight path under the conditions of mountain area advises technology, more particularly to and one kind can effectively improve China mountain
Emergency management and rescue efficiency and safety under the conditions of area, and can flexibly cope with different mountain area flight environment of vehicle and the nothing that abundant rescue prepares is provided
It is man-machine and have the multimachine multiple target emergency rescue path planning method under Mechanism of Human-Computer Cooperation.
Background technology
After mountain area major natural disasters occur, by civilian unmanned plane and navigation have it is man-machine based on aviation emergency management and rescue tool
Have that quick, efficient, degree of danger is low, secondary injury rate is low and by advantages such as disaster area geographical space less-restrictives, it can be
One time made emergency management and rescue response to disaster area.Ensure to the landform in disaster area, disaster-stricken situation, emphasis devastated differentiate with
And goods and materials deliver being smoothed out for work, to reducing people life property loss's important in inhibiting.However the existing boat in China
Empty emergency management and rescue operation regulation and emergency management and rescue scheme are simultaneously not perfect, cause rescue efficiency relatively low and rescue personnel faces after calamity not
The problems such as knowing the danger of environmental threat so that the safety of search and rescue is unable to get guarantee.With Sichuan Province's on May 12nd, 2008
For the earthquake of Wenchuan city, Civil Aviation Administration of China has assembled from east China General Aviation Corp, Zhuhai helicopter branch company of South Airways
Deng total more than 30 frame frame rescue helicopters to implementing rescue work, but after being shaken, disaster area terrain environment is complicated, meteorological condition
Poor, flight information prepares the influence of the problems such as deficiency, severely afflicated area disaster-stricken situation and indefinite rescue target, leads to rescue task
It promotes poor compared with slow and safety etc..Therefore, under the conditions of mountain area, aviation search and rescue preparation for disaster area and
The search of unmanned plane early period is particularly important.It is rational to distribute unmanned plane and have man-machine rescue task, and efficiently
Its search and rescue flight track of planning for disaster-stricken mountain area search and rescue work have more positive meaning.For this purpose, local
After the major natural disasters such as shake, mud-rock flow occur, according to the difference of local rescue team and follow-up supply troop fleet configuration, search
It seeks that rescue landing point, searching target point is different, unmanned plane is different from there is man-machine execution task, how reasonably to unmanned plane and to have
The shuttle flight path of search and rescue is planned in man-machine carry out task distribution, formulates aviation emergency plan HSE, and it is emergent to improve aviation
Rescue efficiency and the critical issue for ensureing rescue safety.
Invention content
It is an object of the invention to overcome the above-mentioned deficiency in the presence of the prior art, a kind of multiple no-manned plane and someone are provided
Multimachine multiple target emergency rescue path planning method under machine synergistic mechanism, the method, can be used in difference according to the present invention
Under the conditions of the major natural disasters of mountain area, unmanned plane and the efficient formulation for having man-machine phase that the collaboration of multimachine multiple target is cooperateed with to search and rescue prediction scheme,
To improve disaster area search and rescue efficiency, ensure that rescue flight carries out safely sufficient preparation.
In order to achieve the above-mentioned object of the invention, the present invention provides following technical schemes：
A kind of unmanned plane and there are the multimachine multiple target emergency rescue path planning method under Mechanism of Human-Computer Cooperation, feature to exist
In including the following steps：
S1：Multiple no-manned plane is carried out to disaster area and cooperates with cover type search, and obtains the geographical position of the doubtful point of disaster affected people
It sets；
S2：According to the geographical location of the doubtful point of disaster affected people obtained in step 1, cooks up multiple no-manned plane and cooperate with doubtful point
The optimal trajectory of search, and implement the doubtful point of multiple no-manned plane collaboration according to the optimal trajectory and search prediction scheme, it obtains disaster affected people and closes
The geographical location of key point and each key point disaster affected people quantity situation；
S3：Key point geographical location and each key point disaster affected people quantity are determined according to the disaster affected people obtained in step 2
Situation, planning is had the optimal trajectory of man-machine coordination key point emergency management and rescue more, and implements more someone according to the optimal trajectory
Machine cooperates with key point emergency rescue prediction scheme.
Further, it carries out multiple no-manned plane using double photoelectric nacelle unmanned planes and cooperates with cover type search.
Wherein, double photoelectric nacelle unmanned planes refer to being mounted on two airborne photoelectric gondolas with certain setting angle
On unmanned aerial vehicle onboard gondola or unmanned aerial vehicle body so that the horizontal irradiation direction of two probes exists centainly with unmanned plane course
Angle, and the illumination levels direction of two photoelectric nacelles is opposite (direction of illumination differs 180 °) so that double photoelectric nacelles without
When a certain place of man-machine process, search can be scanned to the point from the place both sides, it is ensured that the orographic factors such as mountain area are made
At blind area it is minimum, further increase multiple no-manned plane collaboration cover type searching efficiency.
Further, the multiple no-manned plane in described rapid 1 cooperates with cover type search, includes the following steps：
S101：Geographic information image processing is carried out to disaster area, obtains the contour map in disaster area；
S102：According to the disaster area contour map obtained, using Convex Polygon Domain division principle, will each fly height
Degree layer is divided into multiple subtask regions；
S103：According to the subtask region divided, using multimachine oblique line formation search pattern, multiple no-manned plane is carried out to disaster area
Collaboration covering is searched, and records the geographical location of disaster affected people key point and each key point disaster affected people quantity situation.
Wherein, geographic information image is handled in the S101, is specifically comprised the following steps：
1) after obtaining SRTM digital elevation maps, the digital elevation model (DEM) in disaster area is exported using SuperMap
File.
2) digital elevation model (DEM) file is converted into XYZ points using three-dimensional map processing software Global Mapper
Cloud format file, and preserve TXT files.
3) the XYZ point cloud format files that disaster area is loaded in Matlab, reacquire the numerical map of the region, and
The numerical map is encrypted using the interpolation method of bicubic interpolation.
4) by analyze disaster area personnel may residing for height above sea level range (before such as disaster-stricken, personnel's life occupancy
Deng) and unmanned aerial vehicle onboard probe search performance requirement (maximum distance that can recognize that disaster affected people or vehicle etc.), to disaster-stricken
Area carries out height layer division, and flying height when searching for the altitude ranges according to unmanned plane generates regional contour map and is used for
It is used when multiple no-manned plane collaboration cover type search.
Further, the doubtful point of multiple no-manned plane collaboration is carried out using single photoelectric nacelle unmanned plane to search.
Wherein, single photoelectric nacelle unmanned plane refers to that single airborne probe is mounted on nobody with certain setting angle
On machine aircraft pod or unmanned aerial vehicle body so that the illumination levels direction of airborne probe is consistent with unmanned plane course, and energy
Enough using figure transmission module in real time/or record unmanned plane during flying during topographic features and disaster affected people wait for rescue situation etc..
Further, the doubtful point of multiple no-manned plane collaboration searches optimal trajectory in the step 2, mainly in the following way really
It is fixed：
S201：Doubtful geographic location of disaster affected people is obtained, the three-dimensional path planning algorithm in ant group algorithm is selected,
Evaluate the optimal path between the doubtful point of any two；
S202：According to the optimal path that step S201 is evaluated, further combined with unmanned plane quantity, departure place and jump area
Multiple no-manned plane is cooperateed with doubtful point to search optimal trajectory planning problem and is converted to traveling salesman problem, and utilizes genetic algorithm by positioning
It solves, obtains the optimal trajectory that multiple no-manned plane cooperates with doubtful point to search.
Preferably, in the step S202, can further by unmanned plane quantity, departure place and jump area positioning scenarios,
It is preset as following four kinds of patterns：
Pattern one：The doubtful point of multiple no-manned plane collaboration that the same airport of unmanned plane is set out and jump area is departure airport searches mould
Formula；
Pattern two：Same airport is set out and jump area airport is identical, but described that landing airport is different from departure airport
Multiple no-manned plane cooperates with doubtful search pattern
Pattern three：Different airports set out and jump area be respective departure airport, but unmanned plane quantity it is fixed mostly without
Doubtful search pattern of man-machine coordination；
Pattern four：Different airports set out and are respective departure airport by landing, but the quantity of unmanned plane is unfixed more
Unmanned plane cooperates with doubtful search pattern；
And after according to actual conditions choosing associative mode, using genetic algorithm, multiple no-manned plane collaboration of forming into columns is calculated and doubts
Optimal trajectory is searched like.
Further, the optimal trajectories for having man-machine coordination key point emergency management and rescue in the step 3, mainly by walking as follows more
It is rapid to determine：
S301：The geographical location of each disaster affected people key point is obtained, the three-dimensional path planning algorithm in ant group algorithm is selected,
Evaluate the optimal path between any two key point；And by the optimal path between any two key point evaluated away from
It is stored from matrix D 1 is converted to；
S302：Each key point disaster affected people quantity situation is obtained, and is preserved in the form of numbers matrix C2；
S303：According to the Distance matrix D 1 of optimal path between each key point and each key point disaster affected people numbers matrix
C2 acquires each key point disaster affected people Distance matrix D 2；Wherein, the path length of identical key point disaster affected people is 0；
S304：Further be combined with man-machine quantity, departure airport, manned amount, using greedy algorithm to respectively have it is man-machine into
Row rescue task distributes, to be there is the optimal trajectory of man-machine coordination key point emergency management and rescue more.
Further, the step S304 includes mainly：
S304a：According to having man-machine quantity and departure airport, ratio sequence is carried out, and press ranking results, corresponding to it
Someone's airborne people amount be denoted as Matrix Ch；
S304b：The inverse of each key point disaster affected people distance is calculated according to each key point disaster affected people Distance matrix D 2,
Again using the inverse as the equivalent value of next disaster relief personnel, using greedy algorithm, to there is man-machine rescue task to be allocated,
Confirm that every frame has the man-machine disaster relief place that should be gone to and each disaster relief place that should rescue number；
S304c：The rescue task for having man-machine distribution according to every frame, by every frame have after man-machine rescue task voyage summation by
It is arranged according to ascending order, and the airborne people's moment matrix C of someone is updated by ranking resultsh；
S304d：According to have it is man-machine rescued number, update and record each key point disaster affected people quantity situation；
S304e：Again according to each key point disaster affected people quantity situation after update, synchronized update and to record each key point disaster-stricken
Optimal path Distance matrix D 1 between personnel amount Matrix C 2, each disaster-stricken key point and disaster affected people Distance matrix D 2；
S304f：According further to data after update, cycle assignment has man-machine rescue task, until all disaster-stricken people
Member be assigned it is man-machine until.
Preferably, Google Earth flight simulation programs or SuperMap flight simulation programs are called, to Rescue Plan
Carry out simulated flight demonstration.
It is further preferred that calling Google Earth flight simulation api routines, cover type search is cooperateed with to multiple no-manned plane
Emergency preplan carries out simulated flight demonstration；The doubtful point of SuperMap flight simulations demonstration multiple no-manned plane collaboration is called to search emergent pre-
Case has man-machine coordination key to search emergency preplan more.It further ensures multiple no-manned plane in each prediction scheme or has man-machine coordination search and rescue
Task is smoothed out, and improves the execution safety of rescue task.
Further, during planning the optimal trajectory, can foundation respectively have man-machine or unmanned plane cruising ability complete
Distribution task corrects its trajectory planning in time, has man-machine, unmanned plane flight track to fully make rational planning for respectively, obtains most
Whole optimal trajectory, and ensure smoothly completing for multi-machine collaborative rescue task.
Compared with prior art, beneficial effects of the present invention：
1, the path planning method according to the present invention, different mountains can be flexibly applied to by studying for the first time and proposing one kind
Under the conditions of area's natural calamity, with specific reference to disaster area periphery flight resource, the condition, efficient and rational formulation multiple no-manned plane and more
The path planning method for having the emergency rescue prediction scheme that multimachine multiple target is carried out at the same time under Mechanism of Human-Computer Cooperation, effectively improves China mountain
Aviation flight emergency rescue efficiency and safety under the conditions of area, significantly reduce in rescue operations due to landform is unknown, information not
Caused by the reasons such as foot the problems such as secondary injury, the development of China mountain area aviation emergency rescue technology is played and significantly pushes meaning.
Multiple no-manned plane collaboration cover type is searched trajectory planning, more by 2, emergency rescue path planning method of the present invention
The doubtful point of unmanned plane collaboration searches trajectory planning and has man-machine coordination key point to search trajectory planning more and combines successively, by more
Unmanned plane cooperates with cover type trajectory planning, makes double photoelectricity unmanned planes to entire disaster area search quickly, comprehensively, determines and records
Doubtful geographic location of lower disaster affected people；Again by cooperateing with doubtful emergency rescue trajectory planning to multiple no-manned plane, make list
Photoelectricity unmanned plane carries out the collaboration of multimachine multiple target to the doubtful point of record and searches, and quickly determines and records disaster affected people key point institute
In geographical location；The last key point position determined according to multiple no-manned plane, has man-machine rescue flight path rationally to be advised on each airport
It draws, there is man-machine coordination accurately to rescue to realize more.It effectively avoids caused by the blindness and repeatability due to searching target
Rescue is chaotic, in wasting of resources situation and rescue operations due to landform is unknown, information is insufficient etc. caused by secondary injury
The problems such as, multi-machine collaborative search efficiency is significantly improved, and ensure the collaboration safety of emergency management and rescue and making full use of for resource
Property.
3, further, different from previous single airdrome control, path planning method of the present invention, be based on different airports nobody
The configuring conditions such as machine quantity, working performance, the problems such as considering aviation emergency management and rescue task-cycle feasibility comprehensively, and further
Give four kinds of the more unmanned planes and cooperate with doubtful search strategy, allow policymaker according to the actual conditions on different airports and
Disaster area geographical conditions feature selects different search strategies, the emergent search prediction scheme that efficient determination matches with disaster area situation.
4, further, it is of the present invention have man-machine coordination key point emergency rescue trajectory planning, it is ingenious will rescue
There is man-machine quantity to be converted into balanced assignment problem with disaster affected people quantity mismatch problem, using travelling salesman's solution throughway, and ties
Greedy algorithm is closed, to thering is man-machine carry out cycle task appointment, each airport of making rational planning for have man-machine flight rescue flight path, economize on resources
And ensure that all disaster affected peoples are rescued by effective distribution, forming practicable rescue has man-machine mine to target assignment scheme, improves
There is man-machine coordination rescue efficiency more.
5, further, the multimachine multiple target emergency rescue boat in multiple no-manned plane of the present invention and under having Mechanism of Human-Computer Cooperation
In mark planing method, Google Earth and SuperMap flight simulation functions are called, are flown to each emergency rescue scheme
Analog demenstration works, and further ensures multiple no-manned plane in each search and rescue prediction scheme or has man-machine coordination to search and rescue being smoothed out for task,
The safety for having ensured rescue personnel avoids accident from delaying rescue work progress.
Description of the drawings：
Fig. 1 is a kind of unmanned plane of the present invention and has the multimachine multiple target emergency rescue flight path under Mechanism of Human-Computer Cooperation to advise
Draw method flow diagram.
Fig. 2 is that multiple no-manned plane of the present invention cooperates with cover type to search trajectory planning flow chart.
Fig. 3 is that the doubtful point of multiple no-manned plane of the present invention collaboration searches trajectory planning flow chart.
Fig. 4 has man-machine coordination key point emergency rescue trajectory planning flow chart more to be of the present invention.
Fig. 5 is single photoelectric nacelle unmanned plane search model schematic diagram.
Fig. 6 is double photoelectric nacelle unmanned plane search model schematic diagrames.
Fig. 7 is the encrypted disaster area topographic map of bicubic interpolation method.
Fig. 8 is in conjunction with the getable drone flying height layer contour map of unmanned plane during flying.
Fig. 9 is that multiple no-manned plane oblique line formation cover type searches for schematic diagram.
Figure 10 is the disaster area topographic map regenerated in conjunction with unmanned plane during flying performance.
Three-dimensional path planning schematic diagram between doubtful point or key point that Figure 11 is obtained based on ant group algorithm.
The doubtful point of multiple no-manned plane collaboration searches flight path schematic diagram under Figure 12 different modes.
Specific implementation mode
With reference to test example and specific implementation mode, the present invention is described in further detail.But this should not be understood
It is only limitted to embodiment below for the range of the above-mentioned theme of the present invention, it is all that this is belonged to based on the technology that the content of present invention is realized
The range of invention.
As shown in Figure 1, a kind of unmanned plane and having the multimachine multiple target emergency rescue trajectory planning side under Mechanism of Human-Computer Cooperation
Method includes the following steps：
S1：It obtaining disaster area geography information and carries out assessment processing, planning multiple no-manned plane collaboration cover type searches flight path,
To obtain multiple no-manned plane collaboration cover type search prediction scheme, and call Google Earth simulation API demonstration prediction scheme after, implement it is more
Unmanned plane cooperates with cover type to search prediction scheme, and obtains the geographical location information of the doubtful point of disaster affected people；
S2：According to the geographical location of the doubtful point of disaster affected people obtained in step 1, cooks up multiple no-manned plane and cooperate with doubtful point
The optimal trajectory of search searches prediction scheme to obtain the doubtful point of multiple no-manned plane collaboration, and SuperMap flight simulations is called to demonstrate
After prediction scheme, implements multiple no-manned plane collaboration key point and search prediction scheme, obtain the geographical location of disaster affected people key point and each key point
Disaster affected people quantity situation；
S3：The disaster affected people key point geographical location obtained in foundation step 2 and each key point disaster affected people quantity situation,
Planning is had the optimal trajectory of man-machine coordination key point emergency rescue more, is obtained the doubtful point of multiple no-manned plane collaboration and is searched prediction scheme,
And after calling SuperMap flight simulations to demonstrate prediction scheme, implement have man-machine coordination key point emergency rescue prediction scheme more.
As shown in Fig. 2, the optimal trajectory planning of the multiple no-manned plane collaboration cover type search, mainly includes the following steps：
S101：Geographic information image processing is carried out to disaster area, and combines unmanned plane cruising ability, region of search size
Etc. performance indicators, obtain drone flying height layer contour map；Specially：
1) after obtaining SRTM digital elevation maps, the digital elevation model (DEM) in disaster area is exported using SuperMap
File.
2) digital elevation model (DEM) file is converted into XYZ points using three-dimensional map processing software Global Mapper
Cloud format file, and preserve TXT files.
3) the XYZ point cloud format files that disaster area is loaded in Matlab, reacquire the numerical map of the region, and
The numerical map is encrypted using the interpolation method of bicubic interpolation, be utilized bicubic interpolation method treated by
Calamity Topographic Map (as shown in Figure 7).
4) further according to the vertical height above sea level distribution situation residing for disaster area topographic analysis assessment disaster area personnel possibility
(such as disaster-stricken before, personnel's life occupancy etc.), is averagely divided into NvhA vertical range, height above sea level residing for personnel in each range
Degree is hvi→hvi+1, and popped one's head according to unmanned aerial vehicle onboard and search performance requirement height h, divide NvhA UAV Formation Flight height
Layer, every layer of height above sea level are hvi+1+h。
5) recycle Matlab softwares obtain drone flying height layer contour map (as shown in Figure 8), be used for it is each nobody
The machine level of forming into columns searches subtask region division and UAV Formation Flight avoidance.
S102：According to obtained drone flying height layer contour map, further combined with unmanned plane quantity, continuation of the journey energy
Disaster area is divided by the Performance Evaluations coefficients such as power, unmanned plane formation search width using Convex Polygon Domain division principle
Multiple subtask regions；Specifically division methods are：
1) the search subtask regional extent of same flight level divides：If NvhiIn a flight level jth group without
The search width of man-machine formation is bij, the region area to be searched corresponding to the height layer is area (Si), then ignoring turning
Can approximately it think in the case of time(VijIt forms into columns for this group of unmanned plane
Flying speed, TijFor that the time required to completing search mission, should ensure T as far as possibleijDifference is smaller in group).It is possible thereby to be inferred to
The Performance Evaluation coefficient f that jth group unmanned plane is formed into columnsij=area (Sij)/area(Si), and according to its evaluation coefficient using convex polygon
Shape rule obtains the search mission area of jth group unmanned plane formation.
2) different flying height interlayers search the cooperation of subtask region and update：Due to the unmanned plane of different height layer flight
Search time is different, to ensure the abundant use of unmanned plane, when other unmanned planes, which are formed into columns, completes search mission, should turn to fly to not
Region is completed to assist to search element.Set the time according to a preliminary estimate that search task is completed in jth group unmanned plane formation in i flight level
For Tij', when it, which completes it, searches task, turn to fly to assist to search for i+1 flight level.I+1 flying height at this time
The unmanned plane searched on layer completed Search Area area of forming into columns can be approximatelyI+1 flight level residue Search Area can be expressed asAccording to the updated nothing of i+1 flight level
Man-machine formation quantity reappraises unmanned plane formation performance and carries out unmanned plane region division according to convex polygon rule.
S103：In conjunction with the subtask region divided in step S102, using multimachine oblique line formation search pattern, to disaster area into
Row cover type search, and record the geographical location of disaster affected people key point and each key point disaster affected people quantity situation：
Specifically, as shown in figure 9, " multimachine oblique line formation search pattern " described in the step refers specifically to, double light are selected
Main equipment of the electric gondola unmanned plane (as shown in Figure 6) as cover type search and rescue, make the double photoelectric nacelle unmanned planes of multi-section from
Different airports are set out, and cover type search is carried out with " Z " font flight path in disaster area overhead, course should with distributed
The longer sides direction in subtask region is consistent, and can reduce unmanned plane formation number of turns in this way, improves searching efficiency.And
In search process, double photoelectric nacelle unmanned planes are to search for blind area caused by reducing alpine terrain factor, should ensure that unmanned plane is compiled
In team relative to search overlay area on the left of the unmanned plane of the course leftmost side and unmanned plane do for the first time 180 ° turn back when relative to boat
Search overlay area keeps overlapping on the left of to leftmost side unmanned plane, keeps the same area searched from both direction, effectively subtracts
Less due to searching for blind area caused by landform.
Further, unmanned plane is formed into columns during implementing to search prediction scheme, if encounter irregular slalom object, should take leap
Principle.If by unmanned plane climb descent performance influenced can not to complete leap when, should select to be diversion.
Further, distribution search task can be completed in conjunction with unmanned plane cruising ability and whether there is wasting of resources situation,
Flight path is corrected in time, obtains final optimal trajectory planning.After recalling Google Earth simulation API demonstration prediction schemes, implement
The doubtful point place latitude and longitude coordinates of prediction scheme and in real time record disaster affected people, the topographic features in Search Area and each key point are disaster-stricken
Personnel amount situation.And it is Matrix C 1 to arrange latitude coordinate postmenstruation, and reference is provided for subsequent flights task.
Further, main to wrap as shown in figure 3, the doubtful point of multiple no-manned plane collaboration searches optimal trajectory planning in the step 2
Include following steps：
S201：Doubtful geographic location of disaster affected people is obtained, the three-dimensional path planning algorithm in ant group algorithm is selected,
Evaluate the optimal path between the doubtful point of any two；Specially：
1) flying height H is searched according to the minimum of unmanned plane1minAnd the minimum constructive height difference △ between unmanned plane and massif
H1, by the XYZ point cloud format files of disaster area landform, all values increase the minimum constructive height between unmanned plane and massif
Poor △ h1, and minimum search flying height H will be less than1minValue all replace with H1min, import in Matlab after replacement and obtain again
The numerical map of the region is taken, and the numerical map is encrypted (such as Figure 10 institutes using the interpolation method of bicubic interpolation
Show).
2) any two doubtful point (including starting point/drop is solved using the three-dimensional path planning algorithm based on ant group algorithm
Drop point) between optimal path (as shown in figure 11), and the distance of its optimal path is converted into matrix form storage, and will be each
The way point coordinate record of paths gets off.
S202：According to the air route point coordinates of the step S201 optimal paths evaluated, further combined with unmanned plane quantity, go out
Multiple no-manned plane is cooperateed with doubtful point to search optimal trajectory planning problem and is converted to traveling salesman problem by hair ground and jump area positioning, and
According to unmanned plane quantity, departure place and jump area positioning scenarios, corresponding pattern is chosen from following preset four kinds of patterns：
Pattern one：The doubtful point of multiple no-manned plane collaboration that the same airport of unmanned plane is set out and jump area is departure airport searches mould
Formula；
Pattern two：Same airport is set out and jump area airport is identical, but described that landing airport is different from departure airport
Multiple no-manned plane cooperates with doubtful search pattern
Pattern three：Different airports set out and jump area be respective departure airport, but unmanned plane quantity it is fixed mostly without
Doubtful search pattern of man-machine coordination；
Pattern four：Different airports set out and are respective departure airport by landing, but the quantity of unmanned plane is unfixed more
Unmanned plane cooperates with doubtful search pattern.
And record result of calculation, including each unmanned plane way point information etc., to be formed more conveniently
Multiple no-manned plane cooperates with the optimal trajectory that doubtful point is searched.As shown in figure 12, it is the multiple no-manned plane collaboration cooked up under different mode
Doubtful point searches flight path schematic diagram.
Further, flight path is searched according to the doubtful point of multiple no-manned plane collaboration planned under different mode, and combines each nothing
Man-machine cruising ability, is modified flight path, to obtain corresponding to the optimal trajectory that multiple no-manned plane under each pattern cooperates with doubtful point
And search prediction scheme；After calling SuperMap flight simulations demonstration prediction scheme, select single photoelectric nacelle unmanned plane is (as shown in Figure 5) to implement
Multiple no-manned plane cooperates with key point to search prediction scheme, and the geographical location of record disaster affected people key point and the disaster-stricken people of each key point in real time
Member's quantity situation；
As shown in figure 4, in the step 3 have the planning of man-machine coordination key point emergency rescue optimal trajectory more, include mainly
Following steps：
S301：The geographical location of each disaster affected people key point is obtained, the three-dimensional path planning algorithm in ant group algorithm is selected,
Evaluate the optimal path between any two key point；And by the optimal path between any two key point evaluated away from
It is stored from matrix D 1 is converted to；Concrete operations are：
1) disaster area XYZ cloud data are loaded into, and according to key point geographical location information is obtained, reappraise disaster area personnel
The vertical height above sea level distribution situation of key point；
2) basis has man-machine minimum search flying height H2minAnd the minimum constructive height difference △ between unmanned plane and massif
h2, by the XYZ point cloud format files of disaster area landform, all values increase the minimum constructive height between unmanned plane and massif
Poor △ h2, and minimum search flying height H will be less than2minValue all replace with H2min, import in Matlab after replacement and obtain again
The numerical map of the region is taken, and the numerical map is encrypted (such as Fig. 8 institutes using the interpolation method of bicubic interpolation
Show).
3) any two key point (including starting point/drop is solved using the three-dimensional path planning algorithm based on ant group algorithm
Drop point) between optimal path, and the distance of its optimal path is converted into matrix form D1 storage, and by the boat of each paths
Waypoint coordinate record gets off (as shown in Figure 9).
S302：Each key point disaster affected people quantity situation is obtained, and is preserved in the form of numbers matrix C2；
S303：According to the Distance matrix D 1 of optimal path between each key point and each key point disaster affected people numbers matrix
C2 acquires each key point disaster affected people Distance matrix D 2；Wherein, the path length of identical key point disaster affected people is 0；
For example, setting totally 5 key points, respectively d1-d5, each key point disaster affected people quantity is respectively 6/10/9/
11/3, optimal path matrix can be expressed as between each key pointIt is each to close
Key point disaster affected people numbers matrix C2=[6,10,9,11,3]；Then each key point disaster affected people distance matrix is
S304：It is the equivalent value of next disaster relief personnel with the inverse of distance between each point, and is further combined with man-machine number
Amount, departure airport, manned amount, using greedy algorithm to respectively there is man-machine carry out rescue task distribution, until disaster affected people can be suitable
Profit obtain rescue until, specifically include：
S304a：Foundation has man-machine quantity and departure airport to sort in proportion.And ranking results are pressed, corresponding to it
Someone's airborne people amount be denoted as Matrix Ch。
For example, it is 3 framves that A airport rescues, which have man-machine quantity, capacity is respectively 5/5/5；B airport rescues have the man-machine quantity to be
6 framves, it is 8/8/8/8/8/8 to correspond to manned amount；There is man-machine ratio to be ranked up according to different airport rescues, and by its manned amount
Arranged in sequence obtains Matrix C h=[5,8,8,5,8,8,5,8,8]；
S304b：The inverse of each key point disaster affected people distance is calculated according to each key point disaster affected people Distance matrix D 2,
Again using the inverse as the equivalent value of next disaster relief personnel, using greedy algorithm, to there is man-machine rescue task to be allocated,
Confirm that every frame has the man-machine disaster relief place that should be gone to and each disaster relief place that should rescue number；
S304c：The rescue task for having man-machine distribution according to every frame, by every frame have after man-machine rescue task voyage summation by
It is arranged according to ascending order, and the airborne people's moment matrix C of someone is updated by ranking resultsh；
S304d：According to have it is man-machine rescued number, update and record each key point disaster affected people quantity situation；
S304e：Again according to each key point disaster affected people quantity situation after update, synchronized update and to record each key point disaster-stricken
Optimal path Distance matrix D 1 between personnel amount Matrix C 2, each disaster-stricken key point and disaster affected people Distance matrix D 2；
S304f：According further to data after update, cycle assignment has man-machine rescue task, until all disaster-stricken people
Member be assigned it is man-machine until.
And be further combined with man-machine cruising ability and obtain having man-machine coordination key point emergency rescue optimal trajectory more, to
Obtain having man-machine coordination key point emergency plan HSE more.And it is pre- to call SuperMap flight simulations to demonstrate the collaboration emergency management and rescue
Case ensures the smooth execution for having man-machine coordination key point rescue mission more.
Claims (10)
1. a kind of unmanned plane and thering is the multimachine multiple target emergency rescue path planning method under Mechanism of Human-Computer Cooperation, feature to exist
In including the following steps：
S1：Multiple no-manned plane is carried out to disaster area and cooperates with cover type search, and obtains the geographical location of the doubtful point of disaster affected people；
S2：According to the geographical location of the doubtful point of disaster affected people obtained in step 1, cooks up the doubtful point of multiple no-manned plane collaboration and search
Optimal trajectory, and according to the optimal trajectory implement multiple no-manned plane collaboration it is doubtful point search prediction scheme, obtain disaster affected people key point
Geographical location and each key point disaster affected people quantity situation；
S3：According to the disaster affected people key point geographical location and each key point disaster affected people quantity situation obtained in step 2, planning
There is the optimal trajectory of man-machine coordination key point emergency rescue more, and has man-machine coordination crucial according to optimal trajectory implementation more
Point emergency rescue prediction scheme.
2. a kind of unmanned plane and the multimachine multiple target emergency rescue flight path rule having under Mechanism of Human-Computer Cooperation according to claim 1
The method of drawing, which is characterized in that carry out multiple no-manned plane using double photoelectric nacelle unmanned planes and cooperate with cover type search.
3. a kind of unmanned plane according to claim 2 and thering is multimachine multiple target of the Mechanism of Human-Computer Cooperation unmanned plane as under to answer
It is anxious to search and rescue path planning method, which is characterized in that the multiple no-manned plane in the step 1 cooperates with cover type search, including walks as follows
Suddenly：
S101：Geographic information image processing is carried out to disaster area, obtains the contour map in disaster area；
S102：According to the disaster area contour map obtained, using Convex Polygon Domain division principle, by each flight level
It is divided into multiple subtask regions；
S103：According to the subtask region divided, using multimachine oblique line formation search pattern, multiple no-manned plane collaboration is carried out to disaster area
Covering is searched, and records the geographical location of disaster affected people key point and each key point disaster affected people quantity situation.
4. a kind of unmanned plane according to claim 1 and having the multimachine multiple target emergency rescue flight path under Mechanism of Human-Computer Cooperation
Planing method, which is characterized in that the doubtful point of multiple no-manned plane collaboration is carried out using single photoelectric nacelle unmanned plane and is searched.
5. a kind of unmanned plane according to claim 1 and having the multimachine multiple target emergency rescue flight path under Mechanism of Human-Computer Cooperation
Planing method, which is characterized in that the doubtful point of multiple no-manned plane collaboration searches optimal trajectory in the step 2, mainly passes through such as lower section
Formula determines：
S201：Doubtful geographic location of disaster affected people is obtained, the three-dimensional path planning algorithm in ant group algorithm, assessment are selected
Go out the optimal path between the doubtful point of any two；
S202：It is fixed further combined with unmanned plane quantity, departure place and jump area according to the optimal path that step S201 is evaluated
Multiple no-manned plane is cooperateed with doubtful point to search optimal trajectory planning problem and is converted to traveling salesman problem, and asked using genetic algorithm by position
Solution obtains the optimal trajectory that multiple no-manned plane cooperates with doubtful point to search.
6. a kind of unmanned plane according to claim 3 and having the multimachine multiple target emergency rescue flight path under Mechanism of Human-Computer Cooperation
Planing method, which is characterized in that in the step S202, can further position unmanned plane quantity, departure place and jump area
Situation is preset as following four kinds of patterns：
Pattern one：The multiple no-manned plane that the same airport of unmanned plane is set out and jump area is departure airport cooperates with doubtful search pattern；
Pattern two：Same airport is set out and jump area airport is identical, but it is described by land airport it is different from departure airport mostly without
Doubtful search pattern of man-machine coordination
Pattern three：Different airports are set out and jump area is respective departure airport, but the fixed multiple no-manned plane of quantity of unmanned plane
Cooperate with doubtful search pattern；
Pattern four：Different airports set out and will landing be respective departure airport, but unmanned plane quantity it is unfixed mostly nobody
Machine cooperates with doubtful search pattern；
And after according to actual conditions choosing associative mode, using genetic algorithm, the doubtful point of multiple no-manned plane collaboration is calculated and searches
Optimal trajectory.
7. a kind of unmanned plane according to claim 1 and having the multimachine multiple target emergency rescue flight path under Mechanism of Human-Computer Cooperation
Planing method, which is characterized in that the optimal trajectories for having man-machine coordination key point emergency management and rescue in the step 3 mainly pass through more
Following steps determine：
S301：The geographical location of each disaster affected people key point is obtained, the three-dimensional path planning algorithm in ant group algorithm, assessment are selected
Go out the optimal path between any two key point；And the distance of the optimal path between any two key point evaluated is turned
It is changed to the storage of matrix D 1；
S302：Each key point disaster affected people quantity situation is obtained, and is preserved in the form of numbers matrix C2；
S303：According to the Distance matrix D 1 of optimal path between each key point and each key point disaster affected people numbers matrix C2, ask
Obtain each key point disaster affected people Distance matrix D 2；Wherein, the path length of identical key point disaster affected people is 0；
S304：It is further combined with man-machine quantity, departure airport, manned amount, recycles greedy algorithm to respectively there is man-machine progress
Rescue task distributes, until all disaster affected peoples be assigned it is man-machine until, to there is man-machine coordination key point to answer obtain more
The optimal trajectory that first aid is helped.
8. a kind of unmanned plane according to claim 7 and having the multimachine multiple target emergency rescue flight path under Mechanism of Human-Computer Cooperation
Planing method, which is characterized in that the step S304 includes mainly：
S304a：According to having man-machine quantity and a departure airport, ratio sequence is carried out, and press ranking results, by having corresponding to it
Man-machine manned amount is denoted as Matrix Ch；
S304b：Calculate the inverse of each key point disaster affected people distance according to each key point disaster affected people Distance matrix D 2, then with
Equivalent value of the inverse as next disaster relief personnel is confirmed using greedy algorithm to there is man-machine rescue task to be allocated
Every frame has the man-machine disaster relief place that should be gone to and each disaster relief place that should rescue number；
S304c：The rescue task for having man-machine distribution according to every frame, according to liter after thering is man-machine rescue task voyage to sum on every frame
Sequence arranges, and updates the airborne people's moment matrix C of someone by ranking resultsh；
S304d：According to have it is man-machine rescued number, update and record each key point disaster affected people quantity situation；
S304e：Again according to each key point disaster affected people quantity situation after update, synchronized update simultaneously records each key point disaster affected people
Optimal path Distance matrix D 1 between numbers matrix C2, each disaster-stricken key point and disaster affected people Distance matrix D 2；
S304f：According further to data after update, cycle assignment has man-machine rescue task, until all disaster affected peoples are equal
Be assigned it is man-machine until.
9. according to a kind of any unmanned planes of claim 1-6 and thering is the multimachine multiple target under Mechanism of Human-Computer Cooperation is emergent to search
Rescue path planning method, which is characterized in that Google Earth flight simulations or SuperMap flight simulation programs are called, to rescuing
It helps prediction scheme and carries out simulated flight demonstration.
10. according to a kind of any unmanned planes of claim 1-6 and having the multimachine multiple target under Mechanism of Human-Computer Cooperation emergent
Search and rescue path planning method, which is characterized in that during planning the optimal trajectory, continue a journey according to respectively there is man-machine or unmanned plane
Can ability complete distribution task, correct its trajectory planning in time.
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