Global Optimization Method for Grader Operation Path

Abstract

The present invention discloses a global optimization method for a grader operation path for leveling farmland. The method comprises the following steps: a digital elevation model of a field to be leveled is gridded, a position weight of a grid point is determined according to the position of the grid point in the field to be leveled, and the total earthwork volume of the field to be leveled, a target leveling elevation, and a planned excavation and filling volume of each grid are calculated in sequence; an ant colony algorithm is adopted, and the current load earthwork volume of each grid and the existing excavation and filling volume of the grid are used as criteria for node transfer; the path efficiency evaluation index of the best path of all cycles is the highest as the optimal path, and the optimal path is smoothed to obtain a globally optimized path; the present invention adopts the position weight of the grid point to obtain the total earthwork volume, thereby ensuring the accuracy of the earthwork volume calculation; the ant colony algorithm is improved to obtain an optimal operation path that balances the shortest distance and the highest efficiency; a path efficiency evaluation index is set, and the operation efficiency is effectively improved.

Description

Technical Field

[0001] The present invention belongs to the field of agricultural machinery, and relates to a land grader for leveling farmland, and in particular to a path planning method for the land grader operation. Background Art

[0002] In agricultural production, the levelness of farmland significantly impacts the efficiency of water, fertilizer, and pesticide application. Consequently, demand for land leveling equipment has rapidly increased in recent years. While existing land leveling equipment can meet agricultural production requirements for small-scale operations, it is less efficient when leveling large areas. Currently, agricultural production faces a shortage of human resources, and experienced agricultural machinery operators are even more scarce, leading to high land leveling costs.

[0003] Existing land-leveling equipment primarily consists of a leveling blade, which can automatically adjust during operation. This automation utilizes lasers or the Global Navigation Satellite System (GNSS) to acquire information such as the blade's height, attitude, and speed, and uses this information to adjust the blade's attitude in real time. This can achieve high accuracy within a small area, but due to the lack of path planning, achieving overall leveling over a large area requires repetitive rework, which is time-consuming and labor-intensive.

[0004] For leveling path planning, the main focus is on planning the shortest path. Land leveling operations need to consider factors such as the planned excavation and filling volume of the field, the load of the grader, and the steering characteristics. However, the existing shortest path planning process does not take these factors into account.

[0005] For earthwork volume calculation, the commonly used digital elevation model (DEM) calculation method is adopted. The principle is to select points on the target plot according to triangles or squares, and perform weighted averaging of the elevations of each point to obtain the average elevation. The weight coefficient used in the weighted averaging is estimated based on the terrain undulations around each point. Therefore, it is obvious that this average elevation has a certain error. In order to quantify this error, it is necessary to calculate the excavation and fill volume of each point based on the elevation difference between the elevation of each point and the estimated average elevation. The difference between the planned excavation volume and the planned fill volume is the error. Adjusting the weight coefficient of each point until the difference is zero will obtain a more accurate average elevation.

[0006] The DEM grid method is also applicable to calculating earthwork volume for farmland leveling. However, for most farmland that needs to be leveled, it has been used for agriculture for a long time and has a good flatness without significant terrain undulations. In this case, the weight coefficient used in the DEM grid method to reflect the ground undulation trend loses its meaning, which complicates the calculation.

[0007] The ant colony algorithm (ACO) works as follows: an ant colony consists of n ants, each with its own memory. This memory contains a taboo table to store nodes that the ant cannot access during the search, an allow table to store nodes that the ant can access, and a matrix to store the pheromones it releases along each path in a loop. Pheromones evaporate to a certain extent, influencing the ants' choices at forks in the road. Shorter paths accumulate pheromones more quickly, attracting more ants to follow the shortest path. Some ACO algorithms also incorporate a heuristic function to reflect the visibility of nodes between ants when choosing a path. Some shortest path planning methods employ ACO algorithms to optimize and determine the shortest path.

[0008] Ant colony algorithms have been applied to land-leveling path planning. However, because the amount of earthwork involved in land-leveling operations is not considered, land-leveling path planning is simply treated as an ant colony algorithm problem, with the shortest path search being performed. To effectively use the ant colony algorithm for land-leveling path planning, key aspects of the ant colony algorithm—node selection, tabu table update rules, heuristic function settings, and update rules—need to be improved to address the specific characteristics of land-leveling operations.

[0009] In summary, there is an urgent need for a global optimization method for the grader operation path to solve the above problems. Summary of the Invention

[0010] The purpose of the present invention is to provide a global optimization method for the operation path of a grader, integrating the rapid collection of three-dimensional farmland terrain information required for farmland leveling work and global path planning that conforms to the operation characteristics of the grader, so as to solve the problems of low working efficiency, low degree of automation and high labor cost of existing leveling equipment.

[0011] To solve the above problems, the technical solution adopted by the global optimization method of the grader operation path of the present invention is: collecting terrain information of the field to be leveled to obtain a digital elevation model of the field to be leveled, and further comprising the following steps:

[0012] Step 1): The digital elevation model is rasterized using a grid, and the position weight of the grid point is determined according to the position of the grid point in the field to be leveled;

[0013] Step 2): According to the position weight of each grid point, calculate the total earthwork volume V of the field to be leveled, the target leveling elevation H of the field to be leveled e And the planned excavation and filling volume V for each grid g ;

[0014] Step 3): Using the ant colony algorithm, the planned excavation volume V in all grids g The largest grid center point is taken as the starting point, and the planned excavation and filling volume V in all grids is used. gThe grid closest to 0 is taken as the end point, and the planned excavation volume V in all grids is used. g The absolute value of V g |Reach the set earthwork volume threshold V s The center point of the grid is used as the node; the current load earthwork volume V of the leveling blade of each grid L The existing volume of earthwork to be excavated and filled in the grid V P As the criterion for node transfer, the load status of the leveler is used to determine whether the node should be placed in the taboo table. After completing one cycle, the optimal path P is obtained.

[0015] Step 4): Calculate the path efficiency evaluation index I of the optimal path P, and update the number of cycles and the taboo table;

[0016] Step 5): Determine whether the number of cycles or the path efficiency evaluation index I is reached. If so, the one with the highest path efficiency evaluation index I among all the best paths P of the cycles is taken as the optimal path P. b , for the optimal path P b Smoothing is performed to obtain the global optimization path B(u).

[0017] The present invention has the following technical effects after adopting the above technical solution:

[0018] 1. The traditional digital elevation model grid method is to perform a weighted average of the elevations of each grid point to obtain an average elevation. The amount of earthwork cut and fill is then calculated based on the average elevation. The weights are then adjusted until the amount of earthwork cut and fill are essentially equal. This method takes into account the possible steep rises and falls of the ground, and therefore uses elevation weights to reflect different terrains, resulting in very low computational efficiency. The present invention takes into account that farmland is often relatively flat and changes smoothly, but the farmland area is large, so elevation weights are of little significance and increase the computational complexity. Based on the characteristics of farmland leveling operations, the digital elevation model grid method is improved, abandoning the traditional complex elevation weight averaging method and using the position weights of the grid points to obtain the total earthwork volume. This ensures the accuracy of the earthwork volume calculation while greatly reducing the computational complexity.

[0019] 2. Since the operation path planning of the grader is not a simple shortest path planning, it is necessary to comprehensively consider factors such as the operation path length, machine load condition, and planned operation volume. Therefore, the present invention improves the ant colony algorithm. The starting point, end point, and path nodes of the ant colony algorithm are selected according to the grid planned excavation and filling volume. The priority of the grader's forward direction, the real-time earth load of the grader, and the planned excavation and filling volume of the target node are linked to the heuristic function of the ant colony algorithm. Together with the pheromone reflecting the path length, it affects the forward probability between nodes, and can obtain the optimal operation path that balances the shortest distance and the highest efficiency.

[0020] 3. The present invention sets a path efficiency evaluation index based on the grader's operating efficiency characteristics. By comparing the total cut and fill volume of the grader during the planned path with the total planned cut and fill volume of each grid along the route, the index reflects the proportion of the grader's effective operation along the route, that is, the proportion of the grader's operation that is not in an idle state due to an empty or fully loaded blade, thereby effectively improving the grader's operating efficiency.

[0021] 4. The present invention uses a second-order Bezier curve to smooth the planned optimal path, adapting to the steering characteristics of the grader, providing global optimization of the operation path for land leveling work, obtaining a precise optimal path, and promoting the improvement of the working efficiency of the farmland grader. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the specific implementation methods. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0023] Figure 1 is a flow chart of the global optimization method for the grader operation path of the present invention;

[0024] Figure 2 yes Figure 1 Flowchart of the method for constructing a three-dimensional terrain model;

[0025] Figure 3 yes Figure 1 Flowchart of the method for obtaining the planned cut and fill volume;

[0026] Figure 4 yes Figure 1 The effect diagram of the field after rasterization and the marking diagram of relevant parameters and grid points;

[0027] Figure 5 yes Figure 4 A diagram showing the four corner points and the center point of any grid;

[0028] Figure 6 yes Figure 4 A diagram showing the nodes of the local grid and the edges corresponding to the paths between nodes;

[0029] Figure 7 yes Figure 1 Flowchart of the improved ant colony algorithm. DETAILED DESCRIPTION

[0030] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments described herein are only a portion of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0031] like Figure 1 As shown, the terrain information of the field to be leveled is collected and a three-dimensional terrain model of the field to be leveled is constructed. Figure 2 , drive a device equipped with a global navigation satellite system (GNSS) positioning function to perform a traversal run on the field to be leveled to collect the terrain information of the field to be leveled. During the traversal run, the RTK positioning data of the device is periodically obtained through GNSS, which includes the horizontal position X, Y data and altitude H data, and three-dimensional coordinate points (X, Y, H). The above data are recorded, and the three-dimensional terrain model of the field to be leveled is reconstructed from these three-dimensional coordinate points (X, Y, H). The altitude H data can also be obtained using a laser method. Since the GNSS method has better adaptability to the working environment and is more widely used, the present invention adopts the GNSS method to obtain data. The established three-dimensional terrain model is the prerequisite for subsequent path planning and other work.

[0032] like Figure 3 As shown, based on the three-dimensional terrain model of the field to be leveled, a digital simulation of the ground topography is achieved through limited three-dimensional coordinate point (X, Y, H) data to obtain a digital elevation model (DEM). In order to reduce the computational complexity, the present invention adopts a zero-order single-item digital landform model, namely a digital elevation model.

[0033] The digital elevation model is rasterized, and the rasterization mainly includes regular grid and triangulated grid. Since the regular grid method is more conducive to using GPS measurement data for calculating earthwork volume and the calculation is relatively simple, the grid is used in the present invention.

[0034] The flattened field is rasterized according to the set side length L. The grid effect after the local rasterization of the flattened field is as follows Figure 4 As shown, Figure 4 The outermost frame is the outline of the field to be leveled. Since most farmland plots are close to rectangles, the X axis is set to be parallel or nearly parallel to the short side of the field, and the Y axis is set to be parallel or nearly parallel to the long side of the field.

[0035] Rasterization of the fields takes into account the ground characteristics and the operating characteristics of the grader, reducing computational complexity while maintaining accuracy. Since most farmland requiring land leveling has already been used for farmland, it has good flatness and gentle surface changes, with few sharp rises or falls. Therefore, rasterization further reduces data volume without causing significant deviations. Taking into account the operating and turning characteristics of the grader, the grid side length L is set equal to the operating width of the grader's blade.

[0036] After rasterization, the three-dimensional coordinates (X, Y, H) of each grid point are obtained. The weight of the grid point is determined according to its location in the field to be leveled. The location of the grid point in the field to be leveled refers to the middle point of the grid, the edge point, or the inward or outward corner point. There is no need for complex estimation. Figure 4 As shown, when the grid point is at the middle point m(X m , Y m , H m ), the position weight of the middle point m is determined to be 4, where X m , Y m is the horizontal position of the middle point m, H m is the elevation of the middle point m. When the grid point is at the inner corner point c1(X c1 , Y c1 , H c1 ), the position weight of the inward corner point c1 is determined to be 3, where X c1 , Y c1 is the horizontal position of the inward corner point c1, H c1 is the elevation of the inward corner point c1. s , Y s , H s ), the position weight of edge point s is determined to be 2, where X s , Y s is the horizontal position of edge point s, H s is the elevation of the edge point s. c2 , Y c2 , H c2 ), its position weight is determined to be 1, where X c2 , Y c2 is the horizontal position of the outward corner point c2, H c2 is the elevation of the outward corner point c2.

[0037] After determining the position weight of each grid point, the total earthwork volume V of the field to be leveled is calculated according to the following formula:

[0038]

[0039] Among them, S g is the area of ​​a single grid; H m H is the elevation of the grid point at the middle point of the grid; c1 H is the elevation of the grid point at the inner corner of the grid; s H is the elevation of the grid point at the edge of the grid; c2 The elevation of the grid point at the outward corner of the grid.

[0040] Calculate the average elevation H of the field to be leveled based on the total earthwork volume V e , that is, the target flat ground elevation H e :

[0041]

[0042] Where S is the total area of ​​the field to be leveled. Ideally, land leveling does not require moving earth in or out, and the amount of excavation and filling within the field should be balanced. Therefore, the target leveling elevation H is e It represents the ideal elevation of the field after it is leveled.

[0043] According to the target flat ground elevation H e Calculate the planned excavation and filling volume V for each grid g ,like Figure 3 As shown, the calculation formula is:

[0044]

[0045] Among them, H is the elevation of the four corner points of the corresponding grid; when the planned excavation and filling volume V g When it is greater than 0, it means that this grid needs to be excavated; when the planned excavation and filling volume V g When it is less than 0, it means that this grid needs to be filled; when the planned excavation and filling volume V g When it is equal to 0, it means that the earthwork volume of this grid does not need to be increased or decreased.

[0046] The four corner points and center point of any grid are as follows Figure 5 As shown, its four corner points are A1, A2, A3, and A4, and the center point is O.

[0047] The planned excavation and filling volume V of each grid is obtained g Then, according to the horizontal position (X, Y) of each grid center point O and the planned excavation and filling volume V of the corresponding grid, g , using Figure 7 The improved ant colony algorithm is used to plan the path of the grader and the optimal path P is obtained. b The specific method is:

[0048] Step 1: Set the starting point, end point and path nodes of the ant colony algorithm.

[0049] Compare the planned cut and fill volumes V of each grid g The size of the earthwork volume V in all grids is g The largest grid center point is used as the starting point. Because the initial state of the grader is no-load, the planned excavation and filling volume V g Starting with the largest grid allows the blade to be fully loaded in the first grid, maximizing load utilization.

[0050] The planned excavation and filling volume V in all grids g The grid closest to 0 is taken as the end point. Because when the grader is actually running, the load should be cleared before reaching the end point, and it should arrive at the end point empty and start the next round of work.

[0051] The planned earthwork volume V in all grids g The absolute value of V g |Reach the set earthwork volume threshold V s The center point of the grid is used as the node of the ant colony algorithm, and the earthwork threshold V is set s When the earthwork volume threshold V s The size should be consistent with the maximum load capacity V of the leveling blade Lmax related, and should be much smaller than the maximum load V Lma .

[0052] Due to the inevitable errors in earthwork volume calculation, after the grader completes the leveling work according to the optimal path, it needs to perform at least one traversal operation to eliminate the small errors in the operation. Therefore, the planned excavation and filling volume V g Very small grids can be excluded from the necessary nodes during path planning, because the passage of the working path and the final traversal operation can easily make them reach the leveling goal.

[0053] Step 2: Initialize the parameters of the ant colony algorithm, including the number of ants n, the number of cycles N, and the edges e corresponding to the paths between nodes. ij Initial pheromone intensity τ ij ; The edge e corresponding to the path between each node ij The initial level of inspiration η ij , i and j represent two different nodes.

[0054] like Figure 6 As shown, the edge e corresponding to the path between each node ij like Figure 6 As shown, the path between the node O1 (X1, Y1) of the first grid and the node O2 (X2, Y2) of the second grid corresponds to the edge e 12, the path between the node O2(X2,Y2) of the second grid and the node O3(X3,Y3) of the third grid corresponds to the edge e 23 , the path between the node O2 (X2, Y2) of the second grid and the node O4 (X4, Y4) of the fourth grid 3 corresponds to the edge e 24 .

[0055] Step 3: Set the ants' movement rules based on the grader's movement pattern.

[0056] Ants can only move along the X-axis and Y-axis. When moving from one grid node to the next, they can only choose the grids in the front, left, and right directions.

[0057] Step 4: Calculate the forward probability of the ant when transferring between nodes, and perform node transfer according to the operation characteristics of the grader.

[0058] When any ant k moves between nodes, the probability of moving from node i to node j within the cycle time t is The calculation formula is as follows:

[0059]

[0060] Among them, τ ij is the edge e corresponding to the path between node i and node j ij Pheromone intensity on ;η ij is the visibility factor between node i and node j, reflecting the degree of inspiration from i to j; α is the importance index of pheromone; β is the importance index of heuristic factor.

[0061] During node transfers, the rules need to be implemented based on the grader's operating characteristics. Since the grader's steering can cause additional operating deviations, straight driving takes precedence over left and right turns during node transfers.

[0062] After the grader passes each grid, the current load earthwork volume V of the grader blade passing each grid is recorded. L And the grid's existing volume of earthwork to be excavated and filled V P , which is used as the criterion for node transfer. The existing volume of earthwork to be excavated and filled in the grid is V P The initial value of is the planned excavation and filling volume V g .

[0063] Planned cut and fill volume V for each grid g When excavation is required, the planned earthwork volume is counted as a positive value, and when backfill is required, the planned earthwork volume is counted as a negative value. When a motor grader is operating, running the blade empty or fully loaded for extended periods of time is considered idling and should be avoided for operational efficiency.

[0064] The current earthwork volume V of the leveling blade L Less than the maximum load V Lmax When the load of the next node is half of the original load, the next node should increase the load to avoid empty running. Therefore, the node with the existing earthwork volume to be excavated and filled V is preferred. P Earthwork volume V with existing load of blade L Add up the maximum load V of the closest leveling blade Lmax Node.

[0065] The existing load capacity V of the shovel L Greater than the maximum load V Lmax When the load of the next node is half of the total load, the next node should reduce the load to avoid full load and empty running. Therefore, the node grid with the existing earthwork volume V to be excavated and filled is preferred. P The current earthwork volume V of the blade L Add up the nodes closest to 0.

[0066] Step 5: Determine whether the node should be put into the taboo list based on the load status of the leveling shovel.

[0067] Current load volume V of the leveling blade L It also reflects the working status of the grader at the corresponding node. If the grader passes the node with the grader shovel fully loaded or empty, it represents the planned excavation and filling volume V for this node. g Not satisfied; on the contrary, if the motor grader passes the node and the motor grader is not in a fully loaded or empty state, it means that the planned excavation and filling volume of this node is V g Completed. If a grader passes through one of the nodes for the first time in this cycle, the planned excavation and filling volume V is reached. g , represents the planned excavation and filling volume V of this grid g If the node is smaller than the default value and does not need to be included in the planned path, the node is put into the taboo table of this cycle.

[0068] Step 6: After completing a cycle, record the best path P of this cycle and calculate the path efficiency evaluation index I of this best path P. Update the number of cycles and taboo table according to the path efficiency evaluation index I, and update the pheromone.

[0069] The calculation formula of the path efficiency evaluation index I is as follows:

[0070]

[0071] Among them, V d Represents the total amount of earth removed by the grader path, V f Represents the total fill volume of the grader path, V gl Represents the amount of cut and fill required for each grid on the path. The closer the path efficiency evaluation index I is to 1, the less empty runs caused by the shovel being empty or full on the path, and the higher the operation efficiency.

[0072] The edge e corresponding to the road between two nodes i and j ij The formula for calculating the increment of the pheromone factor over the cycle is as follows:

[0073]

[0074] Where Δτ ij (t, t+1) is the number of nodes passing through edge e ij All ants on the edge e ij pheromone amount contribution; It is the edge e of ant k ij is the pheromone increment contributed by the ants; ρ is the pheromone residual coefficient; Q is the total amount of pheromone released by all ants on the path after one cycle; L k is the length of the path taken by the ant in this cycle.

[0075] Step 7: Determine whether the number of cycles has been reached or whether there is a cycle that reaches the path efficiency evaluation index I. If so, end the cycle and use the path efficiency evaluation index I with the highest among all the best paths P of the cycle as the optimal path P for the field leveling operation. b , for the optimal path P b Perform smoothing and output the path planning results.

[0076] Use the efficiency evaluation index I as the optimal path P b The reason why the optimal path is selected is that in land leveling work, the impact of the grader running empty or fully loaded due to the empty or fully loaded grader on the total operation time is much greater than the operation path length. In addition, according to the principle of the ant colony algorithm, the length of the optimal path P in each cycle is already close to the theoretical shortest path length. Therefore, the present invention does not use path length as the criterion for selecting the optimal path.

[0077] In order to adapt to the steering characteristics of the grader, the optimal path P b All turning points are smoothed using the second-order Bezier curve to obtain the second-order Bezier curve B(u), which is the global optimization path B(u). The expression of the second-order Bezier curve B(u) is:

[0078] B(u)=(1-u) 2 P0+2u(1-u)P1+u 2 P2 0≤u≤1

[0079] by Figure 6Take the turning path from the first grid to the second grid and then to the third grid as an example, where u is the independent variable of the curve; P0 is the horizontal coordinate of the node of the grid before turning, that is, the first node (X1, Y1); P1 is the horizontal coordinate of the node of the grid where the turning occurs, that is, the second grid node (X2, Y2); P2 is the horizontal coordinate of the node of the grid after turning, that is, the third grid node (X3, Y3).

Claims

1. A global optimization method for the operation path of a land grader, which collects the terrain information of the land to be leveled and obtains a digital elevation model of the land to be leveled, characterized by: The following steps are involved: Step 1): The digital elevation model is rasterized using a grid, and the position weight of the grid point is determined according to the position of the grid point in the field to be leveled; When a grid point is at the middle point of the grid, its position weight is 4; when a grid point is at the inner corner of the grid, its position weight is 3; when a grid point is at the edge of the grid, its position weight is 2; when a grid point is at the outer corner of the grid, its position weight is 1; Step 2): According to the position weight of each grid point, calculate the total earthwork volume V of the field to be leveled, the target leveling elevation H of the field to be leveled e And the planned excavation and filling volume V for each grid g ; According to the formula Calculate the total earthwork volume V of the field to be leveled, according to the formula Calculate the target ground elevation H of the field to be leveled e , according to the formula Calculate the planned excavation and filling volume V for each grid g ;S g is the area of ​​a single grid; H m H is the elevation of the grid point at the middle point of the grid; c1 H is the elevation of the grid point at the inner corner of the grid; s H is the elevation of the grid point at the edge of the grid; c2 is the elevation of the grid point at the outward corner of the grid; S is the total area of ​​the field to be leveled; H is the elevation of the four corner points of the grid; Step 3): Using the ant colony algorithm, the planned excavation volume V in all grids g The largest grid center point is taken as the starting point, and the planned excavation and filling volume V in all grids is used. g The grid closest to 0 is taken as the end point, and the planned excavation volume V in all grids is used. g The absolute value of V g |Reach the set earthwork volume threshold V s The center point of the grid is used as the node; the current load earthwork volume V of the leveling blade of each grid L The existing volume of earthwork to be excavated and filled in the grid V P As the criterion for node transfer, the load status of the leveler is used to determine whether the node should be placed in the taboo table. After completing one cycle, the optimal path P is obtained. Step 4): Calculate the path efficiency evaluation index I of the optimal path P, and update the number of cycles and the taboo table; Step 5): Determine whether the number of cycles or the path efficiency evaluation index I is reached. If so, the one with the highest path efficiency evaluation index I among all the best paths P of the cycles is taken as the optimal path P. b , for the optimal path P b Smoothing is performed to obtain the global optimization path B(u).

2. The global optimization method for a motor grader operation path according to claim 1, characterized in that: A traversal run is performed on the field to be leveled to collect the terrain information of the field to be leveled, and RTK positioning data is periodically obtained through GNSS to obtain three-dimensional coordinate points. The three-dimensional coordinate points are used to digitally simulate the ground terrain to obtain a digital elevation model.

3. The global optimization method for a motor grader operation path according to claim 1, characterized in that: In step 1), the side length of the grid is set to be equal to the working width of the grader blade.

4. The global optimization method for a motor grader operation path according to claim 1, characterized in that: In step 3), according to the travel mode of the grader, the ant is set to only be able to choose the grids in the front, left and right directions when driving from one grid node to the next, and the priority of going straight is higher than turning left or right.

5. The global optimization method for a motor grader operation path according to claim 4, characterized in that: After the grader passes each grid, when the current load of the grader blade is V L Less than the maximum load V Lmax When the existing earthwork volume to be excavated and filled V is half of the P Earthwork volume V with existing load of blade L Add up the maximum load V of the closest leveling blade Lmax Node; when the existing load of the shovel is V L Greater than the maximum load V Lmax When the existing earthwork volume V to be excavated and filled in the node grid is half of P The current earthwork volume V of the blade L Add up the nodes closest to 0.

6. The global optimization method for a motor grader operation path according to claim 5, characterized in that: If a grader passes through one of the nodes for the first time, the planned excavation and filling volume V is reached. g , then put this node into the taboo table.

7. The global optimization method for a motor grader operation path according to claim 1, characterized in that: In step 4): According to the formula Calculate the path efficiency evaluation index I, V d is the total excavation volume of the grader path, V f is the total fill volume along the grader path, V gl It is the amount of cut and fill required for each grid on the path.

8. The global optimization method for a motor grader operation path according to claim 1, characterized in that: In step 5), a second-order Bezier curve is used for smoothing to obtain a second-order Bezier curve B(u)=(1-u) 2 P0+2u(1-u)P1+u2, u is the independent variable of the curve, 0≤u≤1; P0 is the horizontal coordinate of the node in the grid before the grader turns, P1 is the horizontal coordinate of the node in the grid where the turn occurs, and P2 is the horizontal coordinate of the node in the grid after the turn.

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