CN103699135B - The flight path automatic planning in depopulated helicopter pesticide spraying farmland operation region - Google Patents
The flight path automatic planning in depopulated helicopter pesticide spraying farmland operation region Download PDFInfo
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Abstract
The invention discloses a kind of flight path automatic planning of depopulated helicopter pesticide spraying farmland operation region, the local optimum of planning arbitrary initial vertex, polygon farmland operation region, the local optimum S type trajectory planning of arbitrary original heading and arbitrary initial vertex, arbitrary original heading " returns " font flight path, " returns " font flight path find out global optimum S type flight path respectively and font flight path " returns " in global optimum from local optimum S type trajectory planning and local optimum.The present invention overcomes the deficiency of artificial planning flight path in Traditional Man operating type, make depopulated helicopter under the prerequisite meeting job task, various cost consumption factor can be reduced, improve spraying efficiency.
Description
Technical field
The present invention relates to depopulated helicopter trajectory planning field, particularly a kind of flight path automatic planning of depopulated helicopter pesticide spraying farmland operation region.
Background technology
Under the carrying forward vigorously of the Ministry of Agriculture, in recent years China ploughing, broadcast, Mechanization Level in receipts etc. had to show and improved, but pesticide spraying (particularly paddy rice pesticide spraying), substantially still traditional manual operation.China is a large agricultural country, agricultural pest how is effectively prevented to become one of important goal of China's agricultural production, particularly advocate energetically in country in the process promoting green agriculture, precision agriculture, be applicable to the low cost of China rural situation, accurately, the pesticide spraying machineryization of high-environmental and robotization become a requisite technology, and to utilize small-sized depopulated helicopter to carry out pesticide spraying be the optimal selection of pesticide spraying machineryization.
Under current China rural condition, using miniature self-service driving helicopter to spray insecticide is China, and particularly a kind of method of practicable is compared in southern area.Changsha agricultural sector in 2012 just signs and has purchased the unmanned plant protection aircraft of 50 frame for pesticide spraying operation.
Unmanned pesticide spraying helicopter not only speed is fast, and uses ultra-low volume pesticide spraying, saves agricultural chemicals and water resource, and reduce residues of pesticides and the environmental pollution of crops, operated from a distance can also reduce the injury to dispenser personnel.Be adapted to various landform, meet city's road present situation, join a table top hired car and just can realize trans-regional operation.
At present, the civilian depopulated helicopter of China is in Rapid development stage, and the utilization rate of civilian depopulated helicopter is more and more higher, especially at agriculture field, uses helicopter greatly can improve operating efficiency.But due to the manipulated distance of depopulated helicopter, cause cannot judging concrete state of flight, as heading, flying distance etc. with human eye.Lack the method for the flight track of depopulated helicopter in farmland operation region being carried out to rationally effective planning, cause flight path selected by operating personnel and non-optimal; And drain spray caused by the collimation error, spray by mistake, respray, spraying efficiency is reduced, and operating cost raises.
Unmanned vehicle, in the process of finishing the work, needs the task process completing oneself to how effectively, safely to plan, so-called mission planning that Here it is.In task planning process, most important, be also the most complicated be exactly cook up a flight track completed required for aerial mission, i.e. unmanned vehicle trajectory planning for unmanned vehicle.
Unmanned aerial vehicle flight path planning is exactly consider various factors, as: time of arrival, flying distance, fuel consumption, threat and flight range etc., for unmanned plane cooks up an optimum, or the most satisfied flight track, to ensure satisfactorily to complete aerial mission.
Depopulated helicopter trajectory planning has multiple method, as A* search procedure, Voronoi nomography, genetic algorithm, ant group algorithm, particle swarm optimization algorithm and heuristic search etc.A* algorithm is a kind of optimum heuristic searching algorithm of classics, is generally used for solving static programming problem, has a wide range of applications in path planning and graph search.This algorithm, by heuristic information guiding search, reaches the object reducing hunting zone, improve computing velocity.When utilizing traditional A* algorithm to carry out flight path search, usually planning environment is expressed as the form of grid, then finds minimum cost flight path according to predetermined cost function.The method, to each grid cell calculation cost that may arrive of current location, then selects the grid cell of lowest costs to add search volume to explore.This new grid cell adding search volume is used to again produce more possible path.Voronoi figure is a kind of important geometry in computing machine geometry.McLain and Beard etc. propose a kind of multi-aircraft based on Voronoi figure and work in coordination with path planning method.First by known local radar or threat structure Voronoi figure, the border of Voronoi figure is exactly all flight paths flown, and then provides the weights on these borders, final search optimal trajectory.Genetic algorithm is the computation model of the simulation natural selection of Darwinian evolutionism and the biological evolution process of genetic mechanisms, is a kind of method by simulating nature evolutionary process search optimum solution.The general step carrying out trajectory planning by genetic algorithm has: a) encode to flight path; B) suitable route evaluation function is constructed; C) genetic operator being suitable for trajectory planning is selected; D) calculate and finely tune operator to obtain last solution.Ant group algorithm carrys out realizing route search by the information interchange of ant with mutual cooperation, and this algorithm has good versatility and robustness.The process of ant group algorithm searching route is: a) pheromones of all Nodes on initialization flight range figure, forms initial information prime matrix; B) M ant is positioned at starting point A and waits for and setting out; C) every ant to select on grid chart according to node transition rule more lower, finally arrive impact point, form a feasible air route; D) calculate the objective function in the feasible air route of each ant, preserve optimal air line solution; E) according to objective function, adjust according to the pheromones of pheromones adjustment criterion to each point; F) check optimum solution, judge whether the adjustment will carrying out information evaporation prime factor P, if need to adjust accordingly by certain rule; G) judge whether to meet iterated conditional (namely whether reaching iterations or the minimum target function of setting), if meet, then complete search; If do not meet, then return step b), repeat, until meet iterated conditional.Heuristic search is exactly that search in state space is assessed the position that each is searched for, and obtains best position, then carries out searching for until target from this position.Searching route meaningless in a large number can be omitted like this, improve efficiency.In heuristic search, be very important to the appraisal of position.Have employed different appraisals and can have different effects.
Traditional heuristic search and other method for searching path, in the shortest reachable path of process, flight optimization flight path (time is short, oil consumption is low, security high), avoiding obstacles etc., have respective advantage, but be not but all suitable for the trajectory planning at farmland operation.This is because the singularity of farmland operation determines.Be mainly manifested in:
A) first depopulated helicopter is to cover whole farmland operation regions at the flight path of farmland operation, and this shortest or flight optimization path just with traditional is different.
B) on the basis of the whole operating area of satisfied covering, further consider the flight path in whole region and flying method, namely how to fly and operating efficiency can be made the highest.
C) also will consider oil consumption and residue pesticide volume in flight course, when oil consumption or pesticide volume deficiency, needs proceed operation after making a return voyage and adding, and the distance of its round base station also must calculate in whole planing method.
Traditional heuristic search algorithm is the object of the invention is to be applied in the farmland operation trajectory planning of depopulated helicopter.
The explanation of nouns of using in the present invention is as follows:
Trajectory planning: aircraft can meet aerial mission, and meet the flight path of constraint condition.
Depopulated helicopter: pilotless helicopter.
S type flight track: refer to that depopulated helicopter carries out pesticide spraying along prearranged heading flight, arrive on rear side of frontier point and fly a segment distance, then fly in the opposite direction by with former boat, form bending S type flight track thus.
" return " font flight track: refer to that depopulated helicopter carries out pesticide spraying along prearranged heading flight, arrive and turn round a little, hovering turn, continue flight forward along next course, form " returning " font flight track thus.
Base station: be a base station, when depopulated helicopter fuel oil or agricultural chemicals deficiency, can return to base station is continuation operation of setting out again after depopulated helicopter adds fuel oil, agricultural chemicals.
Summary of the invention
Technical matters to be solved by this invention is, not enough for prior art, a kind of flight path automatic planning of depopulated helicopter pesticide spraying farmland operation region is provided, depopulated helicopter is planned automatically at farmland operation region flight track, generate global optimum S type flight track and " returning " font flight track, overcome the deficiency of artificial planning flight path in Traditional Man operating type, make depopulated helicopter can under the prerequisite meeting job task, reduce various cost consumption factor, improve spraying efficiency.
For solving the problems of the technologies described above, the technical solution adopted in the present invention is: a kind of flight path automatic planning of depopulated helicopter pesticide spraying farmland operation region, and the method is:
1) utilizing Grid Method digitizing polygon farmland operation region, is several grids by polygon farmland operation Region dividing; Described polygon farmland operation region number of vertices is n;
2) for node index matrix is set up in the polygon farmland operation region after digitizing, be a node with each grid, by the terrain information of each grid stored in described node index matrix;
3) following cost function h (n) is defined:
Wherein,
for depopulated helicopter to fly from present node the velocity vector of next destination node; I is that depopulated helicopter flies nonstop to course vector set; J is that the flight of depopulated helicopter side is gathered to vector; K is that the oblique flight of depopulated helicopter is gathered to vector;
4) inspiration memory type method is utilized to carry out the search of depopulated helicopter flight path, the optimum reference flight flight path of font " is returned " in the local of the optimum reference flight flight path of local S type and any original heading, all initial vertexs, polygon farmland operation region that obtain any original heading, all initial vertexs, polygon farmland operation region, and wherein the optimum reference flight flight path of local S type and the optimum reference flight flight path of local " returning " font are respectively 2n bar;
5) cost value of the optimum reference flight flight path of 2n bar local S type in described step 4) and the cost value of the optimum reference flight flight path of 2n bar local " returning " font is solved respectively; The optimum reference flight flight path of local S type minimum for cost value in the optimum reference flight flight path of 2n bar local S type is decided to be global optimum S type flight path; Local minimum for cost value in 2n bar local " returning " font optimum reference flight flight path " is returned " font optimum reference flight flight path to be decided to be global optimum and " to return " font flight path.
The acquisition methods of the optimum reference flight flight path of local S type is:
1) select summit, one, polygon farmland operation region to select a course as original heading as initial vertex, using with the nearest node in initial vertex as present node.
2) all nodes that search is adjacent with the present node of unmanned helicopter flight, find the node meeting constraint condition, will meet the adjacent node of constraint condition as next possible destination node; Meet constraint condition to refer to: in the node adjacent with present node, find the numerical value that each adjacent node is corresponding in node index matrix, namely the minimum adjacent node of numerical value meets constraint condition;
3) judge whether present node is turning point, if so, then calculate the velocity vector from present node to next possible destination node successively, selection and the current minimum node of course vector angle of flying nonstop to, as next destination node, enter step 6); If present node is not turning point, then enter step 4);
4) cost function h (n) is utilized to calculate from present node to the cost value of next possible destination nodes all;
5) the possible destination node selecting cost value minimum is as next destination node;
6) value of obtained next destination node in described node index matrix is added 1, represent that this node is visited once, and this node is put in flight path sequence node table;
7) using obtained next destination node as the present node circulated next time, repeat step 2) ~ step 6), until traveled through all nodes in the polygon farmland operation region after digitizing, obtained an optimum reference flight flight path of local S type;
8) step 1) ~ 7 are repeated), traversal all summits, polygon farmland operation region, cook up the optimum reference flight flight path of local S type on each summit respectively, obtain the optimum reference flight flight path of 2n bar local S type.
The acquisition methods locally " returning " the optimum reference flight flight path of font is:
1) select summit, one, polygon farmland operation region to select a course as original heading as initial vertex, using with the nearest node in initial vertex as present node.
2) all nodes that search is adjacent with the present node of unmanned helicopter flight, find the node meeting constraint condition, will meet the adjacent node of constraint condition as next possible destination node; Meet constraint condition to refer to: in the node adjacent with present node, find the numerical value that each adjacent node is corresponding in node index matrix, namely the minimum adjacent node of numerical value meets constraint condition;
3) judge whether present node is turning point, if, then calculate the velocity vector from present node to next possible destination node successively, select with the current minimum node of course vector angle of flying nonstop to as next destination node, and course vector set I is flown nonstop in renewal, side flight gathers J to vector, and oblique flight gathers K to vector, enters step 6); If present node is not turning point, then enter step 4);
4) cost function h (n) is utilized to calculate from present node to the cost value of next possible destination nodes all;
5) the possible destination node selecting cost value minimum is as next destination node;
6) value of obtained next destination node in described node index matrix is added 1, represent that this node is visited once, and this node is put in flight path sequence node table;
7) using obtained next destination node as the present node circulated next time, repeat step 2) ~ step 6), until traveled through all nodes in the polygon farmland operation region after digitizing, obtain a local and " returned " the optimum reference flight flight path of font;
8) step 1) ~ 7 are repeated), traversal all summits, polygon farmland operation region, the optimum reference flight flight path of font " is returned " in the local cooking up each summit respectively, obtains the optimum reference flight flight path of 2n bar local " returning " font.
The acquisition methods of global optimum S type flight path is:
1) calculate in the optimum reference flight flight path of each local S type, depopulated helicopter fly nonstop to distance x
p1, side flies distance x
p5, takeoff point is apart from track initiation point distance x
p2, abort point is apart from the distance x of base station
p3; And depopulated helicopter operation complete after turn back to the distance x of depopulated helicopter operating personnel position
p4;
2) calculate the cost value of the optimum reference flight flight path of each local S type, wherein the computing formula of the cost value f (p) of local S type optimum reference flight flight path p is:
wherein w
1the coefficient of distance sum is flown nonstop to, w for depopulated helicopter is all
2for all sides of depopulated helicopter fly the coefficient of distance sum, w
1+ w
2=1;
3) optimum for local S type minimum for cost value reference flight flight path is decided to be global optimum S type flight path.
The acquisition methods that font flight path " returns " in global optimum is:
1) calculating each local " returns " in the optimum reference flight flight path of font, depopulated helicopter fly nonstop to distance x
q1, number of turns t, takeoff point is apart from track initiation point distance x
q2, abort point is apart from the distance x of base station
q3; And depopulated helicopter operation complete after turn back to the distance x of depopulated helicopter operating personnel position
q4;
2) calculate the cost value that the optimum reference flight flight path of font " is returned " in each local, the computing formula of wherein " returning " the cost value f (q) of font optimum reference flight flight path q is:
3) local minimum for cost value " is returned " the optimum reference flight flight path of font and be decided to be global optimum S type flight path
Compared with prior art, the beneficial effect that the present invention has is: the present invention can plan at farmland operation region flight track automatically to depopulated helicopter, generate global optimum S type flight track and " returning " font flight track, operator can according to operating habit and operating area condition, pesticide spraying operation is carried out in any selection wherein a kind of trajectory planning, method of the present invention overcomes the deficiency of artificial planning flight path in Traditional Man operating type, can under the prerequisite meeting job task, reduce various cost consumption factor, improve spraying efficiency; Present invention achieves arbitrary initial vertex, any convex polygon farmland operation region, the local optimum S type trajectory planning of arbitrary original heading and local optimum and " return " font trajectory planning; The present invention has taken into full account depopulated helicopter cost factor such as flying distance, the number of times that turns round, pesticide volume, amount of fuel in operating area, based on cost price function minimization principle, " return " font flight path from local optimum S type flight path and local optimum, select global optimum's flight path, calculate simple, easily realize; The present invention extends to the farmland of arbitrary shape, comprises convex polygon and concave polygon, and wherein concave polygon may be partitioned into multiple convex polygon, and then uses method of the present invention to carry out trajectory planning to each convex polygon farmland operation region.
Accompanying drawing explanation
Fig. 1 is region, rectangle farmland ABCD schematic diagram in the embodiment of the present invention;
Fig. 2 is postrotational farmland operation region display figure in the embodiment of the present invention;
Fig. 3 is the farmland operation area schematic in the embodiment of the present invention after rasterizing;
Fig. 4 is that embodiment of the present invention interior joint index matrix sets up schematic diagram;
Fig. 5 is the adjacent node schematic diagram of present node in the embodiment of the present invention;
Fig. 6 is next possible destination node schematic diagram in the embodiment of the present invention;
Fig. 7 is the present node figure of next step circulation in the embodiment of the present invention;
Fig. 8 is that in the embodiment of the present invention, next destination node value adds the node index matrix after 1;
Fig. 9 is the S type track line that the embodiment of the present invention obtains;
Figure 10 is the S type track line of the former reference frame of the embodiment of the present invention;
Figure 11 is " returning " font flight path of the former reference frame of the embodiment of the present invention;
Figure 12 is depopulated helicopter takeoff point S point, base station M point, operation complete and make a return voyage an E point all not at the flight path schematic diagram one of same point;
Figure 13 is depopulated helicopter takeoff point S point, base station M point, operation complete and make a return voyage an E point all not at the flight path schematic diagram two of same point;
Figure 14 is global optimum of the present invention trajectory planning process flow diagram;
Figure 15 is the present invention local S type optimal trajectory planning flow chart;
Figure 16 is the present invention local " returning " font optimal trajectory planning flow chart.
Embodiment
The inventive method is as follows:
(1) local optimum S type trajectory planning
1. digitizing farmland operation region
Digital map is the primary information resource carrying out trajectory planning, and research numerical map great majority adopt Grid Method both at home and abroad, and landform is divided into equally spaced grid, and grid distance is chosen according to required actual conditions.
The present invention utilizes Grid Method to farmland operation zone digit.Namely be the farmland of ((x, y) | 0≤x≤a, 0≤y≤b) for region, x-axis and y-axis be divided into junior unit lattice according to given spacing, obtain the region, farmland of discretize.
Without loss of generality, for region, arbitrary polygon farmland, suppose that its number of vertices is n, the starting point that so can be used as trajectory planning just equals n.And for each initial vertex, for ensureing that flight path can cover whole region, its best original heading prolongs its right and left rectilinear flight.Therefore two headings are had to supply search for each initial vertex.Then a total 2n S type potential track needs search.
2. trajectory planning initialization
Initialization content comprises:
1) create the terrain information of numerical map, divide operating area and non-operating area.
Specific implementation is, for the Digital Region created sets up node index matrix (NodeList).Each grid is exactly a node (later all representing with node), and store the terrain information of each grid cell in index matrix, operating area represents with 0, and non-operating area # represents.So just establish the node index matrix that stores terrain information.What node index value was used for representing present node visits priority, and it is higher to be worth less priority.Node index matrix has memory capability, and after a node is visited in search procedure, the value in its index matrix is by+1, and access privileges will decline.After a node of operating area is visited, its value just becomes 1 from 0, and at this moment the priority of this node declines.Realize in search procedure with this, do not visit node and have the limit priority of visiting all the time, all nodes that the search of guide and elicitation formula can travel through in operating area, make the flight path of planning meet the primary demand of farmland operation.
2) for heuristic information is specified in search
In heuristic search, be very important to the appraisal of position.Have employed different appraisals and can have different effects.Appraisal in inspiration represents with evaluation function, as: f (n)=g (n)+h (n).Wherein f (n) is the evaluation function of node n, and g (n) is from start node to the actual cost of n node in state space, and h (n) is the estimate cost from n to destination node optimal path.Here mainly h (n) embodies the heuristic information of search, because g (n) is known.As h (n) >>g (n), can g (n) be omitted, thus raise the efficiency.
The flight path of depopulated helicopter operating area is all nodes had to pass through in operating area, with ensuring coverage All Jobs region, therefore each flight path is from starting point to the end of job, and we need to specify cost function h (n) from current point to next impact point.
Before definition cost function, first need to understand several flying method.Flying method during depopulated helicopter operation has: fly nonstop to, side flies, tiltedly fly.Consider the manipulation of physical complexity of depopulated helicopter, the priority orders of this three is from high to low successively.So in practice, should adopt to fly nonstop to as far as possible and carry out operation, only arrival border or when needing to turn round just employing side fly or tiltedly fly.Therefore, adopt different flying methods from present node to next destination node, required cost is also different.
Definition depopulated helicopter fly nonstop to course vector set be combined into I(gather I comprise all fly nonstop to course vector), side flight is combined into J to vector set, and oblique flight is combined into K to vector set.From present node to the speed of next destination node be vector
because x-axis overlaps with original heading, thus I be exactly the vector of unit length parallel with x-axis set (such as vector (1,0) just belong to I, (-1,0) also I is belonged to), J is exactly the set of the vector of unit length parallel with y-axis, and K is exactly the vector of unit length set being parallel to straight line y=x.
Definition
That is from present node to the velocity vector of next destination node
fly nonstop to course vector set I if belonged to, so required cost is 1, is least estimated cost; If belong to side flight to gather J to vector, so required cost is 2; If belong to oblique flight to gather K to vector, so required cost is 3.Such definition is to meet with practical operation.Also embody the priority orders of visiting next destination node simultaneously, can visit toward the direction that estimate cost is minimum.
3. utilize and inspire memory type algorithm to carry out flight path search, obtain 2n bar S type local optimum reference flight flight path.Concrete methods of realizing is (see Figure 15):
Step1. select summit as initial vertex and select a course as original heading, using with the nearest node in initial vertex as present node.
Step2. all nodes that search is adjacent with present node, find the node meeting constraint condition, may destination node as next step using qualified adjacent node.Constraint condition is the adjacent node that in node index matrix, value is minimum.
Step3. judge whether present node is turning point.If turning point, then calculate the velocity vector from present node to next possibility node successively
select with the current minimum node of course vector angle of flying nonstop to as next destination node.Perform Step6.
If not turning point, jump to Step4.
Step4., after determining possibility destination node, all cost value f (n) from present node to next possibility node are calculated.F (n)=h (n), h (n) is by may the velocity vector of node to next from present node
determine.
Step5. f (n) is sorted, the next destination node of the conduct selecting f (n) value minimum.
Step6. using the present node that the next destination node obtained circulates as next step, by the value+1 in its node index matrix, represent that this node is visited once.And put in flight path sequence node table.
Step7. repeat Step2 to Step6, find next track points, until traveled through all nodes in operating area, search procedure has completed.Obtain an optimum reference flight flight path of local S type.
Step8. step 1) ~ 7 are utilized), traversal all summits, polygon farmland operation region, cook up the optimum reference flight flight path of local S type on each summit respectively, obtain the optimum reference flight flight path of all possible 2n bar local S type.
(2) local optimum " returns " font trajectory planning
Digitizing farmland operation region and the trajectory planning initialization of " returning " font trajectory planning and S type trajectory planning are identical.Difference is compared with S type, and depopulated helicopter is meeting hovering turn after arrival turning point, changes it and flies nonstop to course.Therefore, utilize that to inspire memory type algorithm to carry out flight path search procedure different from S type.Be described mainly for difference below.
3. utilize and inspire memory type algorithm to carry out flight path search, obtain the optimum reference flight flight path of " a returning " font of any original heading, any initial vertex.Concrete methods of realizing is (see Figure 16):
Step1. select summit as initial vertex and select a course as original heading, using with the nearest node in initial vertex as present node.
Step2. all nodes that search is adjacent with present node, find the node meeting constraint condition, may destination node as next step using qualified adjacent node.Constraint condition is the adjacent node that in node index matrix, value is minimum.
Step3. judge whether present node is turning point.If turn round a little, then calculate successively from present node to next may node velocity vector
select with the current minimum node of course vector angle of flying nonstop to as next destination node.Perform Step6, and course vector set I is flown nonstop in renewal, side flight gathers J to vector, and oblique flight gathers K to vector.Wherein gather I comprise and determine the velocity vector of destination node to present node from next
parallel all vector of unit length, side flight comprises all vector of unit length vertical with set I to vector set J, and oblique flight comprises all vector of unit length with set I vector angle and 45 degree to vector set K.
If not turning point, jump to Step4.
Step4., after determining possibility destination node, all cost value f (n) from present node to next possibility node are calculated.F (n)=h (n), h (n) is by may the velocity vector of node to next from present node
determine.
Step5. f (n) is sorted, the next destination node of the conduct selecting f (n) value minimum.
Step6. using the present node that the next destination node obtained circulates as next step, by the value+1 in its node index matrix, represent that this node is visited once.And put in flight path sequence node table.
Step7. repeat step Step2 to step Step6, find next track points, until traveled through all nodes in operating area, search procedure has completed.Obtain " returning " font local optimum reference flight flight path.
Step8. step 1) ~ 7 are utilized), traversal all summits, polygon farmland operation region, the optimum reference flight flight path of font " is returned " in the local cooking up each summit respectively, obtains the optimum reference flight flight path of all possible 2n bar local " returning " font.
(3) global optimum S type flight path and " returning " font trajectory planning (see Figure 14)
Global optimum's trajectory planning, on the basis of each local optimum, need consider various Cost Problems, S type flight path is discussed below respectively and plans with the global optimum of " returning " font flight path.
1. global optimum S type trajectory planning
Global optimum S type flight path needs the cost factor considered to have: depopulated helicopter in operating area fly nonstop to distance, side flies distance, depopulated helicopter takeoff point is apart from the distance of certain track initiation point, depopulated helicopter because the not enough abort position of fuel oil or agricultural chemicals is far from the distance of base station, and depopulated helicopter operation complete after the distance that returns.For considering above various factors, a kind of global optimum S type flight path decision-making technique need be proposed.The method is used for judging to select global optimum's flight path from all local optimum S type flight paths.
Concrete methods of realizing is:
Step1. calculate in each flight path p, depopulated helicopter fly nonstop to distance x
p1, side flies distance x
p5; Takeoff point is apart from track initiation point distance x
p2; Abort point is apart from the distance x of base station
p3; And depopulated helicopter operation complete after the distance x that returns
p4.
Step2. calculate the cost value f (p) of each flight path p, the computing formula of f (p) is
wherein w
1for all coefficients flying nonstop to distance sum, w
2for all sides fly the coefficient of distance sum, w
1+ w
2=1.
Step3. to all cost value f (p) sequences, what cost value was minimum is global optimum S type flight path.
2. font trajectory planning " returns " in global optimum
Global optimum " return " font flight path need consider cost factor have: depopulated helicopter in operating area flying distance, turn round number of times; Depopulated helicopter takeoff point is apart from the distance of certain track initiation point; Depopulated helicopter is because the not enough abort position of fuel oil or agricultural chemicals is far from the distance of base station; The distance returned after depopulated helicopter operation completes.For considering above various factors, a kind of global optimum need be proposed and " return " font flight path decision-making technique.The method is used for " returning " font flight path from all local optimums judging to select global optimum's flight path.
Concrete methods of realizing is:
Step1. calculate in each flight path p, depopulated helicopter fly nonstop to distance x
p1, number of turns t; Takeoff point is apart from track initiation point distance x
p2; Abort point is apart from the distance x of base station
p3; And depopulated helicopter operation complete after the distance x that returns
p4.
Step2. calculate the cost value f (p) of each flight path p, the computing formula of f (p) is
wherein w
1for all coefficients flying nonstop to distance sum, w
2for the coefficient of number of turns, w
1+ w
2=1.
Step3. to the sequence of all cost value f (p), what cost value was minimum be global optimum " returns " font flight path.
So far, just achieve depopulated helicopter optimum flight track planning in farmland operation region.
Below in conjunction with drawings and Examples, the technical program is described in further details.
(1) local optimum S type trajectory planning
Rectangle farmland region ABCD as shown in Figure 1, depopulated helicopter can select arbitrary summit to be initial vertex, and with arbitrary summit be connected two limits for flying original heading.The following describes and how to obtain all 8 the local optimum S type trajectory plannings of rectangle farmland region ABCD.
1. digitizing farmland operation region
Utilize Grid Method to farmland operation zone digit.Namely be the farmland of ((x, y) | 0≤x≤a, 0≤y≤b) for region, x-axis and y-axis be divided into junior unit lattice according to given spacing, obtain the region, farmland of discretize, spacing size is determined by depopulated helicopter wide cut of spraying insecticide.At this, x-axis and y-axis are divided into junior unit lattice according to the spacing that unit head is 5 meters, as shown in Figure 3.
2. trajectory planning initialization
Initialization content comprises:
1) create the terrain information of numerical map, divide operating area and non-operating area.
Specific implementation is, for the Digital Region created sets up node index matrix (NodeList).Each grid is exactly a node (later all representing with node), and store the terrain information of each grid cell in index matrix, operating area represents with 0, and non-operating area # represents.So just establish the node index matrix that stores terrain information.
2) for heuristic information is specified in search
Definition depopulated helicopter fly nonstop to course vector set be combined into I(gather I comprise all fly nonstop to course vector), side flight is combined into J to vector set, and oblique flight is combined into K to vector set.From present node to the speed of next destination node be vector
Definition
That is, from present node to next destination node velocity vector
fly nonstop to course set I if belonged to, so required cost is 1, is least estimated cost.By that analogy.
3. utilize and inspire memory type algorithm to carry out flight path search, obtain all 8 local S types of rectangle farmland region ABCD optimum with reference to flight track.Concrete methods of realizing is:
Step1. select summit A as initial vertex and select a course AB as original heading, using with the nearest node in initial vertex as present node.
Step2. all nodes that search is adjacent with present node (the black round dot in Fig. 5 represents), find the node meeting constraint condition, may destination node as next step using qualified adjacent node.Constraint condition is the adjacent node that in node index matrix, value is minimum.
According to Step2, as shown in Figure 6, three black round dots of band numbering are next step may impact point for next step possibility destination node obtained.
Step3. judge whether present node is turning point.If turning point, then calculate the velocity vector from present node to next possibility node successively
select with the current minimum node of course vector angle of flying nonstop to as next destination node.Perform Step6.
If not turning point, jump to Step4.
Step4., after determining possibility destination node, all cost value f (n) from present node to next possibility node are calculated.F (n)=h (n), h (n) is by may the velocity vector of node to next from present node
determine.
According to Step4, calculate the velocity vector from present node point to three black color dots of band numbering respectively
according to velocity vector
calculate the cost value arriving each possibility impact point.The cost value of to be the cost value of 1, No. 2 round dots be 2, No. 3 round dots of the cost value to No. 1 round dot is 3.
Step5. f (n) is sorted, the next destination node of the conduct selecting f (n) value minimum.
Can determine that No. 1 round dot is next destination node according to Step5.
Step6. using the present node that the next destination node obtained circulates as next step, by the value+1 in its node index matrix, represent that this node is visited once (as shown in Figure 8).And put in flight path sequence node table.
As shown in Figure 7, No. 1 round dot has become next step present node circulated.
Step7. repeat Step2 to Step6, find next track points, until traveled through all nodes in operating area, search procedure has completed.Obtain an optimum reference flight flight path of local S type.
Obtain taking A as initial vertex AB the optimum reference flight track line of the S type being original heading according to Step7.
Step8. step 1) ~ 7 are utilized), travel through four summits A, B, C and the D in rectangle farmland operation region successively, cook up the optimum reference flight flight path of local S type on each summit respectively, obtain all possible 8 optimum reference flight flight paths of local S type.
Fig. 9 shows the whole process of search, and finally obtains a S type track line.In region, black round dot represents the point in flight path sequence node table.
(2) local optimum " returns " font trajectory planning
Its process is described consistent with (one), and after just arriving turning point in the 3rd step, need change and fly nonstop to course, its net result as shown in figure 11.
(3) global optimum S type flight path and " returning " font trajectory planning
1. global optimum S type trajectory planning
Global optimum S type flight path needs the cost factor considered to have: depopulated helicopter in operating area fly nonstop to distance, side flies distance, depopulated helicopter takeoff point is apart from the distance of certain track initiation point, depopulated helicopter because the not enough abort position of fuel oil or agricultural chemicals is far from the distance of base station, and depopulated helicopter operation complete after the distance that returns.For considering above various factors, a kind of global optimum S type flight path decision-making technique need be proposed.This system, method is used for judging to select global optimum's flight path from all local optimum S type flight paths.
This system concrete methods of realizing is:
Step1. calculate in each S type local optimum flight path of rectangle ABCD p, depopulated helicopter fly nonstop to distance x
p1, side flies distance x
p5; Takeoff point is apart from track initiation point distance x
p2; Abort point is apart from the distance x of base station
p3; And depopulated helicopter operation complete after the distance x that returns
p4.
Below with summit A for starting point, AB is the S type flight path of original heading is example, calculates its cost value f (p).
Suppose depopulated helicopter takeoff point S point, base station M point, operation completes an E point that makes a return voyage all not in same point, as shown in figure 12.
First calculate in this flight path, depopulated helicopter fly nonstop to distance x
p1, side flies distance x
p5.X
p1equal all in flight path and fly nonstop to line segment sum.X
p5equal all sides fly line section sum in flight path.
Calculate takeoff point S again apart from track initiation point A
1distance x
p2equal line segment SA
1length; Abort point is apart from the distance x of base station M
p3equal line segment MA
22 times of length; Apart from the distance x of reentry point E after operation completes
p4equal line segment EA
3length.
Step2. calculate the cost value f (p) of this flight path, the computing formula of f (p) is
wherein w
1for all coefficients flying nonstop to distance sum, w
2for all sides fly the coefficient of distance sum, w
1+ w
2=1.
Coefficient w
1, w
2the ratio calculation rapidly spent according to the speed of flying nonstop to and side out
w
1=0.1，w
2=0.9
The cost value f (p) of this flight path can be calculated thus.
Step3. repeat above step, just can calculate the cost value of each local optimum S type flight path, to all cost value f (p) sequences, what cost value was minimum is global optimum S type flight path.
Thus, the planning of global optimum S type operation reference track is achieved.
2. font trajectory planning " returns " in global optimum
Global optimum " return " font flight path need consider cost factor have: depopulated helicopter in operating area flying distance, turn round number of times; Depopulated helicopter takeoff point is apart from the distance of certain track initiation point; Depopulated helicopter is because the not enough abort position of fuel oil or agricultural chemicals is far from the distance of base station; The distance returned after depopulated helicopter operation completes.For considering above various factors, the present invention proposes a kind of global optimum and " returns " font flight path decision-making technique.The method is used for " returning " font flight path from all local optimums judging to select global optimum's flight path.
Concrete methods of realizing is:
Step1. calculating each local optimum of rectangle ABCD " returns " in font flight path p, depopulated helicopter fly nonstop to distance x
p1, number of turns t; Takeoff point is apart from track initiation point distance x
p2; Abort point is apart from the distance x of base station
p3; And depopulated helicopter operation complete after the distance x that returns
p4.
Below with summit A for starting point, AB is " returning " font flight path of original heading is example, calculates its cost value f (p).
Suppose depopulated helicopter takeoff point S point, base station M point, operation completes an E point that makes a return voyage all not in same point, as shown in figure 13.
First calculate in this flight path, depopulated helicopter fly nonstop to distance x
p1, number of turns t.X
p1equal all in flight path and fly nonstop to line segment sum.T equals all turning point number sums in flight path (4 black round dots of band numeral number (1 ~ 4) are turning point).
Calculate takeoff point S again apart from track initiation point A
1distance x
p2equal line segment SA
1length; Abort point is apart from the distance x of base station M
p3equal line segment MA
22 times of length; Apart from the distance x of reentry point E after operation completes
p4equal line segment EA
3length.
Step2. calculate the cost value f (p) of this flight path, the computing formula of f (p) is
wherein w
1for all coefficients flying nonstop to distance sum, w
2for the coefficient of number of turns, w
1+ w
2=1.
Coefficient w
1, w
2according to flying nonstop to the ratio calculation of operation and cornering operation complexity out
w
1=0.25，w
2=0.75
The cost value f (p) of this flight path can be calculated thus.
Step3. repeat above step, just can calculate the cost value that each local optimum " returns " font flight path, to the sequence of all cost value f (p), what cost value was minimum be global optimum " returns " font flight path.
Thus, achieve global optimum and " return " planning of font operation reference track.
Claims (4)
1. the flight path automatic planning in depopulated helicopter pesticide spraying farmland operation region, is characterized in that, the method is:
1) utilizing Grid Method digitizing polygon farmland operation region, is several grids by polygon farmland operation Region dividing; Described polygon farmland operation region number of vertices is n;
2) for node index matrix is set up in the polygon farmland operation region after digitizing, be a node with each grid, by the terrain information of each grid stored in described node index matrix;
3) following cost function h (n) is defined:
Wherein,
for depopulated helicopter to fly from present node the velocity vector of next destination node; I is that depopulated helicopter flies nonstop to course vector set; J is that the flight of depopulated helicopter side is gathered to vector; K is that the oblique flight of depopulated helicopter is gathered to vector;
4) inspiration memory type method is utilized to carry out the search of depopulated helicopter flight path, the optimum reference flight flight path of font " is returned " in the local of the optimum reference flight flight path of local S type and any original heading, all initial vertexs, polygon farmland operation region that obtain any original heading, all initial vertexs, polygon farmland operation region, and wherein the optimum reference flight flight path of local S type and the optimum reference flight flight path of local " returning " font are respectively 2n bar;
5) solve described step 4 respectively) in the cost value of the optimum reference flight flight path of 2n bar local S type and the cost value of 2n bar local " returning " font optimum reference flight flight path; The optimum reference flight flight path of local S type minimum for cost value in the optimum reference flight flight path of 2n bar local S type is decided to be global optimum S type flight path; Local minimum for cost value in 2n bar local " returning " font optimum reference flight flight path " is returned " font optimum reference flight flight path to be decided to be global optimum and " to return " font flight path;
The acquisition methods of the optimum reference flight flight path of local S type is:
1) select summit, one, polygon farmland operation region to select a course as original heading as initial vertex, using with the nearest node in initial vertex as present node;
2) all nodes that search is adjacent with the present node of unmanned helicopter flight, find the node meeting constraint condition, will meet the adjacent node of constraint condition as next possible destination node; Meet constraint condition to refer to: in the node adjacent with present node, find the numerical value that each adjacent node is corresponding in node index matrix, namely the minimum adjacent node of numerical value meets constraint condition;
3) judge whether present node is turning point, if so, then calculate the velocity vector from present node to next possible destination node successively, selection and the current minimum node of course vector angle of flying nonstop to, as next destination node, enter step 6); If present node is not turning point, then enter step 4);
4) cost function h (n) is utilized to calculate from present node to the cost value of next possible destination nodes all;
5) the possible destination node selecting cost value minimum is as next destination node;
6) value of obtained next destination node in described node index matrix is added 1, represent that this node is visited once, and this node is put in flight path sequence node table;
7) using obtained next destination node as the present node circulated next time, repeat step 2) ~ step 6), until traveled through all nodes in the polygon farmland operation region after digitizing, obtain an optimum reference flight flight path of local S type;
8) step 1 is repeated) ~ 7), traversal all summits, polygon farmland operation region, cook up the optimum reference flight flight path of local S type on each summit respectively, obtain the optimum reference flight flight path of 2n bar local S type.
2. the flight path automatic planning in depopulated helicopter pesticide spraying farmland operation region according to claim 1, is characterized in that, the acquisition methods locally " returning " the optimum reference flight flight path of font is:
1) select summit, one, polygon farmland operation region to select a course as original heading as initial vertex, using with the nearest node in initial vertex as present node;
2) all nodes that search is adjacent with the present node of unmanned helicopter flight, find the node meeting constraint condition, will meet the adjacent node of constraint condition as next possible destination node; Meet constraint condition to refer to: in the node adjacent with present node, find the numerical value that each adjacent node is corresponding in node index matrix, namely the minimum adjacent node of numerical value meets constraint condition;
3) judge whether present node is turning point, if, then calculate the velocity vector from present node to next possible destination node successively, select with the current minimum node of course vector angle of flying nonstop to as next destination node, and course vector set I is flown nonstop in renewal, side flight gathers J to vector, and oblique flight gathers K to vector, enters step 6); If present node is not turning point, then enter step 4);
4) cost function h (n) is utilized to calculate from present node to the cost value of next possible destination nodes all;
5) the possible destination node selecting cost value minimum is as next destination node;
6) value of obtained next destination node in described node index matrix is added 1, represent that this node is visited once, and this node is put in flight path sequence node table;
7) using obtained next destination node as the present node circulated next time, repeat step 2) ~ step 6), until traveled through all nodes in the polygon farmland operation region after digitizing, obtain a local and " returned " the optimum reference flight flight path of font;
8) step 1 is repeated) ~ 7), traversal all summits, polygon farmland operation region, the optimum reference flight flight path of font " is returned " in the local cooking up each summit respectively, obtains the optimum reference flight flight path of 2n bar local " returning " font.
3. the flight path automatic planning in depopulated helicopter pesticide spraying farmland operation region according to claim 1, is characterized in that, the acquisition methods of global optimum S type flight path is:
1) calculate in the optimum reference flight flight path of each local S type, depopulated helicopter fly nonstop to distance x
p1, side flies distance x
p5, takeoff point is apart from track initiation point distance x
p2, abort point is apart from the distance x of base station
p3; And depopulated helicopter operation complete after turn back to the distance x of depopulated helicopter operating personnel position
p4;
2) calculate the cost value of the optimum reference flight flight path of each local S type, wherein the computing formula of the cost value f (p) of local S type optimum reference flight flight path p is:
wherein w
1the coefficient of distance sum is flown nonstop to, w for depopulated helicopter is all
2for all sides of depopulated helicopter fly the coefficient of distance sum, w
1+ w
2=1;
3) optimum for local S type minimum for cost value reference flight flight path is decided to be global optimum S type flight path.
4. the flight path automatic planning in depopulated helicopter pesticide spraying farmland operation region according to claim 2, is characterized in that, the acquisition methods that font flight path " returns " in global optimum is:
1) calculating each local " returns " in the optimum reference flight flight path of font, depopulated helicopter fly nonstop to distance x
q1, number of turns t, takeoff point is apart from track initiation point distance x
q2, abort point is apart from the distance x of base station
q3; And depopulated helicopter operation complete after turn back to the distance x of depopulated helicopter operating personnel position
q4;
2) calculate the cost value that the optimum reference flight flight path of font " is returned " in each local, the computing formula of wherein " returning " the cost value f (q) of font optimum reference flight flight path q is:
3) local minimum for cost value " is returned " the optimum reference flight flight path of font and be decided to be global optimum S type flight path.
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