CN103699135A - Automatic planning method for flight path of unmanned helicopter for spraying pesticide in farmland operation area - Google Patents
Automatic planning method for flight path of unmanned helicopter for spraying pesticide in farmland operation area Download PDFInfo
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Abstract
The invention discloses an automatic planning method for a flight path of an unmanned helicopter for spraying pesticide in a farmland operation area. The method comprises the steps of planning a local optimum S-shaped flight path of any starting vertex and any starting flight direction of a polygonal farmland operation area and a local optimum concentric-square-shaped flight path of any starting vertex and any starting flight direction; respectively finding out a global optimum S-shaped flight path and a global optimum concentric-square-shaped flight path from the local optimum S-shaped flight paths and the local optimum concentric-square-shaped flight paths. The automatic planning method for the flight path of the unmanned helicopter for spraying pesticide in the farmland operation area has the advantages that the defect of manually planning the flight path in the traditional manual method is overcome; on the premise that the unmanned helicopter can meet the requirements of operation tasks, various cost consumption factors are reduced and the spraying efficiency is improved.
Description
Technical field
The present invention relates to depopulated helicopter trajectory planning field, particularly the flight path automatic planning in a kind 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, the Mechanization Level of the aspect such as receipts had showing and improved, but pesticide spraying (particularly paddy rice pesticide spraying), substantially still traditional manual operation.China Shi Yige large agricultural country, how effectively to prevent agricultural pest to become one of important goal of China's agricultural production, particularly in country, advocate energetically in the process of promoting green agriculture, precision agriculture, the low cost of applicable China rural situation, pesticide spraying machineryization and robotization accurate, high-environmental become a requisite technology, and utilize small-sized depopulated helicopter to carry out pesticide spraying, are the optimal selections of pesticide spraying machineryization.
Under current China rural condition, using miniature self-service driving helicopter to spray insecticide is China, particularly the more real a kind of feasible method in southern area.Within 2012, Changsha agricultural sector just signs and has purchased 50 unmanned plant protection aircrafts for pesticide spraying operation.
Not only speed is fast for unmanned pesticide spraying helicopter, and uses ultra-low volume pesticide spraying, saves agricultural chemicals and water resource, reduces residues of pesticides and the environmental pollution of crops, and 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 can greatly improve operating efficiency.But due to the distance controlled of depopulated helicopter, cause cannot judging concrete state of flight with human eye, as heading, flying distance etc.To depopulated helicopter, the flight track in farmland operation region carries out rationally the effectively method of planning to shortage, causes the selected flight path of operating personnel not optimum; And due to the caused drain spray of the collimation error, spray by mistake, respray, spraying efficiency is reduced, operating cost raises.
How effectively unmanned vehicle, need to, the task process that completes oneself safely plans, so-called mission planning that Here it is in the process of finishing the work.In task planning process, most important, be also that the most complicated for unmanned vehicle, cooking up one completes the needed flight track of aerial mission exactly, i.e. unmanned vehicle trajectory planning.
Unmanned aerial vehicle flight path planning is exactly to consider various factors, as: time of arrival, flying distance, fuel consumption, threat and flight range etc., for unmanned plane is cooked up an optimum, or the most satisfied flight track, to guarantee satisfactorily to complete aerial mission.
Depopulated helicopter trajectory planning has several different methods, 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, in path planning and graph search, has a wide range of applications.This algorithm, by heuristic information guiding search, reaches the object that reduces hunting zone, improves computing velocity.While utilizing traditional A* algorithm to carry out flight path search, conventionally planning environment is expressed as to the form of grid, then according to predetermined cost function, finds minimum cost flight path.The method each grid cell calculation cost that may arrive to current location, then selects the grid cell of lowest costs to add search volume to explore.Add this new grid cell of search volume to be used to again produce more possible path.Voronoi figure is a kind of important geometry in computing machine geometry.McLain and Beard etc. have proposed the collaborative path planning method of a kind of multi-aircraft based on Voronoi figure.First by known local radar or threat structure Voronoi, scheme, the border of Voronoi figure is exactly all flight paths that fly, and then provides the weights on these borders, final search optimal trajectory.Genetic algorithm is the computation model of the natural selection of simulation Darwin theory of biological evolution and the biological evolution process of science of heredity mechanism, is a kind of by the method for simulating nature evolutionary process search optimum solution.The general step that carries out trajectory planning by genetic algorithm has: a) flight path is encoded; B) construct suitable route evaluation function; C) select to be suitable for the genetic operator of trajectory planning; D) calculate and finely tune operator and obtain final solution.Ant group algorithm is to come realizing route to search for by the information interchange of ant and 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) more lower according on state transitions rules selection grid chart of every ant, finally arrives impact point, forms 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, according to pheromones, adjust criterion the pheromones of each point is adjusted; F) check optimum solution, judge whether to carry out the adjustment of information evaporation prime factor P, if need to adjust accordingly by certain rule; G) judge whether to meet iterated conditional (whether reaching iterations or the minimum target function of setting), if meet, complete search; If do not meet, return to step b), repeat, until meet iterated conditional.Heuristic search is exactly that search in state space is assessed the position of each search, obtains best position, then searches for until target from this position.Can omit so a large amount of meaningless searching routes, improve efficiency.In heuristic search, to the appraisal of position, be very important.Adopted different appraisals can have different effects.
Traditional heuristic search and other method for searching path, at aspects such as processing the shortest reachable path, flight optimization flight path (time is short, oil consumption is low, safe), avoiding obstacles, have advantage separately, 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 is just different with the shortest traditional or flight optimization path.
B) meeting on the basis that covers whole operating areas, further consider flight path and flying method in whole region, how flying can be so that operating efficiency be the highest.
C) in flight course, also will consider oil consumption and residue pesticide volume, when oil consumption or pesticide volume deficiency, after the interpolation of need to making a return voyage, proceed operation, the distance of its round base station also must be calculated in whole planing method.
The object of the invention is to traditional heuristic search algorithm 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, arrives frontier point rear side and flies a segment distance, then by flying in the opposite direction with former boat, form thus crooked S type flight track.
" return " font flight track: refer to that depopulated helicopter carries out pesticide spraying along prearranged heading flight, after arrival is turned round a little, hovering turn, continues flight forward along next course, form thus " returning " font flight track.
Base station: be a groundwork station, when depopulated helicopter fuel oil or agricultural chemicals deficiency, can return to base station is the continuation operation of setting out again after depopulated helicopter interpolation fuel oil, agricultural chemicals.
Summary of the invention
Technical matters to be solved by this invention is, not enough for prior art, the flight path automatic planning in a kind of depopulated helicopter pesticide spraying farmland operation region is provided, depopulated helicopter is planned automatically at farmland operation region flight track, generate the S of global optimum type flight track and " returning " font flight track, overcome the deficiency of artificial planning flight path in Traditional Man operating type, depopulated helicopter can met under the prerequisite of job task, reduce various cost consumption factors, improve spraying efficiency.
For solving the problems of the technologies described above, the technical solution adopted in the present invention is: the flight path automatic planning in a kind of depopulated helicopter pesticide spraying farmland operation region, and the method is:
1) utilize Grid Method digitizing polygon farmland operation region, polygon farmland operation region is divided into several grids; Described polygon farmland operation region number of vertices is n;
2) for the polygon farmland operation region after digitizing, set up node index matrix, take each grid as a node, deposit the terrain information of each grid in described node index matrix;
3) definition following cost function h (n):
Wherein,
for depopulated helicopter is from the fly velocity vector of next destination node of present node; I is that depopulated helicopter is flown 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) utilize and inspire memory type method to carry out the search of depopulated helicopter flight path, obtain the optimum reference flight flight path of local S type of any original heading, all initial vertexs, polygon farmland operation region and the optimum reference flight flight path of font " is returned " in the part of any original heading, all initial vertexs, polygon farmland operation region, wherein the optimum reference flight flight path of local S type and part " are returned " font optimum reference flight flight path and are respectively 2n bar;
5) solve respectively the cost value of the optimum reference flight flight path of the local S type of 2n bar in described step 4) and the cost value of the optimum reference flight flight path of local " returning " font of 2n bar; The optimum reference flight flight path of local S type of cost value minimum in the optimum reference flight flight path of the local S type of 2n bar is decided to be to the S of global optimum type flight path; Font optimum reference flight flight path " is returned " in the part of cost value minimum in the optimum reference flight flight path of local " returning " font of 2n bar 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 Yi Ge summit, polygon farmland operation region as initial vertex and select a course as original heading, using with the nearest node in initial vertex as present node.
2) the search all nodes adjacent with the present node of unmanned helicopter flight, find the node that meets constraint condition, using the adjacent node that meets constraint condition as next possible destination node; Meeting constraint condition refers to: in the node adjacent with present node, find the numerical value of each adjacent node correspondence in node index matrix, the adjacent node of numerical value minimum meets constraint condition;
3) judge whether present node is turning point, if so, calculates successively the velocity vector from present node to next possible destination node, selection as next destination node, enters step 6) with the current node of flying nonstop to course vector angle minimum; If present node is not turning point, enter step 4);
4) utilize cost function h (n) to calculate the cost value from present node to all next possible destination nodes;
5) select the possible destination node of cost value minimum as next destination node;
6) by resulting next destination node, the value in described node index matrix adds 1, represents that this node is visited once, and this node is put in flight path sequence node table;
7) using resulting next destination node as the present node circulating, repeating step 2 next time)～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) repeating step 1)～7), travel through all summits, polygon farmland operation region, cook up respectively the optimum reference flight flight path of local S type on each summit, obtain the optimum reference flight flight path of the local S type of 2n bar.
The acquisition methods of the optimum reference flight flight path of local " returning " font is:
1) select Yi Ge summit, polygon farmland operation region as initial vertex and select a course as original heading, using with the nearest node in initial vertex as present node.
2) the search all nodes adjacent with the present node of unmanned helicopter flight, find the node that meets constraint condition, using the adjacent node that meets constraint condition as next possible destination node; Meeting constraint condition refers to: in the node adjacent with present node, find the numerical value of each adjacent node correspondence in node index matrix, the adjacent node of numerical value minimum meets constraint condition;
3) judge whether present node is turning point, if, calculate successively the velocity vector from present node to next possible destination node, select with the current node of flying nonstop to course vector angle minimum as next destination node, and upgrade and fly nonstop to course vector set I, side flight is gathered J to vector, and tiltedly flight is gathered K to vector, enters step 6); If present node is not turning point, enter step 4);
4) utilize cost function h (n) to calculate the cost value from present node to all next possible destination nodes;
5) select the possible destination node of cost value minimum as next destination node;
6) by resulting next destination node, the value in described node index matrix adds 1, represents that this node is visited once, and this node is put in flight path sequence node table;
7) using resulting next destination node as the present node circulating next time, repeating step 2)～step 6), until traveled through all nodes in the polygon farmland operation region after digitizing, obtain a part and " return " the optimum reference flight flight path of font;
8) repeating step 1)～7), traversal all summits, polygon farmland operation region, cook up respectively the part on each summit and " return " the optimum reference flight flight path of font, obtain the optimum reference flight flight path of local " returning " font of 2n bar.
The acquisition methods of the S of global optimum type flight path is:
1) calculate in the optimum reference flight flight path of each local S type the flying nonstop to apart from x of depopulated helicopter
p1, side flies apart from x
p5, takeoff point apart from track initiation point apart from x
p2, abort point is apart from the distance x of base station
p3; And depopulated helicopter operation turns back to the distance x of depopulated helicopter operating personnel position after completing
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 the optimum reference flight flight path of local S type p is:
w wherein
1for depopulated helicopter is all, fly nonstop to the coefficient apart from sum, w
2for all sides of depopulated helicopter fly the coefficient apart from sum, w
1+ w
2=1;
3) the optimum reference flight flight path of the local S type of cost value minimum is decided to be to the S of global optimum type flight path.
The acquisition methods that font flight path " returns " in global optimum is:
1) calculate each part and " return " in the optimum reference flight flight path of font, the flying nonstop to apart from x of depopulated helicopter
q1, turning number of times t, takeoff point apart from track initiation point apart from x
q2, abort point is apart from the distance x of base station
q3; And depopulated helicopter operation turns back to the distance x of depopulated helicopter operating personnel position after completing
q4;
2) calculate the cost value that the optimum reference flight flight path of font " is returned " in each part, the computing formula of wherein " returning " the cost value f (q) of the optimum reference flight flight path of font q is:
3) part of cost value minimum " is returned " to the optimum reference flight flight path of font and be decided to be the S of global optimum 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 the S of global optimum type flight track and " returning " font flight track, operator can be according to operating habit and operating area condition, select arbitrarily wherein a kind of trajectory planning to carry out pesticide spraying operation, method of the present invention has overcome the deficiency of artificial planning flight path in Traditional Man operating type, can meet under the prerequisite of job task, reduce various cost consumption factors, improve spraying efficiency; The present invention has realized local optimum S type trajectory planning and the local optimum of arbitrary initial vertex, any convex polygon farmland operation region, arbitrary original heading and " has returned " 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, from local optimum S type flight path and local optimum, " return " font flight path, select global optimum's flight path, calculate simply, 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 a plurality of convex polygons, 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 demonstration figure in the embodiment of the present invention;
Fig. 3 is the farmland operation area schematic after rasterizing in the embodiment of the present invention;
Fig. 4 is that in the embodiment of the present invention, node index matrix is set 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 that the former reference frame of the embodiment of the present invention " returns " font flight path;
Figure 12 is that depopulated helicopter takeoff point S point, base station M point, operation complete an E point that makes a return voyage all not at the flight path schematic diagram one of same point;
Figure 13 is that depopulated helicopter takeoff point S point, base station M point, operation complete an E point that makes a return voyage 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 local S type of the present invention optimal trajectory planning flow chart;
Figure 16 is local " returning " font optimal trajectory of the present invention 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 main information source of carrying out trajectory planning, studies numerical map great majority both at home and abroad and adopts Grid Method, 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.For region, be the farmland of ((x, y) | 0≤x≤a, 0≤y≤b), x axle and y axle are 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 can be used as so trajectory planning just equals n.And for each initial vertex, for guaranteeing that flight path can cover whole region, its best original heading is to prolong its right and left rectilinear flight.Therefore for each initial vertex, there are two headings can supply search.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 He Fei operating area, operating area.
Specific implementation is, for the Digital Region creating is set up node index matrix (NodeList).Each grid is exactly a node (later all representing with node), is storing the terrain information of each grid cell in index matrix, and operating area represents with 0, and non-operating area represents with #.So just set up the node index matrix of a storage terrain information.Node index value is used for representing the priority of visiting of present node, is worth less priority higher.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, the at this moment priority of this node decline from 0.With this, realize in search procedure, do not visit node and have all the time the limit priority of visiting, guiding heuristic search can travel through all nodes in operating area, makes the flight path of planning meet the primary demand of farmland operation.
2) for heuristic information is specified in search
In heuristic search, to the appraisal of position, be very important.Adopted different appraisals 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 the actual cost from start node to n node in state space, and h (n) is the estimate cost from n to destination node optimal path.Mainly here the heuristic information that h (n) has embodied search, because g (n) is known.When h (n) >>g (n), can omit g (n), thereby raise the efficiency.
The flight path of depopulated helicopter operating area is must be through all nodes 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 the cost function h (n) from current to next impact point.
Before definition cost function, first need to understand several flying methods.Flying method during depopulated helicopter operation has: fly nonstop to, side flies, tiltedly fly.Consider the manipulation of physical complexity of depopulated helicopter, this three's priority orders is from high to low successively.So in practice, should adopt to fly nonstop to as far as possible and carry out operation, while only maybe needing to turn round on arrival border, just adopt side to fly or tiltedly fly.Therefore, from present node, to next destination node, adopt different flying methods, needed cost is also different.
Definition depopulated helicopter is flown nonstop to course vector set and is combined into I(set I and comprises all course vectors of flying nonstop to), side flight is combined into J to vector set, and tiltedly flight is combined into K to vector set.Speed from present node to next destination node is vector
because x axle overlaps with original heading, so I is exactly, the set of the vector of unit length parallel with x axle is (such as vector (1,0) just belongs to I, (1,0) also belong to I), J is exactly the set of the vector of unit length parallel with y axle, and K is exactly the vector of unit length set that is parallel to straight line y=x.
Definition
That is to say the velocity vector from present node to next destination node
if belonged to, fly nonstop to course vector set I, so required cost is 1, is least estimated cost; If belong to side flight, to vector, gather J, so required cost is 2; If belong to oblique flight, to vector, gather K, so required cost is 3.Definition is in order to meet with practical operation like this.Also embodied the priority orders of visiting next destination node, can visit toward the direction of estimate cost minimum simultaneously.
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 (seeing Figure 15):
Step1. select a summit as initial vertex and select a course as original heading, using with the nearest node in initial vertex as present node.
Step2. the search all nodes adjacent with present node, find the node that meets constraint condition, may destination node as next step using qualified adjacent node.Constraint condition is the minimum adjacent node of value in node index matrix.
Step3. judge whether present node is turning point.If turning point calculates the velocity vector from present node to next possibility node successively
select with the current node of flying nonstop to course vector angle minimum as next destination node.Carry out Step6.
If not turning point, jump to Step4.
Step4. determine after possibility destination node, calculate all cost value f (n) from present node to next possibility node.F (n)=h (n), h (n) is by the velocity vector from present node to next possibility node
determine.
Step5. f (n) is sorted, select f (n) to be worth the next destination node of minimum conduct.
Step6. the present node using the next destination node obtaining as next step circulation, by value+1 in its node index matrix, represents 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 completes.Obtain an optimum reference flight flight path of local S type.
Step8. utilize step 1)～7), travel through all summits, polygon farmland operation region, cook up respectively the optimum reference flight flight path of local S type on each summit, obtain the optimum reference flight flight path of the local S type of all possible 2n bar.
(2) local optimum " is returned " font trajectory planning
" returning " font trajectory planning is identical with digitizing farmland operation region and the trajectory planning initialization of S type trajectory planning.Difference is to compare with S type, and depopulated helicopter is meeting hovering turn after arriving turning point, changes it and flies nonstop to course.Therefore, utilize to inspire memory type algorithm to carry out flight path search procedure different from S type.Mainly for difference, describe 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 (seeing Figure 16):
Step1. select a summit as initial vertex and select a course as original heading, using with the nearest node in initial vertex as present node.
Step2. the search all nodes adjacent with present node, find the node that meets constraint condition, may destination node as next step using qualified adjacent node.Constraint condition is the minimum adjacent node of value in node index matrix.
Step3. judge whether present node is turning point.If turn round a little, calculate successively may node to next from present node velocity vector
select with the current node of flying nonstop to course vector angle minimum as next destination node.Carry out Step6, and upgrade and fly nonstop to course vector set I, side flight is gathered J to vector, and tiltedly flight is gathered K to vector.Wherein gathering I comprises and from next, determines that destination node is to the velocity vector of present node
parallel all vector of unit length, side flight comprises all vector of unit length vertical with set I to vector set J, tiltedly flight comprises and set I vector angle and 45 all vector of unit length of spending to vector set K.
If not turning point, jump to Step4.
Step4. determine after possibility destination node, calculate all cost value f (n) from present node to next possibility node.F (n)=h (n), h (n) is by the velocity vector from present node to next possibility node
determine.
Step5. f (n) is sorted, select f (n) to be worth the next destination node of minimum conduct.
Step6. the present node using the next destination node obtaining as next step circulation, by value+1 in its node index matrix, represents that this node is visited once.And put in flight path sequence node table.
Step7. repeating step Step2, to step Step6, finds next track points, until traveled through all nodes in operating area, search procedure completes.Obtain " returning " font local optimum reference flight flight path.
Step8. utilize step 1)～7), traversal all summits, polygon farmland operation region, cook up respectively the part on each summit and " return " the optimum reference flight flight path of font, obtain the optimum reference flight flight path of local " returning " font of all possible 2n bar.
(3) S of global optimum type flight path and " returning " font trajectory planning (seeing Figure 14)
Global optimum's trajectory planning, on the basis of each local optimum, need consider various Cost Problems, and global optimum's planning of S type flight path and " returning " font flight path is discussed respectively below.
1. the S of global optimum type trajectory planning
The cost factor that the S of global optimum type flight path need to be considered has: 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 is due to the distance of the not enough abort of fuel oil or agricultural chemicals position far from base station, and the distance returned after completing of depopulated helicopter operation.For considering above various factors, need to propose a kind of S of global optimum type flight path decision-making technique.The method is for selecting global optimum's flight path from all local optimum S type flight path judgements.
Concrete methods of realizing is:
Step1. calculate in each flight path p the flying nonstop to apart from x of depopulated helicopter
p1, side flies apart from x
p5; Takeoff point apart from track initiation point apart from x
p2; Abort point is apart from the distance x of base station
p3; And the distance x that returns after completing of depopulated helicopter operation
p4.
Step2. the cost value f (p) that calculates each flight path p, the computing formula of f (p) is
w wherein
1for all coefficients of flying nonstop to apart from sum, w
2for all sides fly the coefficient apart from sum, w
1+ w
2=1.
Step3. to all cost value f (p) sequence, the S of the global optimum type that the is flight path of cost value minimum.
2. font trajectory planning " returns " in global optimum
The cost factor that font flight path need to consider " is returned " by global optimum to be had: depopulated helicopter in operating area flying distance, number of times turns round; Depopulated helicopter takeoff point is apart from the distance of certain track initiation point; Depopulated helicopter is due to the distance of the not enough abort of fuel oil or agricultural chemicals position far from base station; The distance of returning after depopulated helicopter operation completes.For considering above various factors, need to propose a kind of global optimum and " return " font flight path decision-making technique.The method is selected global optimum's flight path for " return " judgement of font flight path from all local optimums.
Concrete methods of realizing is:
Step1. calculate in each flight path p the flying nonstop to apart from x of depopulated helicopter
p1, turning number of times t; Takeoff point apart from track initiation point apart from x
p2; Abort point is apart from the distance x of base station
p3; And the distance x that returns after completing of depopulated helicopter operation
p4.
Step2. the cost value f (p) that calculates each flight path p, the computing formula of f (p) is
w wherein
1for all coefficients of flying nonstop to apart from sum, w
2for the coefficient of turning number of times, w
1+ w
2=1.
Step3. to all cost value f (p) sequence, font flight path " returns " in the global optimum that is of cost value minimum.
So far, just realized 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, it is initial vertex that depopulated helicopter can be selected arbitrary summit, and to take two limits that arbitrary summit is connected be original heading flight.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.For region, be the farmland of ((x, y) | 0≤x≤a, 0≤y≤b), x axle and y axle are divided into junior unit lattice according to given spacing, obtain the region, farmland of discretize, spacing size is determined by the depopulated helicopter wide cut of spraying insecticide.At this, the spacing that is 5 meters according to unit head by x axle and y axle is divided into junior unit lattice, as shown in Figure 3.
2. trajectory planning initialization
Initialization content comprises:
1) create the terrain information of numerical map, divide He Fei operating area, operating area.
Specific implementation is, for the Digital Region creating is set up node index matrix (NodeList).Each grid is exactly a node (later all representing with node), is storing the terrain information of each grid cell in index matrix, and operating area represents with 0, and non-operating area represents with #.So just set up the node index matrix of a storage terrain information.
2) for heuristic information is specified in search
Definition depopulated helicopter is flown nonstop to course vector set and is combined into I(set I and comprises all course vectors of flying nonstop to), side flight is combined into J to vector set, and tiltedly flight is combined into K to vector set.Speed from present node to next destination node is vector
Definition
That is to say, from present node to next destination node velocity vector
if belonged to, fly nonstop to course set I, 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 the local S type optimums of rectangle farmland region ABCD with reference to flight track.Concrete methods of realizing is:
Step1. select a 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. the search all nodes adjacent with present node (the black round dot in Fig. 5 represents), find the node that meets constraint condition, may destination node as next step using qualified adjacent node.Constraint condition is the minimum adjacent node of value in node index matrix.
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 obtaining.
Step3. judge whether present node is turning point.If turning point calculates the velocity vector from present node to next possibility node successively
select with the current node of flying nonstop to course vector angle minimum as next destination node.Carry out Step6.
If not turning point, jump to Step4.
Step4. determine after possibility destination node, calculate all cost value f (n) from present node to next possibility node.F (n)=h (n), h (n) is by the velocity vector from present node to next possibility node
determine.
According to Step4, calculate respectively the velocity vector of three black color dots from present node point to band numbering
according to velocity vector
calculate the cost value that arrives each possibility impact point.The cost value that is 1, No. 2 round dot to the cost value of No. 1 round dot is that the cost value of 2, No. 3 round dots is 3.
Step5. f (n) is sorted, select f (n) to be worth the next destination node of minimum conduct.
According to Step5, can determine that No. 1 round dot is next destination node.
Step6. the present node using the next destination node obtaining as next step circulation, by value+1 in its node index matrix, represents that this node 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 the present node of next step circulation.
Step7. repeat Step2 to Step6, find next track points, until traveled through all nodes in operating area, search procedure completes.Obtain an optimum reference flight flight path of local S type.
According to Step7, obtain take the optimum reference flight track line of a S type that A is ABWei original heading, initial vertex.
Step8. utilize step 1)～7), travel through successively four summit A, B, C and the D in rectangle farmland operation region, cook up respectively the optimum reference flight flight path of local S type on each summit, obtain the optimum reference flight flight paths of all possible 8 local S types.
Fig. 9 has shown the whole process of search, and has finally obtained a S type track line.In region, black round dot represents the point in flight path sequence node table.
(2) local optimum " is returned " font trajectory planning
Its process is described consistent with (one), just in the 3rd step, arrives after turning point, needs to change to fly nonstop to course, and its net result as shown in figure 11.
(3) S of global optimum type flight path and " returning " font trajectory planning
1. the S of global optimum type trajectory planning
The cost factor that the S of global optimum type flight path need to be considered has: 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 is due to the distance of the not enough abort of fuel oil or agricultural chemicals position far from base station, and the distance returned after completing of depopulated helicopter operation.For considering above various factors, need to propose a kind of S of global optimum type flight path decision-making technique.This system, method is for selecting global optimum's flight path from all local optimum S type flight path judgements.
This system concrete methods of realizing is:
Step1. calculate in each S type local optimum flight path p of rectangle ABCD the flying nonstop to apart from x of depopulated helicopter
p1, side flies apart from x
p5; Takeoff point apart from track initiation point apart from x
p2; Abort point is apart from the distance x of base station
p3; And the distance x that returns after completing of depopulated helicopter operation
p4.
Summit A take below as starting point, and the S type flight path that AB is original heading is example, calculates its cost value f (p).
Suppose that depopulated helicopter takeoff point S point, base station M point, operation complete an E point that makes a return voyage all not in same point, as shown in figure 12.
First calculate in this flight path the flying nonstop to apart from x of depopulated helicopter
p1, side flies apart from x
p5.X
p1equal all line segment sums of flying nonstop in flight path.X
p5equal all side fly line section sums in flight path.
Calculate again takeoff point S and put A apart from track initiation
1apart from 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; After operation completes apart from the distance x of reentry point E
p4equal line segment EA
3length.
Step2. the cost value f (p) that calculates this flight path, the computing formula of f (p) is
w wherein
1for all coefficients of flying nonstop to apart from sum, w
2for all sides fly the coefficient apart from sum, w
1+ w
2=1.
Coefficient w
1, w
2according to the ratio calculation of the speed of flying nonstop to and side degree at full speed out
w
1=0.1，w
2=0.9
Can calculate thus the cost value f (p) of this flight path.
Step3. repeat above step, just can calculate the cost value of each local optimum S type flight path, to all cost value f (p) sequence, the S of the global optimum type that the is flight path of cost value minimum.
Thus, realized the planning of the S of global optimum type operation reference track.
2. font trajectory planning " returns " in global optimum
The cost factor that font flight path need to consider " is returned " by global optimum to be had: depopulated helicopter in operating area flying distance, number of times turns round; Depopulated helicopter takeoff point is apart from the distance of certain track initiation point; Depopulated helicopter is due to the distance of the not enough abort of fuel oil or agricultural chemicals position far from base station; The distance of returning 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 selected global optimum's flight path for " return " judgement of font flight path from all local optimums.
Concrete methods of realizing is:
Step1. calculate each local optimum of rectangle ABCD and " return " in font flight path p, the flying nonstop to apart from x of depopulated helicopter
p1, turning number of times t; Takeoff point apart from track initiation point apart from x
p2; Abort point is apart from the distance x of base station
p3; And the distance x that returns after completing of depopulated helicopter operation
p4.
Summit A take below as starting point, and " returning " font flight path that AB is original heading is example, calculates its cost value f (p).
Suppose that depopulated helicopter takeoff point S point, base station M point, operation complete an E point that makes a return voyage all not in same point, as shown in figure 13.
First calculate in this flight path the flying nonstop to apart from x of depopulated helicopter
p1, turning number of times t.X
p1equal all line segment sums of flying nonstop in flight path.T equals all turning point number sums in flight path (4 black round dots of band numeral number (1～4) are turning point).
Calculate again takeoff point S and put A apart from track initiation
1apart from 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; After operation completes apart from the distance x of reentry point E
p4equal line segment EA
3length.
Step2. the cost value f (p) that calculates this flight path, the computing formula of f (p) is
w wherein
1for all coefficients of flying nonstop to apart from sum, w
2for the coefficient of turning number of times, w
1+ w
2=1.
Coefficient w
1, w
2according to flying nonstop to operation and the ratio calculation of turning operation complexity out
w
1=0.25，w
2=0.75
Can calculate thus the cost value f (p) of this flight path.
Step3. repeat above step, just can calculate the cost value that each local optimum " is returned " font flight path, to all cost value f (p) sequence, font flight path " returns " in the global optimum that is of cost value minimum.
Thus, realize global optimum and " returned " planning of font operation reference track.
Claims (5)
1. the flight path automatic planning in depopulated helicopter pesticide spraying farmland operation region, is characterized in that, the method is:
1) utilize Grid Method digitizing polygon farmland operation region, polygon farmland operation region is divided into several grids; Described polygon farmland operation region number of vertices is n;
2) for the polygon farmland operation region after digitizing, set up node index matrix, take each grid as a node, deposit the terrain information of each grid in described node index matrix;
3) definition following cost function h (n):
Wherein,
for depopulated helicopter is from the fly velocity vector of next destination node of present node; I is that depopulated helicopter is flown 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) utilize and inspire memory type method to carry out the search of depopulated helicopter flight path, obtain the optimum reference flight flight path of local S type of any original heading, all initial vertexs, polygon farmland operation region and the optimum reference flight flight path of font " is returned " in the part of any original heading, all initial vertexs, polygon farmland operation region, wherein the optimum reference flight flight path of local S type and part " are returned " font optimum reference flight flight path and are respectively 2n bar;
5) solve respectively the cost value of the optimum reference flight flight path of the local S type of 2n bar in described step 4) and the cost value of the optimum reference flight flight path of local " returning " font of 2n bar; The optimum reference flight flight path of local S type of cost value minimum in the optimum reference flight flight path of the local S type of 2n bar is decided to be to the S of global optimum type flight path; Font optimum reference flight flight path " is returned " in the part of cost value minimum in the optimum reference flight flight path of local " returning " font of 2n bar to be decided to be global optimum and " to return " font flight path.
2. the flight path automatic planning in depopulated helicopter pesticide spraying farmland operation according to claim 1 region, is characterized in that, the acquisition methods of the optimum reference flight flight path of local S type is:
1) select Yi Ge summit, polygon farmland operation region as initial vertex and select a course as original heading, using with the nearest node in initial vertex as present node.
2) the search all nodes adjacent with the present node of unmanned helicopter flight, find the node that meets constraint condition, using the adjacent node that meets constraint condition as next possible destination node; Meeting constraint condition refers to: in the node adjacent with present node, find the numerical value of each adjacent node correspondence in node index matrix, the adjacent node of numerical value minimum meets constraint condition;
3) judge whether present node is turning point, if so, calculates successively the velocity vector from present node to next possible destination node, selection as next destination node, enters step 6) with the current node of flying nonstop to course vector angle minimum; If present node is not turning point, enter step 4);
4) utilize cost function h (n) to calculate the cost value from present node to all next possible destination nodes;
5) select the possible destination node of cost value minimum as next destination node;
6) by resulting next destination node, the value in described node index matrix adds 1, represents that this node is visited once, and this node is put in flight path sequence node table;
7) using resulting next destination node as the present node circulating, repeating step 2 next time)～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) repeating step 1)～7), travel through all summits, polygon farmland operation region, cook up respectively the optimum reference flight flight path of local S type on each summit, obtain the optimum reference flight flight path of the local S type of 2n bar.
3. the flight path automatic planning in depopulated helicopter pesticide spraying farmland operation according to claim 1 region, is characterized in that, the acquisition methods of the optimum reference flight flight path of local " returning " font is:
1) select Yi Ge summit, polygon farmland operation region as initial vertex and select a course as original heading, using with the nearest node in initial vertex as present node.
2) the search all nodes adjacent with the present node of unmanned helicopter flight, find the node that meets constraint condition, using the adjacent node that meets constraint condition as next possible destination node; Meeting constraint condition refers to: in the node adjacent with present node, find the numerical value of each adjacent node correspondence in node index matrix, the adjacent node of numerical value minimum meets constraint condition;
3) judge whether present node is turning point, if, calculate successively the velocity vector from present node to next possible destination node, select with the current node of flying nonstop to course vector angle minimum as next destination node, and upgrade and fly nonstop to course vector set I, side flight is gathered J to vector, and tiltedly flight is gathered K to vector, enters step 6); If present node is not turning point, enter step 4);
4) utilize cost function h (n) to calculate the cost value from present node to all next possible destination nodes;
5) select the possible destination node of cost value minimum as next destination node;
6) by resulting next destination node, the value in described node index matrix adds 1, represents that this node is visited once, and this node is put in flight path sequence node table;
7) using resulting next destination node as the present node circulating next time, repeating step 2)～step 6), until traveled through all nodes in the polygon farmland operation region after digitizing, obtain a part and " return " the optimum reference flight flight path of font;
8) repeating step 1)～7), traversal all summits, polygon farmland operation region, cook up respectively the part on each summit and " return " the optimum reference flight flight path of font, obtain the optimum reference flight flight path of local " returning " font of 2n bar.
4. the flight path automatic planning in depopulated helicopter pesticide spraying farmland operation according to claim 2 region, is characterized in that, the acquisition methods of the S of global optimum type flight path is:
1) calculate in the optimum reference flight flight path of each local S type the flying nonstop to apart from x of depopulated helicopter
p1, side flies apart from x
p5, takeoff point apart from track initiation point apart from x
p2, abort point is apart from the distance x of base station
p3; And depopulated helicopter operation turns back to the distance x of depopulated helicopter operating personnel position after completing
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 the optimum reference flight flight path of local S type p is:
w wherein
1for depopulated helicopter is all, fly nonstop to the coefficient apart from sum, w
2for all sides of depopulated helicopter fly the coefficient apart from sum, w
1+ w
2=1;
3) the optimum reference flight flight path of the local S type of cost value minimum is decided to be to the S of global optimum type flight path.
5. the flight path automatic planning in depopulated helicopter pesticide spraying farmland operation according to claim 3 region, is characterized in that, the acquisition methods that font flight path " returns " in global optimum is:
1) calculate each part and " return " in the optimum reference flight flight path of font, the flying nonstop to apart from x of depopulated helicopter
q1, turning number of times t, takeoff point apart from track initiation point apart from x
q2, abort point is apart from the distance x of base station
q3; And depopulated helicopter operation turns back to the distance x of depopulated helicopter operating personnel position after completing
q4;
2) calculate the cost value that the optimum reference flight flight path of font " is returned " in each part, the computing formula of wherein " returning " the cost value f (q) of the optimum reference flight flight path of font q is:
3) part of cost value minimum " is returned " to the optimum reference flight flight path of font and be decided to be the S of global optimum type flight path.
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