CN108613676B - A kind of unmanned plane and there is the emergency rescue path planning method under Mechanism of Human-Computer Cooperation - Google Patents
A kind of unmanned plane and there is the emergency rescue path planning method under Mechanism of Human-Computer Cooperation Download PDFInfo
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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 collaboration cover type search being carried out to disaster area, and obtains the geographical location of the doubtful point of disaster affected people；S2: the 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 track under the conditions of mountain area advises technology, in particular 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 technique
Mountain area major natural disasters occur after, 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 going on smoothly for work, to reduction 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 lower 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 been assembled from east China General Aviation Corp, Zhuhai helicopter branch company, 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 reasonable 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 subsequent supply troop's fleet configuration, search
It seeks rescue landing point, search that 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, improves aviation emergency
Rescue efficiency and the critical issue for ensureing rescue safety.
Summary of the invention
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 with have man-machine phase cooperate with multimachine multiple target collaboration search and rescue prediction scheme efficient formulation,
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 is the multimachine multiple target emergency rescue path planning method under Mechanism of Human-Computer Cooperation, feature exists
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: it according to the geographical location of the doubtful point of disaster affected people obtained in step 1, cooks up multiple no-manned plane and cooperates 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, multiple no-manned plane is carried out using double photoelectric nacelle unmanned planes cooperate with cover type search.
Wherein, double photoelectric nacelle unmanned planes, which refer to, is 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 of two photoelectric nacelles are contrary (direction of illumination differ 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 two 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: using Convex Polygon Domain division principle, each flight is high according to the disaster area contour map obtained
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 search, and record disaster affected people key point geographical location 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 map, the digital elevation model (DEM) in SuperMap output disaster area is utilized
File.
2) digital elevation model (DEM) file is converted into XYZ point using three-dimensional map processing software Global Mapper
Cloud format file, and save TXT file.
3) the XYZ point cloud format file that disaster area is loaded in Matlab, reacquires the numerical map of the region, and
The numerical map is encrypted using the interpolation method of bicubic interpolation.
4) by analysis disaster area personnel may locating 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, which refers to, is mounted on nobody for single airborne probe 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: obtaining doubtful geographic location of disaster affected people, selects the three-dimensional path planning algorithm in ant group algorithm,
Evaluate the optimal path between the doubtful point of any two；
S202: the optimal path evaluated according to step S201, 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 modes:
Mode one: the same airport of unmanned plane is set out and jump area is the doubtful point search mould of multiple no-manned plane collaboration of departure airport
Formula；
Mode 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
Mode three: different airports are set out and jump area is respective departure airport, but unmanned plane quantity it is fixed mostly without
Doubtful search pattern of man-machine coordination；
Mode four: different airports are set out and will land as respective departure airport, 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 more, it is main by walking as follows
It is rapid to determine:
S301: obtaining the geographical location of each disaster affected people key point, selects the three-dimensional path planning algorithm in ant group algorithm,
Evaluate the optimal path between any two key point；And by optimal path between any two key point evaluated away from
It is stored from matrix D 1 is converted to；
S302: obtaining each key point disaster affected people quantity situation, and is saved 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: being further combined with man-machine quantity, departure airport, manned amount, using greedy algorithm to respectively have it is man-machine into
Row rescue task distribution, to more be there is the optimal trajectory of man-machine coordination key point emergency management and rescue.
Further, the step S304 is specifically included that
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: calculating the inverse of each key point disaster affected people distance 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: having the rescue task of 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 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 updating, synchronized update and to record each key point disaster-stricken
Optimal path Distance matrix D 1 and disaster affected people Distance matrix D 2 between personnel amount Matrix C 2, each disaster-stricken key point；
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 program or SuperMap flight simulation program are called, to Rescue Plan
Carry out simulated flight demonstration.
It is further preferred that calling Google Earth flight simulation api routine, cover type search is cooperateed with to multiple no-manned plane
Emergency preplan carries out simulated flight demonstration；The doubtful point of SuperMap flight simulation demonstration multiple no-manned plane collaboration is called to search emergency 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 gone on smoothly, 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, so that sufficiently making rational planning for respectively has man-machine, unmanned plane flight track, 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 the disaster area periphery flight resource, condition, efficient and rational formulation multiple no-manned plane and more
There is the path planning method of multimachine multiple target while the emergency rescue prediction scheme carried out 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
The problems such as secondary injury caused by the reasons such as foot, plays significant promotion meaning to the development of China mountain area aviation emergency rescue technology.
2, multiple no-manned plane collaboration cover type is searched trajectory planning, more by 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 successively combines, by more
Unmanned plane cooperates with cover type trajectory planning, makes double photoelectricity unmanned planes search quickly, comprehensively to entire disaster area, 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 track rationally to be advised on each airport
It draws, so that realize has man-machine coordination accurately to rescue more.It effectively avoids caused by blindness and repeatability as 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, and the emergency that efficient determination and disaster area situation match searches prediction scheme.
4, further, have in man-machine coordination key point emergency rescue trajectory planning of the present invention more, it is ingenious to rescue
There are man-machine quantity and disaster affected people quantity mismatch problem to be converted into balanced assignment problem, using travelling salesman's solution throughway, and ties
Greedy algorithm is closed, to there is man-machine carry out cycle task appointment, there is man-machine flight rescue track on each airport of making rational planning for, economizes on resources
And ensure all disaster affected peoples by effective distribution rescue, 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 function are called, is 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 going on smoothly for task,
The safety for having ensured rescue personnel avoids accident from delaying rescue work progress.
Detailed description of the invention:
Fig. 1 is that a kind of unmanned plane of the present invention is advised with the multimachine multiple target emergency rescue track having under Mechanism of Human-Computer Cooperation
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 to be of the present invention more.
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 track schematic diagram under Figure 12 different mode.
Specific embodiment
Below with reference to test example and specific embodiment, the present invention is described in further detail.But this should not be understood
It is all that this is belonged to based on the technology that the content of present invention is realized for the scope of the above subject matter of the present invention is limited to the following embodiments
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: obtaining disaster area geography information and carries out assessment processing, and planning multiple no-manned plane collaboration cover type searches track,
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: it according to the geographical location of the doubtful point of disaster affected people obtained in step 1, cooks up multiple no-manned plane and cooperates with doubtful point
The optimal trajectory of search so that obtaining the doubtful point of multiple no-manned plane collaboration searches prediction scheme, and calls SuperMap flight simulation to demonstrate
After prediction scheme, implements multiple no-manned plane collaboration key point and search prediction scheme, the geographical location of acquisition 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 simulation 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；Specifically:
1) after obtaining SRTM digital elevation map, the digital elevation model (DEM) in SuperMap output disaster area is utilized
File.
2) digital elevation model (DEM) file is converted into XYZ using three-dimensional map processing software Global Mapper
Point cloud format file, and save TXT file.
3) the XYZ point cloud format file that disaster area is loaded in Matlab, reacquires 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 vertical height above sea level distribution situation locating 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 locating 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 software 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；Specific division methods are as follows:
1) the search subtask regional scope of same flight level divides: setting NvhiIn a flight level jth group without
The search width of man-machine formation is bij, region area to be searched corresponding to the height layer is area (Si), then ignoring turning
Can approximately it think in the case where time(VijIt forms into columns for this group of unmanned plane
Flying speed, TijThe time required to completing search mission, it should guarantee 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 are searched the cooperation of subtask region and are updated: due to the unmanned plane of different height layer flight
Search time is different, should turn to fly to not when other unmanned planes, which are formed into columns, completes search mission for the abundant use for guaranteeing unmanned plane
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 disaster affected people key point geographical location and each key point disaster affected people quantity situation:
Specifically, selecting double light as shown in figure 9, " multimachine oblique line formation search pattern " described in the step refers specifically to
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 carry out cover type search in disaster area overhead with " Z " font flight path, 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 and unmanned plane on the left of the unmanned plane of the course leftmost side 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
It is few that blind area is searched for as 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 to be unable 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,
Amendment track in time obtains final optimal trajectory planning.After recalling Google Earth simulation API demonstration prediction scheme, 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 arrange latitude coordinate postmenstruation for Matrix C 1, 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: obtaining doubtful geographic location of disaster affected people, selects the three-dimensional path planning algorithm in ant group algorithm,
Evaluate the optimal path between the doubtful point of any two；Specifically:
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 file 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 replace all 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 institute using the interpolation method of bicubic interpolation
Show).
2) the doubtful point of any two (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 way point coordinate of the step S201 optimal path 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 mode is chosen from following preset four kinds of modes:
Mode one: the same airport of unmanned plane is set out and jump area is the doubtful point search mould of multiple no-manned plane collaboration of departure airport
Formula；
Mode 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
Mode three: different airports are set out and jump area is respective departure airport, but unmanned plane quantity it is fixed mostly without
Doubtful search pattern of man-machine coordination；
Mode four: different airports are set out and will land as respective departure airport, but the quantity of unmanned plane is unfixed more
Unmanned plane cooperates with doubtful search pattern.
And record calculated result, including each unmanned plane way point information etc., to be formed more conveniently
The optimal trajectory that multiple no-manned plane cooperates with doubtful point to search.As shown in figure 12, the multiple no-manned plane collaboration to be cooked up under different mode
Doubtful point searches track schematic diagram.
Further, track 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 track, to obtain corresponding to the optimal trajectory that multiple no-manned plane under each mode cooperates with doubtful point
And search prediction scheme；After calling SuperMap flight simulation 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 records geographical location and the disaster-stricken people of each key point of disaster affected people 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, mainly include
Following steps:
S301: obtaining the geographical location of each disaster affected people key point, selects the three-dimensional path planning algorithm in ant group algorithm,
Evaluate the optimal path between any two key point；And by optimal path between any two key point evaluated away from
It is stored from matrix D 1 is converted to；Concrete operations are as follows:
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 file 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 replace all 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 institute 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: obtaining each key point disaster affected people quantity situation, and is saved 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: take the inverse of distance between each point as the equivalent value of next disaster relief personnel, and be 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
Benefit 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 rescue, which has man-machine quantity, capacity is respectively 5/5/5；B airport rescue has the man-machine quantity to be
6 framves, corresponding to manned amount is 8/8/8/8/8/8；There is man-machine ratio to be ranked up according to different airport rescues, and its is manned
Amount arranged in sequence obtains Matrix C h=[5,8,8,5,8,8,5,8,8]；
S304b: calculating the inverse of each key point disaster affected people distance 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: having the rescue task of 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 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 updating, synchronized update and to record each key point disaster-stricken
Optimal path Distance matrix D 1 and disaster affected people Distance matrix D 2 between personnel amount Matrix C 2, each disaster-stricken key point；
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, thus
Obtain having man-machine coordination key point emergency plan HSE more.And it is pre- to call SuperMap flight simulation to demonstrate the collaboration emergency management and rescue
Case ensures the smooth execution for having man-machine coordination key point rescue mission more.
Claims (7)
1. a kind of unmanned plane and having the multimachine multiple target emergency rescue path planning method under Mechanism of Human-Computer Cooperation, feature exists
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: it according to the geographical location of the doubtful point of disaster affected people obtained in step S1, cooks up multiple no-manned plane and doubtful point is cooperateed with to search
Target-seeking optimal trajectory, and implement the doubtful point of multiple no-manned plane collaboration according to the optimal trajectory and search prediction scheme, it is crucial to obtain disaster affected people
The geographical location of point 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 S2, rule
The optimal trajectory for more being had man-machine coordination key point emergency rescue is drawn, and implements have man-machine coordination pass more according to the optimal trajectory
Key point emergency rescue prediction scheme；
Multiple no-manned plane in the step S1 cooperates with cover type search, 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, is obtained
Obtain the drone flying height layer contour map in disaster area；
S102: according to the drone flying height layer contour map in the disaster area obtained, further combined with unmanned plane quantity, continue
Each flight level is divided into more by boat ability and unmanned plane formation search width using Convex Polygon Domain division principle
A sub- mission area；
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；
Moreover, carrying out multiple no-manned plane using double photoelectric nacelle unmanned planes cooperates with cover type search；Using single photoelectric nacelle unmanned plane
The doubtful point of multiple no-manned plane collaboration is carried out to search.
2. a kind of unmanned plane according to claim 1 and having the multimachine multiple target emergency rescue track 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 S2, main by such as lower section
Formula determines:
S201: obtaining doubtful geographic location of disaster affected people, selects the three-dimensional path planning algorithm in ant group algorithm, assessment
Optimal path between the doubtful point of any two out；
S202: the optimal path evaluated according to step S201, it is fixed 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 asked using genetic algorithm by position
Solution obtains the optimal trajectory that multiple no-manned plane cooperates with doubtful point to search.
3. a kind of unmanned plane according to claim 2 and having the multimachine multiple target emergency rescue track under Mechanism of Human-Computer Cooperation
Planing method, which is characterized in that in the step S202, unmanned plane quantity, departure place and jump area are further positioned into feelings
Condition is preset as following four kinds of modes:
Mode one: the same airport of unmanned plane set out and jump area be departure airport multiple no-manned plane cooperate with doubtful search pattern；
Mode two: same airport is set out and jump area airport is identical, but the jump area airport it is different from departure airport mostly without
Doubtful search pattern of man-machine coordination；
Mode 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；
Mode four: different airports set out and jump area 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.
4. a kind of unmanned plane according to claim 1 and having the multimachine multiple target emergency rescue track 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 S3 mainly pass through more
Following steps determine:
S301: obtaining the geographical location of each disaster affected people key point, selects the three-dimensional path planning algorithm in ant group algorithm, assessment
Optimal path between any two key point out；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: obtaining each key point disaster affected people quantity situation, and is saved in the form of numbers matrix C2；
S303: it according to the Distance matrix D 1 of optimal path between each key point and each key point disaster affected people numbers matrix C2, asks
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: being further combined with man-machine quantity, departure airport, manned amount, recycles greedy algorithm to respectively there is man-machine progress
Rescue task distribution, 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.
5. a kind of unmanned plane according to claim 4 and having the multimachine multiple target emergency rescue track under Mechanism of Human-Computer Cooperation
Planing method, which is characterized in that the step S304 is specifically included that
S304a: having man-machine ratio to be ranked up according to different airport rescues, and by its manned amount arranged in sequence, obtains Matrix Ch；
S304b: calculating 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 affected people 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: having the rescue task of man-machine distribution according to every frame, according to liter after having man-machine rescue task voyage to sum on every frame
Sequence arrangement, 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 updating, synchronized update simultaneously records each key point disaster affected people
Optimal path Distance matrix D 1 and disaster affected people Distance matrix D 2 between numbers matrix C2, each disaster-stricken key point；
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.
6. a kind of unmanned plane according to claim 1 to 3 is searched with the multimachine multiple target having under Mechanism of Human-Computer Cooperation emergency
Rescue path planning method, which is characterized in that Google Earth flight simulation demonstration multiple no-manned plane is called to cooperate with cover type search
Prediction scheme calls the doubtful point of SuperMap flight simulation demonstration multiple no-manned plane collaboration to search prediction scheme and have man-machine coordination key point to answer more
It is anxious to search and rescue prediction scheme.
7. a kind of unmanned plane according to claim 1 to 3 is searched with the multimachine multiple target having under Mechanism of Human-Computer Cooperation emergency
Rescue path planning method, which is characterized in that during planning the optimal trajectory, foundation respectively has man-machine or unmanned plane continuation of the journey energy
Can power complete distribution task, correct its trajectory planning in time.
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