Reel type sprinkling irrigation machine in-field path planning method for soil mechanical compaction subduction

Abstract

The invention relates to the technical field of in-field path planning, in particular to a reel type sprinkler in-field path planning method for soil mechanical compaction subduction. The invention aims to solve the problems of low sprinkling irrigation efficiency according to the planned path and soil structure damage caused by soil compaction in the existing path planning method in the field. The method comprises the following steps: dividing field parcels by adopting a convex edge scanning algorithm to obtain regular field parcels and irregular field parcels; acquiring initial ridges of sprinkling irrigation paths of the regular field parcels and the irregular field parcels; and planning a sprinkling irrigation path in the field to obtain a planned in-field path, and then starting sprinkling irrigation from the starting ridge. The in-field path planning method is used for in-field path planning of the reel type sprinkling machine.

Description

Technical Field

[0001] The invention relates to the technical field of field path planning, and in particular to a field path planning method for a reel-type sprinkler irrigator aimed at reducing soil mechanical compaction. Background Art

[0002] With the rapid development of modern technology and the in-depth promotion of smart agriculture, the intelligent and precise operation of agricultural machinery has gradually become an important way to improve agricultural production efficiency and achieve sustainable development. As an important equipment for farmland irrigation, reel sprinkler is widely used in modern agricultural production due to its strong adaptability, easy mobility and uniform irrigation.

[0003] Traditional sprinkler irrigation uses fixed regular paths for sprinkler irrigation. However, in irregular fields, this traditional sprinkler irrigation path planning will lead to repeated coverage of some areas, resulting in repeated irrigation of some areas, while other areas are not fully irrigated. Therefore, the traditional field path planning method will lead to low sprinkler irrigation efficiency and waste of water resources. In addition, when the path planned by the traditional field path planning method is repeatedly irrigated, the soil will be compacted many times, thereby reducing the soil permeability and water retention, and also causing damage to the soil structure. Summary of the invention

[0004] The purpose of the present invention is to solve the problems of low irrigation efficiency according to the planned path and destruction of soil structure caused by soil compaction in the existing field path planning methods, and to propose a field path planning method for a reel-type sprinkler for reducing mechanical compaction of soil.

[0005] A method for field path planning of a reel sprinkler for reducing soil mechanical compaction is described as follows:

[0006] Step 1: Use the convex edge scanning algorithm to divide the field into regular fields and irregular fields, specifically:

[0007] Step 1: Obtain the boundary line segment set of each field, and construct the edge table ET using the boundary line segments of the field;

[0008] Step 1 and 2: Use the working width L of the reel sprinkler as the moving step length of the scanning line, scan each field, and use the scanning results and the edge table ET to construct the active edge table AET;

[0009] Step 13: Obtain the intersection of each boundary line segment in the active edge table AET and the scan line, thereby obtaining a set of intersection pairs Pair;

[0010] Step 14: Use the intersection point pair set Pair to divide the field into regular fields and irregular fields;

[0011] Step 2: Obtain the starting ridges of the sprinkler irrigation paths for regular and irregular fields, specifically:

[0012] Step 21: Use bat algorithm to obtain the starting ridge of sprinkler irrigation in irregular fields;

[0013] Step 22: Get the starting ridge of the regular field:

[0014] The boundary line A and the boundary line B are used as tangents of the working circle to obtain the working circle, and the ridge where the center of the working circle is located is the starting ridge of the regular field;

[0015] The starting points of boundary line A and boundary line B are the same boundary point;

[0016] Step 3: Plan the irrigation path within the field, obtain the planned field path, and then start irrigation from the starting ridge.

[0017] Furthermore, in the step 11, the boundary line segment set of each field is obtained, and the edge table ET is constructed using the boundary line segments of the field, specifically:

[0018] First, obtain the field boundary point set P = {(x i ,y i )|i=1,2,...,n}, and obtain the field boundary line segment set E={e j =(x i1 ,y i1 )→(x i2 ,y i2 )|j=1,2,...,m};

[0019] Among them, (x i ,y i ) is the coordinate of the ith field boundary point, n is the total number of field boundary points, (x i1 ,y i1 ) is the coordinate of the i1th field boundary point, (x i2 ,y i2 ) is the coordinate of the i2th field boundary point, j is the field boundary line segment number, m is the total number of field boundary line segments, e j is the jth boundary line segment of the field, → is the connection relationship;

[0020] Then, the field boundary segment is used to obtain the field boundary segment increment Δx j :

[0021]

[0022] Among them, || is the absolute value symbol;

[0023] Finally, using the field boundary segment increment Δx jGet the edge table ET:

[0024] ET={(y min,j ,y max,j ,x min,j ,Δx j )|j=1,2,...,m}

[0025] y min,j =min(y i1 ,y i2 )

[0026] y max,j =max(y i1 ,y i2 )

[0027] Among them, y min,j Yes j The minimum value of the ordinates of the two endpoints, y max,j Yes j The minimum value of the horizontal coordinates of the two endpoints, x min,j Yes min,j The horizontal coordinate of the corresponding endpoint.

[0028] Furthermore, in the steps 1 and 2, the working width L of the reel sprinkler is used as the moving step length of the scanning line, each field is scanned, and the active edge table AET is constructed using the scanning results and the edge table ET, specifically:

[0029] First, obtain the field circumscribed rectangle R = [(x min ,y min ),(x max ,y max )];

[0030] x min =min(x i ),x max =max(x i ),y min =min(y i ),y max =max(y i )

[0031] Among them, x min is the minimum value of the horizontal coordinate of the field boundary point, x max is the maximum value of the horizontal coordinate of the field boundary point, y min is the minimum value of the vertical coordinate of the field boundary point, y max is the maximum value of the vertical coordinate of the field boundary point, (x min ,y min ) is the coordinate of the lower left corner of the circumscribed rectangle of the field boundary, (x max ,y max) is the coordinate of the upper right corner of the circumscribed rectangle of the field boundary;

[0032] Then, y min As the starting ordinate of the scanning line y', L is used as the moving step of the scanning line, and each field is scanned along the y-axis direction until y'>y max , get y min to y max All boundary segments within the range, and add the minimum abscissa value, maximum ordinate value and corresponding boundary segment increment of each boundary segment to the active edge table AET:

[0033] AET={(x min,j ,Δx j ,y max,j )|j=1,2,...,m}.

[0034] Furthermore, the step 13 obtains the intersection of each boundary line segment in the active edge table AET and the scan line, thereby obtaining a set of intersection pairs Pair, specifically:

[0035] First, obtain the horizontal coordinates of the intersection of each boundary line segment in the active edge table AET and the scan line:

[0036] x current,j =x min,j +(yy min,j )·Δx j

[0037] Among them, x current,j is the horizontal coordinate of the intersection of the jth boundary line segment and the scan line;

[0038] Then, the horizontal coordinates of the intersections of each boundary line segment and the scan line are arranged in ascending order, and every two horizontal coordinates are sequentially combined into an intersection pair to obtain an intersection pair set Pair, specifically:

[0039] Pair={(x 2k-1 ,x 2k ),k=1,...,K}

[0040] Among them, x 2k-1 is the horizontal coordinate of the 2k-1th intersection point, x 2k is the horizontal coordinate of the 2kth intersection point, and 2K is the total number of intersection points between all boundary segments and scan lines.

[0041] Furthermore, in step 14, the field is divided using the set of intersection points Pair to obtain regular field plots and irregular field plots, specifically:

[0042] First, we use the intersection point pair set Pair to obtain the regular field set R = {R k|k=1,2,...,K}:

[0043] R k =[(x 2k-1 ,y),(x 2k ,y+L)]

[0044] Among them, R k is the kth regular region, (x 2k-1 ,y) is the coordinate of the upper left corner of the kth regular area, (x 2k ,y+L) is the coordinate of the lower right corner of the kth regular area;

[0045] Then, the coordinates in the regular field set R are removed from the field boundary point set P, and the area composed of other coordinates is the irregular field.

[0046] Furthermore, the bat algorithm is used in step 21 to obtain the sprinkler irrigation starting ridge in the irregular field, specifically:

[0047] A1. Randomly initialize N starting ridge candidate points (x i' ,y i' ); Initialize the current time t = 0, and use the initialized starting ridge candidate point as the bat's initial position X i' (t) ; Initialize bat speed V i' (t) =0;

[0048] Among them, (x i' ,y i' ) is the position of the i'th candidate starting ridge point, i' is the number of the candidate starting ridge point, x min ≤x i' ≤x max ,y min ≤y i' ≤y max ;

[0049] The position of the i'th starting ridge candidate point is the midpoint of the i'th ridge;

[0050] A2. Get the fitness value of each bat and take the bat with the smallest fitness value as the optimal bat X best , and record the position of the optimal bat (x best ,y best );

[0051] A3. A pulse frequency is randomly generated for each bat, and the bat's flight speed is obtained based on the pulse frequency, so as to update the bat's position according to the bat's flight speed:

[0052] First, generate the pulse frequency corresponding to the bat:

[0053] f i' =f min +(f max -f min )·rand()

[0054] Among them, f i' is the pulse frequency corresponding to bat i', [f min ,f max ] is the pulse search range, f min is the pulse search minimum value, f max is the pulse search maximum value, rand() is the random number generation function;

[0055] Then, update the bat's flight speed based on the pulse frequency:

[0056] V i' (t+1) =ω·V i' (t) +(X best -X i' (t) )·f i'

[0057] Among them, V i' (t+1) is the flight speed of bat i' at time t+1, ω is the inertia weight, V i' (t) is the flying speed of bat i' at time t, X best is the current optimal bat position, X i' (t) is the position of bat i' at time t;

[0058] Finally, update the bat's position based on its flight speed:

[0059] X i' (t+1) =X i' (t) +V i' (t+1)

[0060] Among them, X i' (t+1) is the position of bat i' at time t+1, X i' (t) is the flying speed of bat i' at time t, V i' (t+1) is the flight speed of bat i' at time t+1;

[0061] A4. Calculate the fitness value of the bat after updating the bat position. If the fitness value of the bat after updating the position is less than the fitness value of the optimal bat, the bat after the current updated bat position is taken as the optimal bat, and the updated position is taken as the optimal bat position and recorded; otherwise, the optimal bat and the optimal bat position remain unchanged;

[0062] A5. Randomly perturb the optimal bat and update the position of the optimal bat:

[0063] Generate a random number rand1 in the range [0,1] and compare the random number rand1 with the pulse frequency r of bat i' i' Compare, if rand1>r i' , then perform a local random perturbation on the optimal bat, take the perturbed optimal bat position as the updated optimal bat position, and then execute step A6; otherwise, update the optimal bat position using the following formula:

[0064]

[0065] in, is the updated optimal bat position, A i' is the pulse intensity of bat i', ε∈[-1,1], ε is a random perturbation;

[0066] A6. Get the fitness value of each bat after updating the bat position. If the fitness value of the bat after updating is less than the fitness value of the bat before updating, F(X i' (t+1) )<F(X i' (t) ), then the bat position X will be updated i' (t+1) as the corresponding bat position; otherwise, the bat position X i' (t) constant;

[0067] A7. Get the current fitness values ​​of all bats and obtain the minimum fitness value. If the minimum fitness value is less than the current optimal bat fitness value, update the pulse frequency r. i' Harmony Strong A i' , then execute step A8; otherwise, directly execute step A8;

[0068] Update pulse frequency r i' Harmony Strong A i' , using the following formula:

[0069] A i' (t+1) =α·A i' (t)

[0070] r i'(t+1) =r i' (t) ·(1-e -βt )

[0071] Among them, α is the sound intensity attenuation coefficient, β is the frequency increase coefficient, A i' (t) is the pulse intensity of bat i' at time t, r i' (t) is the pulse frequency of bat i' at time t;

[0072] A8. Update the optimal bat position to the bat position corresponding to the current minimum fitness value, and then determine whether the maximum number of iterations T has been reached. max , if t = T max Then the ridge corresponding to the current optimal bat position is the starting ridge for sprinkler irrigation in the irregular field; otherwise, set t=t+1 and return to step A3.

[0073] Furthermore, the step of obtaining the adaptability value of each bat in A2 is specifically:

[0074]

[0075]

[0076] Among them, C irregular is the geometric center point of the irregular field, j' is the point number in the irregular field, N' is the total number of points in the irregular field, (x j' ,y j' ) are the coordinates of the j'th point in the irregular field.

[0077] Furthermore, in step 3, the irrigation path in the field is planned to obtain the planned field path, and then the irrigation is started from the starting ridge, specifically:

[0078] Step 31: Randomly initialize the positions in M ​​furrows, and use the positions in M ​​furrows to randomly generate M' paths R m' =[(x m',1 ,y m',1 ),(x m',2 ,y m',2 ),...,(x m',M ,y m',M )], each path is a firefly;

[0079] Among them, (x m',1 ,y m',1 ) is the first point in the kth path, (x m',M ,y m',M ) is the Mth point in the m'th path;

[0080] Step 32: Obtain the objective function value of each firefly, take the firefly corresponding to the minimum objective function value as the optimal firefly, and take the objective function value of the optimal firefly as the fluorescence brightness I of the optimal firefly m' ;

[0081] Step 33: Get the fluorescence brightness I of the two fireflies m' and I m* , get the fluorescence brightness difference and attraction of two fireflies:

[0082] Among them, I m' is the fluorescence brightness of firefly m', I m* is the fluorescence brightness of the firefly m*;

[0083] Step 3 and 4: According to the difference in fluorescence brightness of the fireflies, the brighter firefly between the two fireflies is obtained, and the firefly m' moves toward the brighter firefly m*, and the position of the firefly m' is updated using the attraction between the two fireflies:

[0084]

[0085] in, is the position of firefly m' at time t+1, is the position of firefly m' at time t, is the position of the firefly m* at time t, α' is the step size factor, ε'∈[-1,1], ε' is random noise, β m'm* is the attraction between firefly m' and firefly m*;

[0086] Step 35: Randomly perturb the current optimal firefly and update the optimal firefly:

[0087]

[0088] in, is the optimal firefly position at time t+1, is the optimal firefly position at time t;

[0089] Step 36: Obtain the objective function value of the updated firefly, compare the objective function of the updated firefly with the objective function value of the optimal firefly, update the firefly corresponding to the minimum objective function value to the optimal firefly, and use the objective function value of the optimal firefly as the fluorescence brightness of the optimal firefly;

[0090] Step 37: Determine whether the current number of iterations T' has been reached max , if t'=T' max Then output the path corresponding to the optimal firefly as the planned field path; otherwise, set t'=t'+1 and return to step three;

[0091] Step 38: Take the starting ridge obtained in step 2 as the starting point and perform sprinkler irrigation according to the planned field path obtained in step 37.

[0092] Furthermore, the objective function value of each firefly in step 32 is obtained as follows:

[0093] F(R k )=ω1·D m',total +ω2·C m',compact -ω3·E m',efficiency

[0094]

[0095]

[0096]

[0097]

[0098]

[0099]

[0100]

[0101] Among them, ω1 is the total path length weight, ω2 is the compaction weight, ω3 is the sprinkler efficiency weight, and D k,total is the total length of the kth path, C k,compact is the compaction degree of the m'th path, E k,efficiency is the sprinkler efficiency of the m'th path, F(R m' ) is the set of positions in the m'th path, D total,m' is the total length of the m'th path, D row,w is the row distance of the wth operation, d return,w' is the return distance of the w'th operation, W is the total number of operations, compact(l') is the function of whether the l'th ridge is compacted, if compacted, compact(l') is 1, if not compacted, compact(l') is 0, L' is the total number of ridges, C compact,m' is the number of ridges compacted by sprinkler irrigation along the m'th path, E efficiency,m' is the sprinkler efficiency of the m'th path, A cov,m' is the coverage area of ​​the sprinkler irrigation according to the m'th path, n rows is the number of ridges covered in one operation, L is the working width of the convolution disk, and W * is the ridge width, is the floor symbol, A cov,l' is the irrigation area of ​​the l'th ridge, tend,l' is the end time of sprinkler irrigation of the l'th ridge, t start,l' is the start time of sprinkler irrigation for the l'th ridge, R dynamic (t) is the sprinkler radius, t is the time, R0 is the maximum sprinkler radius, v(t) is the variable speed of the reel sprinkler, v max is the maximum speed of the reel sprinkler;

[0102] If the sprinkler passes over the current ridge during its travel path, it means that the current ridge is compacted.

[0103] Furthermore, the step 33 of obtaining the fluorescence brightness of the two fireflies I m' and Get the fluorescence brightness difference and attractiveness of two fireflies, specifically:

[0104] ΔI m'm* =I m' -I m*

[0105]

[0106] r m'm* =‖X' m' -X' m*

[0107] in, is the difference in fluorescence brightness between firefly m' and firefly m*, is the attraction between fireflies m' and m*, β0 is the maximum attraction, γ' is the attraction attenuation coefficient, is the Euclidean distance between firefly m' and firefly m*, X' m' is the location of the firefly m', is the position of the firefly m*.

[0108] The beneficial effects of the present invention are:

[0109] The present invention proposes a field path planning method for a reel-type sprinkler for reducing soil mechanical compaction. By distinguishing between regular and irregular parts in the field, combined with the optimization of the sprinkler coverage and operation path, a field sprinkler path that reduces the impact of mechanical compaction is planned. The present invention is based on the bat algorithm to obtain the sprinkler starting point, and combines the firefly algorithm to optimize the sprinkler path, to obtain the field sprinkler path with the best path length, compaction degree and sprinkler efficiency, thereby improving the sprinkler efficiency, reducing soil compaction, maintaining soil permeability and water retention, and minimizing the degree of damage to the soil structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0110] Figure 1 It is a flow chart of the present invention;

[0111] Figure 2 It is a convex edge type scanning line flow chart;

[0112] Figure 3 This is the flowchart of the bat algorithm;

[0113] Figure 4 This is the flow chart of the firefly algorithm. DETAILED DESCRIPTION

[0114] Specific implementation method 1: Figure 1 As shown, the specific process of the field path planning method of the reel-type sprinkler for reducing soil mechanical compaction in this embodiment is as follows:

[0115] Step 1: Figure 2 As shown, the convex edge scanning algorithm is used to classify the fields to obtain regular fields and irregular fields, specifically:

[0116] Step 1: Get the boundary line segment set of each field, and use the boundary line segments of the field to construct the edge table ET:

[0117] First, obtain the field boundary point set P = {(x i ,y i )|i=1,2,...,n}, and obtain the field boundary line segment set E={e j =(x i1 ,y i1 )→(x i2 ,y i2 )|j=1,2,...,m};

[0118] Among them, (x i ,y i ) is the coordinate of the ith field boundary point, n is the total number of field boundary points, (x i1 ,y i1 ) is the coordinate of the i1th field boundary point, (x i2 ,y i2 ) is the coordinate of the i2th field boundary point, j is the field boundary line segment number, m is the total number of field boundary line segments, e j is the jth boundary line segment of the field, → is the connection relationship; the lower left corner vertex in the convex field is the origin of the coordinate axis, the x-axis direction is the direction perpendicular to the ridge, and the y-axis direction is the ridge direction.

[0119] Then, the field boundary segment is used to obtain the field boundary segment increment Δx j :

[0120]

[0121] Among them, || is the absolute value symbol;

[0122] Finally, using the field boundary segment increment Δx j Get the edge table ET:

[0123] ET={(y min,j ,y max,j ,x min,j ,Δx j )|j=1,2,...,m}

[0124] y min,j =min(y i1 ,y i2 )

[0125] y max,j =max(y i1 ,y i2 )

[0126] Among them, y min,j Yes j The minimum value of the ordinates of the two endpoints, y max,j Yes j The minimum value of the horizontal coordinates of the two endpoints, x min,j Yes min,j The horizontal coordinate of the corresponding endpoint.

[0127] Step 1 and 2: Use the working width L of the reel sprinkler as the moving step length of the scanning line, scan each field, and construct the active edge table AET based on the scanning results and the edge table ET, specifically:

[0128] First, obtain the field circumscribed rectangle R = [(x min ,y min ),(x max ,y max )];

[0129] x min =min(x i ),x max =max(x i ),y min =min(y i ),y max =max(y i )

[0130] Among them, x min is the minimum value of the horizontal coordinate of the field boundary point, x max is the maximum value of the horizontal coordinate of the field boundary point, y min is the minimum value of the vertical coordinate of the field boundary point, y max is the maximum value of the vertical coordinate of the field boundary point, (x min ,y min) is the coordinate of the lower left corner of the circumscribed rectangle of the field boundary, (x max ,y max ) is the coordinate of the upper right corner of the circumscribed rectangle of the field boundary;

[0131] Then, y min As the starting ordinate of the scanning line y', L is used as the moving step of the scanning line, and each field is scanned along the y-axis direction until y'>y max , get y min to y max All boundary segments within the range, and add the minimum abscissa value, maximum ordinate value and corresponding boundary segment increment of each boundary segment to the active edge table AET:

[0132] AET={(x min,j ,Δx j ,y max,j )|j=1,2,...,m}

[0133] Step 13: Use the intersection of each boundary line segment in the active edge table AET and the scan line to obtain a set of intersection pairs, specifically:

[0134] First, obtain the horizontal coordinates of the intersection of each boundary line segment in the active edge table AET and the scan line:

[0135] x current,j =x min,j +(yy min,j )·Δx j

[0136] Among them, x current,j is the horizontal coordinate of the intersection of the jth boundary line segment and the scan line;

[0137] Then, the horizontal coordinates of the intersections of each boundary line segment and the scan line are arranged in ascending order, and every two horizontal coordinates are sequentially combined into an intersection pair to obtain an intersection pair set Pair, specifically:

[0138] Pair={(x 2k-1 ,x 2k ),k=1,...,K}

[0139] Among them, x 2k-1 is the horizontal coordinate of the 2k-1th intersection point, x 2k is the horizontal coordinate of the 2kth intersection point, 2K is the total number of intersection points between all boundary segments and scan lines;

[0140] Step 14: Use the intersection point pair set Pair to classify the fields to obtain regular fields and irregular fields;

[0141] Regular field set R = {Rk |k=1,2,...,K} is:

[0142] R k =[(x 2k-1 ,y),(x 2k ,y+L)]

[0143] Among them, R k are the coordinates of the upper left corner and lower right corner of the kth regular area, (x 2k-1 ,y) is the coordinate of the upper left corner of the kth regular area, (x 2k ,y+L) is the coordinate of the lower right corner of the kth regular area;

[0144] In the field boundary point set P, except for the coordinates of the regular field R, the area composed of other coordinates is the irregular field area.

[0145] Step 2: Figure 3 As shown, the starting ridges of the sprinkler irrigation paths of regular and irregular fields are obtained, specifically:

[0146] Step 21: Use the bat algorithm to obtain the starting ridge for sprinkler irrigation in irregular fields:

[0147] A1. Randomly initialize N starting ridge candidate points (x i' ,y i' ); Initialize the current time t = 0, and use the initialized starting ridge candidate point as the bat's initial position X i' (t) ; Initialize bat speed V i' (t) =0;

[0148] Among them, (x i' ,y i' ) is the position of the i'th candidate starting ridge point (the starting ridge candidate position refers to the midpoint of the current ridge), i' is the number of the starting ridge candidate point, x min ≤x i' ≤x max ,y min ≤y i' ≤y max ;

[0149] A2. Get the fitness value of each bat and take the bat with the smallest fitness value as the optimal bat X best , and record the position of the optimal bat (x best ,y best ):

[0150] The adaptability value of the bat is obtained by:

[0151]

[0152] Among them, (x center ,y center ) are the coordinates of the geometric centre of the irregular field;

[0153]

[0154] Among them, C irregular is the geometric center point of the irregular field, j' is the point number in the irregular field, N' is the total number of points in the irregular field, (x j' ,y j' ) are the coordinates of the j'th point in the irregular field;

[0155] A3. A pulse frequency is randomly generated for each bat, and the bat's flight speed is obtained based on the pulse frequency, so as to update the bat's position according to the bat's flight speed:

[0156] First, generate the pulse frequency corresponding to the bat:

[0157] f i' =f min +(f max -f min )·rand()

[0158] Among them, f i' is the pulse frequency corresponding to bat i', [f min ,f max ] is the pulse search range (e.g. 0 to 2), f min is the pulse search minimum value, f max is the pulse search maximum value, rand() is the random number generation function;

[0159] Then, update the bat's flight speed based on the pulse frequency:

[0160] V i' (t+1) =ω·V i' (t) +(X best -X i' (t) )·f i'

[0161] Among them, V i' (t+1) is the flight speed of bat i' at time t+1, ω is the inertia weight, which is used to balance global and local search (0.9-0.4 dynamically decreasing), V i' (t) is the flying speed of bat i' at time t, X best is the current optimal bat position, X i' (t)is the position of bat i' at time t;

[0162] Finally, update the bat's position based on its flight speed:

[0163] X i' (t+1) =X i' (t) +V i' (t+1)

[0164] Among them, X i' (t+1) is the position of bat i' at time t+1, X i' (t) is the flying speed of bat i' at time t, V i' (t+1) is the flight speed of bat i' at time t+1;

[0165] A4. Calculate the fitness value of the bat after updating the bat position. If the fitness value of the bat after updating the position is less than the fitness value of the optimal bat, the bat after the current updated bat position is taken as the optimal bat, and the updated position is taken as the optimal bat position and recorded; otherwise, the optimal bat and the optimal bat position remain unchanged;

[0166] A5. Randomly perturb the optimal bat and update the position of the optimal bat:

[0167] Generate a random number rand1∈[0,1] and compare the random number rand1 with the pulse frequency r of bat i' i' Compare, if rand1>r i' , then perform a local random perturbation on the optimal bat, take the perturbed optimal bat position as the updated optimal bat position, and then execute step A6; otherwise, update the optimal bat position using the following formula:

[0168]

[0169] in, is the updated optimal bat position, A i' is the pulse intensity of bat i', ε∈[-1,1], ε is a random perturbation;

[0170] A6. Get the fitness value of each bat after updating the bat position. If the fitness value of the bat after updating is less than the fitness value of the bat before updating, F(X i' (t+1) )<F(X i' (t) ), then the bat position X will be updated i' (t+1) as the corresponding bat position; otherwise, the bat position X i'(t) constant;

[0171] A7. Get the current fitness values ​​of all bats and obtain the minimum fitness value. If the minimum fitness value is less than the current optimal bat fitness value, update the pulse frequency r. i' Harmony Strong A i' , then execute step A8; otherwise, directly execute step A8;

[0172] A i' (t+1) =α·A i' (t)

[0173] r i' (t+1) =r i' (t) ·(1-e -βt )

[0174] Among them, α = 0.98 is the sound intensity attenuation coefficient, β = 0.02 is the frequency increase coefficient, A i' (t) is the pulse intensity of bat i' at time t, r i' (t) is the pulse frequency of bat i' at time t;

[0175] A8. Update the optimal bat position to the position of the bat corresponding to the current minimum fitness value, and then determine whether the maximum number of iterations T has been reached. max , if t = T max Then the ridge corresponding to the current optimal bat position is the starting ridge for sprinkler irrigation in the irregular field; otherwise, set t=t+1 and return to step A3.

[0176] Step 22: The starting ridge of the regular field is obtained by:

[0177] The boundary lines A and B are used as tangents of the working circle to obtain the working circle. The ridge where the center of the working circle is located is the starting ridge of the regular field.

[0178] The starting points of boundary line A and boundary line B are the same boundary point.

[0179] Step 3: Plan the irrigation path in the field, obtain the planned field path, and then start irrigation from the starting ridge, such as Figure 4 As shown, specifically:

[0180] Step 31: Randomly initialize the positions in M ​​furrows, and use the positions in M ​​furrows to randomly generate M' paths R m' =[(x m',1 ,y m',1 ),(x m',2 ,ym',2 ),...,(x m',M ,y m',M )], each path is a firefly;

[0181] Among them, (x m',1 ,y m',1 ) is the first point in the kth path, (x m',M ,y m',M ) is the Mth point in the m'th path;

[0182] Step 32: Obtain the objective function value of each firefly, take the firefly corresponding to the minimum objective function value as the optimal firefly, and take the objective function value of the optimal firefly as the fluorescence brightness I of the optimal firefly m' ;

[0183] The specific objective function value for each firefly is obtained as follows:

[0184] F(R k )=ω1·D m',total +ω2·C m',compact -ω3·E m',efficiency

[0185]

[0186]

[0187]

[0188]

[0189]

[0190]

[0191]

[0192] Among them, ω1 is the total path length weight, ω2 is the compaction weight, ω3 is the sprinkler efficiency weight, and D k,total is the total length of the kth path, C k,compact is the compaction degree of the m'th path, E k,efficiency is the sprinkler efficiency of the m'th path, F(R m' ) is the set of positions in the m'th path, D total,m' is the total length of the m'th path, D row,w is the row distance of the wth operation, d return,w'is the return distance of the w'th operation, W is the total number of operations, compact(l') is the function of whether the l'th ridge is compacted, if compacted it is 1 (walking once in the ridge is considered compacted), if not compacted it is 0, L' is the total number of ridges, C compact,m' is the number of ridges compacted by sprinkler irrigation along the m'th path, E efficiency,m' is the sprinkler efficiency of the m'th path, A cov,m' is the coverage area of ​​the sprinkler irrigation according to the m'th path, n rows is the number of ridges covered in one operation, L is the working width of the convolution disk, and W * is the ridge width, is the floor symbol, A cov,l' is the irrigation area of ​​the l'th ridge, t end,l' is the end time of sprinkler irrigation of the l'th ridge, t start,l' is the start time of sprinkler irrigation for the l'th ridge, R dynamic (t) is the sprinkler radius, t is the time, R0 is the maximum sprinkler radius, v(t) is the variable speed of the reel sprinkler, v max It is the maximum speed of the reel sprinkler.

[0193] Step 33: Get the fluorescence brightness I of the two fireflies m' and Get the fluorescence brightness difference and attractiveness of two fireflies:

[0194]

[0195]

[0196]

[0197] in, is the difference in fluorescence brightness between firefly m' and firefly m*, is the attraction between fireflies m' and m*, β0 = 1 is the maximum attraction, γ' = 1 is the attenuation coefficient of attraction with distance, is the Euclidean distance between firefly m' and firefly m*, X' m' is the position of firefly m', X' m* is the position of firefly m*;

[0198] Step 34: Determine the brighter firefly between every two fireflies according to the difference in fluorescence brightness of the fireflies. The firefly m' moves toward the brighter firefly m*, and the position of the firefly m' is updated using the attraction between the two fireflies:

[0199]

[0200] in, is the position of firefly m' at time t+1, is the position of firefly m' at time t, is the position of the firefly m* at time t, α' = 0.2 is the step factor, and ε'∈[-1,1] is uniform random noise;

[0201] Step 35: Randomly perturb the current optimal firefly and update the optimal firefly:

[0202]

[0203] in, is the optimal firefly position at time t+1, is the optimal firefly position at time t;

[0204] Step 36: Obtain the objective function value of the updated firefly, compare the objective function value of the updated firefly with the objective function value of the optimal firefly, update the firefly corresponding to the minimum objective function value to the optimal firefly, and use the objective function value of the optimal firefly as the brightness of the optimal firefly;

[0205] Step 37: Determine whether the current number of iterations T' has been reached max , if t'=T' max Then output the path corresponding to the optimal firefly as the planned field path; otherwise, set t'=t'+1 and return to step three.

[0206] Step 38: Take the starting ridge obtained in step 2 as the starting point and perform sprinkler irrigation according to the planned field path obtained in step 37.

Claims

1. A method for field path planning of a reel sprinkler for reducing soil mechanical compaction, characterized in that The specific process of the method is: Step 1: Use the convex edge scanning algorithm to divide the field into regular fields and irregular fields, specifically: Step 1: Obtain the boundary line segment set of each field, and construct the edge table ET using the boundary line segments of the field; Step 1 and 2: Use the working width L of the reel sprinkler as the moving step length of the scanning line, scan each field, and use the scanning results and the edge table ET to construct the active edge table AET; Step 13: Obtain the intersection of each boundary line segment in the active edge table AET and the scan line, thereby obtaining a set of intersection pairs Pair; Step 14: Use the intersection point pair set Pair to divide the field into regular fields and irregular fields; Step 2: Obtain the starting ridges of the sprinkler irrigation paths for regular and irregular fields, specifically: Step 21: Use bat algorithm to obtain the starting ridge of sprinkler irrigation in irregular fields; Step 22: Get the starting ridge of the regular field: The boundary line A and the boundary line B are used as tangents of the working circle to obtain the working circle, and the ridge where the center of the working circle is located is the starting ridge of the regular field; The starting points of boundary line A and boundary line B are the same boundary point; Step 3: Plan the irrigation path within the field, obtain the planned field path, and then start irrigation from the starting ridge.

2. The method for field path planning of a reel-type sprinkler for reducing soil mechanical compaction according to claim 1, characterized in that: The step 11 obtains the boundary line segment set of each field, and constructs the edge table ET using the boundary line segments of the field, specifically: First, obtain the field boundary point set P = {(x i ,y i )|i=1,2,...,n}, and obtain the field boundary line segment set E={e j =(x i1 ,y i1 )→(x i2 ,y i2 )|j=1,2,...,m}; Among them, (x i ,y i ) is the coordinate of the ith field boundary point, n is the total number of field boundary points, (x i1 ,y i1 ) is the coordinate of the i1th field boundary point, (x i2 ,y i2 ) is the coordinate of the i2th field boundary point, j is the field boundary line segment number, m is the total number of field boundary line segments, e j is the jth boundary line segment of the field, → is the connection relationship; Then, the field boundary segment is used to obtain the field boundary segment increment Δx j : Among them, | | is the absolute value symbol; Finally, using the field boundary segment increment Δx j Get the edge table ET: ET={(y min,j ,y max,j ,x min,j ,Δx j )|j=1,2,...,m} and min,j =min(and i1 ,and i2 ) and max,j =max(y i1 ,and i2 ) Among them, y min,j Yes j The minimum value of the ordinates of the two endpoints, y max,j Yes j The minimum value of the horizontal coordinates of the two endpoints, x min,j Yes min,j The horizontal coordinate of the corresponding endpoint.

3. The method for field path planning of a reel-type sprinkler for reducing soil mechanical compaction according to claim 2, characterized in that: In the steps 1 and 2, the working width L of the reel sprinkler is used as the moving step length of the scanning line, each field is scanned, and the active edge table AET is constructed using the scanning results and the edge table ET, specifically: First, obtain the field circumscribed rectangle R = [(x min ,y min ),(x max ,y max )]; x min =min(x i ),x max =max(x i ),y min =min(y i ),y max =max(y i ) Among them, x min is the minimum value of the horizontal coordinate of the field boundary point, x max is the maximum value of the horizontal coordinate of the field boundary point, y min is the minimum value of the vertical coordinate of the field boundary point, y max is the maximum value of the vertical coordinate of the field boundary point, (x min ,y min ) is the coordinate of the lower left corner of the circumscribed rectangle of the field boundary, (x max ,y max ) is the coordinate of the upper right corner of the circumscribed rectangle of the field boundary; Then, y min As the starting ordinate of the scanning line y', L is used as the moving step of the scanning line, and each field is scanned along the y-axis direction until y'>y max , get y min to y max All boundary segments within the range, and add the minimum abscissa value, maximum ordinate value and corresponding boundary segment increment of each boundary segment to the active edge table AET: AET={(x min,j ,Δx j ,y max,j )|j=1,2,...,m}。 4. The method for field path planning of a reel-type sprinkler for reducing soil mechanical compaction according to claim 3, characterized in that: The step 13 obtains the intersection of each boundary line segment in the active edge table AET and the scan line, thereby obtaining a set of intersection pairs Pair, specifically: First, obtain the horizontal coordinates of the intersection of each boundary line segment in the active edge table AET and the scan line: x current,j =x min,j +(y-y min,j )·Δx j Among them, x current,j is the horizontal coordinate of the intersection of the jth boundary line segment and the scan line; Then, the horizontal coordinates of the intersections of each boundary line segment and the scan line are arranged in ascending order, and every two horizontal coordinates are sequentially combined into an intersection pair to obtain an intersection pair set Pair, specifically: Pair={(x 2k-1 ,x 2k ),k=1,...,K} Among them, x 2k-1 is the horizontal coordinate of the 2k-1th intersection point, x 2k is the horizontal coordinate of the 2kth intersection point, and 2K is the total number of intersection points between all boundary segments and scan lines.

5. The method for field path planning of a reel-type sprinkler for reducing soil mechanical compaction according to claim 4, characterized in that: The step 14 uses the intersection point pair set Pair to divide the field into regular fields and irregular fields, specifically: First, we use the intersection point pair set Pair to obtain the regular field set R = {R k |k=1,2,...,K}: R k =[(x 2k-1 ,y),(x 2k ,y+L)] Among them, Rk is the kth regular region, (x 2k-1 ,y) is the coordinate of the upper left corner of the kth regular area, (x 2k ,y+L) is the coordinate of the lower right corner of the kth regular area; Then, the coordinates in the regular field set R are removed from the field boundary point set P, and the area composed of other coordinates is the irregular field.

6. The method for field path planning of a reel-type sprinkler for reducing soil mechanical compaction according to claim 5, characterized in that: The step 21 in which the bat algorithm is used to obtain the sprinkler irrigation starting ridge in the irregular field is specifically as follows: A1. Randomly initialize N starting ridge candidate points (x i' ,y i' ); Initialize the current time t = 0, and use the initialized starting ridge candidate point as the bat's initial position X i' (t) ; Initialize bat speed V i' (t) =0; Among them, (x i' ,y i' ) is the position of the i'th candidate starting ridge point, i' is the number of the candidate starting ridge point, x min ≤x i' ≤x max ,y min ≤y i' ≤y max ; The position of the i'th starting ridge candidate point is the midpoint of the i'th ridge; A2. Get the fitness value of each bat and take the bat with the smallest fitness value as the optimal bat X best , and record the position of the optimal bat (x best ,y best ); A3. A pulse frequency is randomly generated for each bat, and the bat's flight speed is obtained based on the pulse frequency, so as to update the bat's position according to the bat's flight speed: First, generate the pulse frequency corresponding to the bat: f i' =f min +(f max -f min )·rand() Among them, f i' is the pulse frequency corresponding to bat i', [f min ,f max ] is the pulse search range, f min is the pulse search minimum value, f max is the pulse search maximum value, rand() is the random number generation function; Then, update the bat's flight speed based on the pulse frequency: V i' (t+1) =ω·V i' (t) +(X best -X i' (t) )·f i' Among them, V i' (t+1) is the flight speed of bat i' at time t+1, ω is the inertia weight, V i' (t) is the flying speed of bat i' at time t, X best is the current optimal bat position, X i' (t) is the position of bat i' at time t; Finally, update the bat's position based on its flight speed: X i' (t+1) =X i' (t) +V i' (t+1) Among them, X i' (t+1) is the position of bat i' at time t+1, X i' (t) is the flying speed of bat i' at time t, V i' (t+1) is the flight speed of bat i' at time t+1; A4. Calculate the fitness value of the bat after updating the bat position. If the fitness value of the bat after updating the position is less than the fitness value of the optimal bat, the bat after the current updated bat position is taken as the optimal bat, and the updated position is taken as the optimal bat position and recorded; otherwise, the optimal bat and the optimal bat position remain unchanged; A5. Randomly perturb the optimal bat and update the position of the optimal bat: Generate a random number rand1 in the range [0,1] and compare the random number rand1 with the pulse frequency r of bat i' i' Compare, if rand1>r i' , then perform a local random perturbation on the optimal bat, take the perturbed optimal bat position as the updated optimal bat position, and then execute step A6; otherwise, update the optimal bat position using the following formula: in, is the updated optimal bat position, A i' is the pulse intensity of bat i', ε∈[-1,1], ε is a random perturbation; A6. Get the fitness value of each bat after updating the bat position. If the fitness value of the bat after updating is less than the fitness value of the bat before updating, i' (t+1) )<F(X i' (t) ), then the bat position X will be updated i' (t+1) as the corresponding bat position; otherwise, the bat position X i' (t) constant; A7. Get the current fitness values ​​of all bats and obtain the minimum fitness value. If the minimum fitness value is less than the current optimal bat fitness value, update the pulse frequency r. i' Harmony Strong A i' , then execute step A8; otherwise, directly execute step A8; Update pulse frequency r i' Harmony Strong A i' , using the following formula: A i' (t+1) =α·A i' (t) r i' (t+1) ＝r i' (t) ·(1-e -βt ) Among them, α is the sound intensity attenuation coefficient, β is the frequency increase coefficient, A i' (t) is the pulse intensity of bat i' at time t, r i' (t) is the pulse frequency of bat i' at time t; A8. Update the optimal bat position to the bat position corresponding to the current minimum fitness value, and then determine whether the maximum number of iterations T has been reached. max , if t = T max Then the ridge corresponding to the current optimal bat position is the starting ridge for sprinkler irrigation in the irregular field; otherwise, set t=t+1 and return to step A3.

7. The method for field path planning of a reel-type sprinkler for reducing soil mechanical compaction according to claim 6, characterized in that: The step A2 of obtaining the adaptability value of each bat is specifically: Among them, C irregular is the geometric center point of the irregular field, j' is the point number in the irregular field, N' is the total number of points in the irregular field, (x j' ,y j' ) are the coordinates of the j'th point in the irregular field.

8. The method for field path planning of a reel-type sprinkler for reducing soil mechanical compaction according to claim 7, characterized in that: The step 3 of planning the irrigation path in the field, obtaining the planned field path, and then starting irrigation from the starting ridge is as follows: Step 31: Randomly initialize the positions in M ​​furrows, and use the positions in M ​​furrows to randomly generate M' paths R m' =[(x m',1 ,y m',1 ),(x m',2 ,y m',2 ),...,(x m',M ,y m',M )], each path is a firefly; Among them, (x m',1 ,y m',1 ) is the first point in the kth path, (x m',M ,y m',M ) is the Mth point in the m'th path; Step 32: Obtain the objective function value of each firefly, take the firefly corresponding to the minimum objective function value as the optimal firefly, and take the objective function value of the optimal firefly as the fluorescence brightness I of the optimal firefly m' ; Step 33: Get the fluorescence brightness I of the two fireflies m' and I m* , get the fluorescence brightness difference and attraction of two fireflies: Among them, I m' is the fluorescence brightness of firefly m', I m* is the fluorescence brightness of the firefly m*; Step 3 and 4: According to the difference in fluorescence brightness of the fireflies, the brighter firefly between the two fireflies is obtained, and the firefly m' moves toward the brighter firefly m*, and the position of the firefly m' is updated using the attraction between the two fireflies: in, is the position of firefly m' at time t+1, is the position of firefly m' at time t, is the position of the firefly m* at time t, α' is the step size factor, ε'∈[-1,1], ε' is random noise, β m'm* is the attraction between firefly m' and firefly m*; Step 35: Randomly perturb the current optimal firefly and update the optimal firefly: in, is the optimal firefly position at time t+1, is the optimal firefly position at time t; Step 36: Obtain the objective function value of the updated firefly, compare the objective function of the updated firefly with the objective function value of the optimal firefly, update the firefly corresponding to the minimum objective function value to the optimal firefly, and use the objective function value of the optimal firefly as the fluorescence brightness of the optimal firefly; Step 37: Determine whether the current number of iterations T' has been reached max , if t'=T' max Then output the path corresponding to the optimal firefly as the planned field path; otherwise, set t'=t'+1 and return to step three; Step 38: Take the starting ridge obtained in step 2 as the starting point and perform sprinkler irrigation according to the planned field path obtained in step 37.

9. The method for field path planning of a reel-type sprinkler for reducing soil mechanical compaction according to claim 8, characterized in that: The objective function value of each firefly in step 32 is obtained as follows: F(R k )=ω1·D m',total +ω2·C m',compact -ω3·E m',efficiency Among them, ω1 is the total path length weight, ω2 is the compaction weight, ω3 is the sprinkler efficiency weight, and D k,total is the total length of the kth path, C k,compact is the compaction degree of the m'th path, E k,efficiency is the sprinkler efficiency of the m'th path, F(R m' ) is the set of positions in the m'th path, D total,m' is the total length of the m'th path, D row,w is the row distance of the wth operation, d return,w' is the return distance of the w'th operation, W is the total number of operations, compact(l') is the function of whether the l'th ridge is compacted, if compacted, compact(l') is 1, if not compacted, compact(l') is 0, L' is the total number of ridges, C compact,m' is the number of ridges compacted by sprinkler irrigation along the m'th path, E efficiency,m' is the sprinkler efficiency of the m'th path, A cov,m' is the coverage area of ​​the sprinkler irrigation according to the m'th path, n rows is the number of ridges covered in one operation, L is the working width of the convolution disk, and W * is the ridge width, is the floor symbol, A cov,l' is the irrigation area of ​​the l'th ridge, t end,l' is the end time of sprinkler irrigation of the l'th ridge, t start,l' is the start time of sprinkler irrigation for the l'th ridge, R dynamic (t) is the sprinkler radius, t is the time, R0 is the maximum sprinkler radius, v(t) is the variable speed of the reel sprinkler, v max is the maximum speed of the reel sprinkler; If the sprinkler passes over the current ridge during its travel path, it means that the current ridge is compacted.

10. The method for field path planning of a reel-type sprinkler for reducing soil mechanical compaction according to claim 9, characterized in that: The step 33 in which the fluorescence brightness of the two fireflies is obtained is m' and I m* , get the fluorescence brightness difference and attraction of the two fireflies, specifically: ΔI m'm* =I m' -I m* r m'm* =||X' m' -X' m* || in, is the difference in fluorescence brightness between firefly m' and firefly m*, is the attraction between fireflies m' and m*, β0 is the maximum attraction, γ' is the attraction attenuation coefficient, is the Euclidean distance between firefly m' and firefly m*, X' m' is the location of the firefly m', is the position of the firefly m*.

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