A method for simultaneously planting and managing agricultural machinery

Abstract

The present invention discloses a method for planting, managing and tracking operations of intelligent agricultural machinery, comprising the following steps: building a planting, managing and tracking system, which includes a terminal unit and a background server; loading the terminal unit on an intelligent agricultural machinery; performing planting by the intelligent agricultural machinery, recording trajectory information of the planting operation, and uploading the information to the background server; when entering the later stage of field management or harvesting, the intelligent agricultural machinery loaded with the terminal unit is connected to the background server, and downloads the operation trajectory information of the designated field in the planting stage; if the operation trajectory of the intelligent agricultural machinery in the planting stage is inconsistent with the operation trajectory of the intelligent agricultural machinery in the later stage of field management or harvesting, the planting operation trajectory information needs to be adjusted and processed to obtain operation trajectory information adapted to the intelligent agricultural machinery in the later stage of field management or harvesting; the intelligent agricultural machinery in the later stage of management or harvesting completes the tracking operation according to the adapted operation trajectory information obtained through the adjustment.

Description

Technical Field

[0001] The present invention relates to an agricultural management method, and in particular to an intelligent agricultural machinery planting and management simultaneous operation method. Background Art

[0002] Currently, when smart agricultural machinery navigates crops, it only analyzes and processes the operating environment faced by the current link and performs operations, separating the various links of farming, management, and harvesting. During navigation operations, it mainly uses AB points for straight-line path planning and straight-line operations. Although this improves operating efficiency in vast farmland operations, this method is too idealistic and is still acceptable for use in arable land and planting stages where crops have not yet grown. Once the crop management and harvesting stages begin, due to the influence of various factors such as different field types, types of operating equipment, and planting methods, smart agricultural machinery will experience varying degrees of slippage and drift during planting operations, resulting in an offset in the actual planting position of the crops and the inability to complete the planting of the crops in the same straight line. For example, the shape of the rice seedling belt planted by an unmanned transplanter will still appear as an irregular curve. This will inevitably cause damage to crops when smart agricultural machinery uses the AB point straight-line operation method, reducing crop yields and failing to meet the requirements of refined agricultural management. Summary of the Invention

[0003] The purpose of the present invention is to overcome the above-mentioned problems and provide a method for the same-track operation of intelligent agricultural machinery for planting, management and harvesting. The method records the operation trajectory information of agricultural machinery in the early farming stage, provides operation trajectory guidance information for the later management and harvesting stages, and can carry out fine management of crops, so that the intelligent agricultural machinery can operate in accordance with the actual planting position of the crops, optimize the operation path, and reduce the crop damage rate caused by agricultural machinery operations.

[0004] The purpose of the present invention is achieved through the following technical solutions:

[0005] A method for simultaneously planting and managing crops with an intelligent agricultural machine comprises the following steps:

[0006] Step 1: Building a system for planting, managing and tracking plants in the same track. The system includes a terminal unit and a backend server. The terminal unit is connected to the backend server via a network and includes a navigation and positioning module, a display module, a data transmission module and a processor module.

[0007] Step 2: Install the terminal unit of the planting, management and tracking system on the intelligent agricultural machine; perform planting through the intelligent agricultural machine, record the trajectory information of the planting operation, and upload it to the backend server;

[0008] Step 3: When the crops are planted and enter the later stage of field management or harvesting, the intelligent agricultural machinery performing field management or harvesting is equipped with the terminal unit of the planting, management and tracking system. Before entering the designated field for operation, the intelligent agricultural machinery connects to the backend server and downloads the operation trajectory information of the designated field in the planting stage stored in the backend server;

[0009] Step 4: If the operation trajectory of the intelligent agricultural machinery in the planting stage is inconsistent with the operation trajectory of the intelligent agricultural machinery in the later field management or harvesting stage, the intelligent agricultural machinery in the later field management or harvesting stage needs to adjust the operation trajectory information to obtain the operation trajectory information that is compatible with the intelligent agricultural machinery in the later field management or harvesting stage;

[0010] Step 5: In the later management or harvesting stages, the intelligent agricultural machinery completes the same operation based on the adapted operation trajectory information obtained through adjustment.

[0011] In a preferred embodiment of the present invention, in step one, the positioning module is an RTK module of the Beidou navigation satellite system, and the RTK module is connected to the processor module via a data cable; the RTK module sends the received positioning information to the processor module. After receiving the positioning information of the two RTK modules, the processor module calculates the real-time positioning coordinates of the center point of the intelligent agricultural machinery, the azimuth of the fuselage direction, and the driving speed, and at the same time sets a target coordinate point for the intelligent agricultural machinery, and navigates the agricultural machinery to the target point according to the distance and heading between the current position of the machinery and the target point.

[0012] Furthermore, two RTK modules are mounted on the left and right ends of the frame of the intelligent agricultural machinery in a manner symmetrical to the central axis of the fuselage. The connection line between the two RTK modules is perpendicular to the forward direction of the intelligent agricultural machinery. The RTK module establishes a real-time data connection with the Beidou navigation satellite and multiple base stations to receive positioning information.

[0013] In a preferred embodiment of the present invention, in step one, the processor module is connected to the display module, and the positioning data processing results, the machine operation status, and the field operation completion rate are displayed through the display module; after the intelligent agricultural machinery completes the operation of the designated field, the positioning information of the entire operation process of the intelligent agricultural machinery is recorded and a set of field operation trajectory information is temporarily stored in the display module in the form of a series of coordinate points.

[0014] In a preferred embodiment of the present invention, in step 1, the display module is connected to the data transmission module, which is connected to the background server through the data transmission module to upload the operation trajectory information to the background server or download the operation trajectory information from the background server.

[0015] In a preferred embodiment of the present invention, in step 2, before the planting operation, a straight line is marked at points A and B at both ends of the field, and the field path is planned based on the line; the path planning is performed by the processor module;

[0016] During the planting operation, the real-time positioning information of the intelligent agricultural machinery passing by is transmitted to the processor module through the positioning module, and the processor module processes the positioning information and controls the intelligent agricultural machinery to perform navigation operations; the processed positioning information is transmitted and temporarily stored in the form of a set of geodetic coordinates. After the intelligent agricultural machinery completes the operation of any field, the field will be marked with a designated number and its corresponding operation trajectory information will be connected to the background server through the data transmission module, and the operation trajectory information in the geodetic coordinate format will be uploaded to the background server for storage, so that other intelligent agricultural machinery can download the operation trajectory information.

[0017] In a preferred embodiment of the present invention, in step 4, the method for adjusting the operation trajectory information is as follows:

[0018] Convert the operation trajectory information from geodetic coordinates to the plane coordinates of the earth projection, and then use all the positioning coordinate points in the original trajectory information as the reference to calculate the new operation path coordinates in the plane coordinate system according to the azimuth and distance;

[0019] Assume that the coordinates of the original trajectory point A are (Xa, Ya), and the coordinates of the coordinate point B to be determined are (Xb, Yb). The straight-line distance between point B and point A is L, and the azimuth of point B relative to point A is M, with true north as 0 degrees. The coordinates of B can be obtained using the following formula:

[0020] Xb=Xa+(L*cos(M));

[0021] Yb=Ya+(L*sin(M)).

[0022] Furthermore, let the number of operating rows of the intelligent agricultural machinery in the early planting stage be a, the number of operating rows of the intelligent agricultural machinery in the later field management or harvesting stage be b, and the distance between crop rows be d. With the original operation trajectory information as the center, parallel trajectories are calculated to the left and right sides respectively. The number and spacing of these parallel trajectories depend on the number of operating rows of the agricultural machinery in the two stages:

[0023] When a / b is an odd number, the original trajectory is retained as one of the rows of the new trajectory, and n = (a / b-1) / 2 parallel trajectories are calculated to the left and right sides respectively, and the distance between adjacent parallel trajectories is P = b*d;

[0024] When a / b is an even number, the original trajectory is not retained, and it is used as the basis for calculation to both sides. The number of parallel trajectories on both sides is The distance between the original track and its two adjacent parallel tracks is P1 = b*d / 2, and the distance between the remaining parallel tracks is P2 = b*d. Based on the original track as a reference, the above numbers and distances can be used to complete the calculation.

[0025] After the calculation is completed, the reorganized trajectory information is converted from plane coordinates back into geodetic coordinates in latitude and longitude format for intelligent agricultural machinery to complete navigation operations.

[0026] Furthermore, the operation trajectory information recorded in the early planting phase is a series of dense positioning coordinate points. It is necessary to select feature points from the operator's trajectory information. The standard for selecting feature points is to ensure that the intelligent agricultural machinery does not touch or damage the crops during operation. The method is as follows:

[0027] When the crop row has a bend, the curvature of the crop row under the extreme working condition is taken, and the intelligent agricultural machine is made to travel at the minimum turning radius. The distance between its outermost planting point and the steering center is taken as R, and the distance between two adjacent planting points of the agricultural machine is taken as L. This is the maximum bend angle of the crop row planted by the intelligent agricultural machine. At this bend angle, the intelligent agricultural machine's travel wheels start to move toward the next feature point at the midpoint between the two crop rows.

[0028] If the crop is not touched, the maximum driving angle occurs when the driving direction is tangent to the outermost crop row, that is, the maximum straight-line distance between feature points can be taken as By selecting and rearranging the feature points of the operation trajectory information at intervals of this distance, an operation path that is compatible with intelligent agricultural machinery for subsequent field management or harvesting can be generated.

[0029] In a preferred embodiment of the present invention, in step 5, during the same-track operation, the processor module sequentially uses the coordinates of the feature points arranged in the adapted operation trajectory information as the target coordinate points of the intelligent agricultural machine. When the intelligent agricultural machine reaches a target point, the next feature point is used as the new target point until the same-track operation of the field is completed.

[0030] During the same-track operation, the real-time trajectory information of the operation is received through the positioning module, and the geodetic coordinates in the form of longitude and latitude are stored in the background server through the data transmission module.

[0031] A preferred embodiment of the present invention is that, after the intelligent agricultural machinery completes the same-track operation, the operation trajectories of the early stage of crop planting and the later management or harvesting stages are compared, the data of the operation trajectory are analyzed, and the operation speed of the intelligent agricultural machinery and the selection of operation trajectory feature points are optimized based on the data, thereby improving the degree of refinement of crop planting management by the same-track operation method.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. The intelligent agricultural machinery planting and management method of the present invention records the agricultural machinery operation trajectory information in the early tillage stage, provides operation trajectory guidance information for the later management or harvesting stage, and can carry out refined management of crops, so that the intelligent agricultural machinery can operate in accordance with the actual planting position of the crops, optimize the operation path, and reduce the crop damage rate caused by agricultural machinery operations.

[0034] 2. When applying the operation trajectory information of the early planting stage in the same operation of the later management or harvesting stage, the operation trajectory information is adapted and adjusted to obtain the target operation path that fits the planting position of the crop so as to carry out the operation, thereby achieving the purpose of reducing the crop damage rate and improving the adaptability of intelligent agricultural machinery to complex planting conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a schematic diagram of the trajectory information adaptation and adjustment of the intelligent agricultural machinery planting and management operation method of the present invention.

[0036] Figure 2 This is a schematic diagram of the overall feature point selection for trajectory information adaptation and adjustment of the intelligent agricultural machinery planting and management operation method of the present invention.

[0037] Figure 3 This is a schematic diagram of the selection of local feature points for adaptive adjustment of trajectory information in the intelligent agricultural machinery planting and management operation method of the present invention.

[0038] Figure 4-5 Schematic diagram of operation path calculation under two different situations of the intelligent agricultural machinery planting and management operation method of the present invention. DETAILED DESCRIPTION

[0039] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described below in conjunction with embodiments and drawings, but the embodiments of the present invention are not limited thereto.

[0040] The intelligent agricultural machinery planting and management simultaneous operation method of this embodiment includes the following steps:

[0041] Step 1. The system required for the same-track operation method includes the Beidou navigation satellite system RTK module (positioning module), embedded board (processor module), 4G module (data processing module), visualization terminal (display module), and cloud server platform (backend server). The intelligent agricultural machinery that uses the same-track operation method is equipped with a system. Each intelligent agricultural machinery is equipped with two Beidou navigation satellite system RTK modules on the left and right ends above its frame in a manner symmetrical to the central axis of the fuselage. The connection line between the two RTK modules is perpendicular to the forward direction of the agricultural machinery. The RTK module establishes a real-time data connection with the Beidou navigation satellite and multiple base stations to receive positioning information, which can provide centimeter-level positioning accuracy. The RTK module connects to the embedded control board via a data cable and transmits the received positioning information to the embedded control board. After receiving the positioning information from both RTK modules, the embedded control board calculates the real-time positioning coordinates of the intelligent agricultural machine's center point (in geodetic coordinates in longitude and latitude), the machine's azimuth, and its travel speed. It also sets a target coordinate point for the machine and guides it toward the target point based on the distance and heading between the machine's current position and the target point. The embedded control board is connected to a visualization terminal, which displays information such as positioning data processing results, machine operating status, and field operation completion rate. After the intelligent agricultural machine completes a designated field operation, its entire positioning process is recorded and temporarily stored on the visualization terminal as a series of coordinate points, forming a field operation trajectory. The visualization terminal is connected to a 4G module, which transmits and receives 4G signals to connect to a cloud server platform, allowing it to upload and download operation trajectory information to and from the cloud server.

[0042] Step 2: The intelligent agricultural machinery equipped with the system described in Step 1 performs path planning through the system's embedded board in its operation link (mainly in the plowing and planting links) and performs automatic navigation operations in the field. Since there are no crops or other obstacles in the field that affect the operation of the machine in the early plowing and planting links, the intelligent agricultural machinery can mark an operation straight line by marking points A and B at both ends of the field, and use this to plan the field path and complete the operation. During its operation, the RTK module on the machine will receive all positioning information of the agricultural machinery passing through in real time during the operation, and transmit it to the embedded board in real time. The embedded board processes the positioning information and controls the agricultural machinery to perform navigation operations. The processed positioning information is transmitted in the form of a set of geodetic coordinates and temporarily stored in the visualization terminal. After the intelligent agricultural machinery completes the operation of any field, it will mark the field with a specific number corresponding to its operation trajectory information. The visualization terminal is connected to the cloud server through the 4G module, and the operation trajectory information in the geodetic coordinate format is uploaded to the cloud server for storage, making it convenient for other intelligent agricultural machinery to download the operation trajectory information.

[0043] Step three, when the crops are planted and enter the later stage of field management and harvesting, the intelligent agricultural machinery performing field management or harvesting operations is also equipped with the system described in step one. Before the intelligent agricultural machinery enters the designated field for operation, the visualization terminal is connected to the cloud server through the 4G module, and searches and downloads the operation trajectory information of the intelligent agricultural machinery in the designated field during the planting stage stored in the cloud server according to the field number.

[0044] In step 4, after the intelligent agricultural machinery in the management and harvesting phase obtains the operation trajectory information of the intelligent agricultural machinery in the planting phase, the visualization terminal transmits the trajectory information to the embedded board. Because different machines have different parameters such as wheelbase, number of operating rows, and turning radius, the trajectory information needs to be adapted to meet the needs of agricultural machinery in different stages to complete the same operation. If the number of operating rows of the intelligent agricultural machinery in the planting phase is inconsistent with that of the intelligent agricultural machinery in the management and harvesting phase, the agricultural machinery in the later phase needs to reprocess the operation trajectory information and convert the trajectory into a target path that meets the operation range of the machine. For example, the agricultural machinery in the planting phase can plant six rows of crops in a single operation, while the agricultural machinery in the later management phase can only manage two rows of crops in a single operation. Since the six rows of crops are planted simultaneously, the operation trajectory information of each row in the early planting phase can be reorganized into three parallel rows of trajectory information to meet the application of intelligent agricultural machinery in the management phase.

[0045] The calculation and reconstruction process of the operation trajectory information mainly includes converting the operation trajectory information from geodetic coordinates to plane coordinates of the earth projection, and then using all the positioning coordinate points in the original trajectory information as a reference, and calculating the corresponding operation path coordinates on the plane coordinate system according to the azimuth and distance. For example, if the coordinates of the original trajectory coordinate point A are (Xa, Ya), the coordinate value of the coordinate point B (Xb, Yb) needs to be calculated. The straight-line distance between point B and point A is L, and the azimuth of point B relative to point A is M (with the true north direction as 0 degrees as the reference), then Xb = Xa + (L*cos(M)), Yb = Ya + (L*sin(M)), and the coordinate points of other positions can be calculated based on the original trajectory coordinate points according to the relative distance and azimuth. Specifically, the above-mentioned straight-line distance L and azimuth M are measured according to the actual data required:

[0046] For example, the current agricultural machinery is working on a row of seedlings, facing due north, that is, the azimuth is 0. The coordinate point of a seedling below the position of the agricultural machinery is (X1, Y1). It is necessary to calculate the position of the seedling to its right. Because the seedlings planted by the transplanter are 30 cm apart, the straight-line distance here is L = 30. Then, because it is on the right side, the target azimuth M = 0 + 90 = 90 degrees, so the coordinates of the seedling on the right are calculated (X2, Y2).

[0047] See also Figure 1 and Figure 4-5, for the situation where the number of agricultural machinery operation rows in the early planting stage and the later management stage are inconsistent, it is also necessary to calculate the original trajectory information into multiple parallel trajectory information according to the above-mentioned coordinate point calculation method. Let the number of intelligent agricultural machinery operation rows in the early planting stage be a, the number of intelligent agricultural machinery operation rows in the later management stage be b, and the distance between crop rows be d. It is necessary to use the original operation trajectory information as the center and calculate a certain number of parallel trajectories to the left and right sides respectively. The number and interval distance depend on the number of operation rows of agricultural machinery in the two stages. When a / b is an odd number, the original trajectory is retained as one of the rows of the new trajectory, and a number of parallel trajectories of n=(a / b-1) / 2 are calculated to the left and right sides respectively. The distance between adjacent parallel trajectories is P=b*d. Specifically, when the rice transplanter in the planting stage is a six-row rice transplanter, that is, a=6, and the number of operation rows of the weeder in the management stage is 2, that is, b=2, then a / b=3, which is an odd number, such as Figure 4 As shown, the six short black lines are the working rows of the rice transplanter, and the one long black line is the working path of the rice transplanter. Then, the path of the weeder when operating should be three dotted lines. At this time, the dotted path required by the weeder needs to be inferred through the long black line working path of the rice transplanter. Since the middle path of the three dotted paths of the weeder coincides with the long black line path of the rice transplanter, the original path of the rice transplanter can be used directly for this dotted path, while the left and right dotted paths need to be inferred. At this time, the number of paths required to be calculated on both sides is n=(6 / 3)-1=1, and the distance P=b*d=2d. The heading information of the rice transplanter's working path is known, and the headings on the left and right sides of the path are respectively in a relationship of plus or minus 90 degrees with the heading of the rice transplanter path. According to the rice transplanter's working path information, the working paths suitable for the weeder on both sides can be inferred through the distance P and the heading angle.

[0048] When a / b is an even number, the original trajectory is not retained, and it is used as the basis for calculation to both sides. The number of parallel trajectories on both sides is The distance between the original track and its two adjacent parallel tracks is P1 = b*d / 2, and the distance between the remaining parallel tracks is P2 = b*d. Taking the original track as the reference, the calculation can be completed based on the above numbers and distances. Specifically, if the rice transplanter in the planting stage is a six-row rice transplanter, that is, a = 6, and if the number of operating rows of the weeder in the management stage is 1, that is, b = 1, then a / b = 6, which is an even number, such as Figure 5As shown in the figure; 6 short black solid lines are the working rows of the rice transplanter, and 1 long black solid line is the working path recorded by the rice transplanter. Then, the path of the weeder when operating should be six dotted lines. At this time, the dotted path required by the weeder needs to be inferred through the long black solid line working path of the rice transplanter. The number of paths required to be calculated on both sides is n = (6 / 1) / 2 = 3, and the distance between the rice transplanter working path and its two adjacent weeder paths is P1 = 1*d / 2 = 0.5d. The distance between the remaining parallel paths is P2 = 1*d = d. Similarly, when the distances P1, P2 and heading information are known, the working paths suitable for the weeder on both sides can be inferred based on the working path information of the rice transplanter.

[0049] After the calculation is complete, the reconstructed trajectory information is converted from plane coordinates to geodetic coordinates in latitude and longitude format for the intelligent agricultural machinery to complete navigation operations. Furthermore, since the operation trajectory information recorded in the early stages is a series of dense positioning coordinate points, the intelligent agricultural machinery in the later stages does not need all coordinate information. Therefore, it is necessary to select feature points from the trajectory information. The feature points that can represent the operation trajectory curve are selected and used as the operation target path. This can reduce the amount of data processing required by the intelligent agricultural machinery during navigation and eliminate unnecessary heading adjustments during navigation.

[0050] See also Figure 2 Since the intelligent agricultural machinery travels between the crop rows, the standard for selecting feature points should ensure that the agricultural machinery does not touch or damage the crops as much as possible during the operation. If the distance between the two feature points is too far, when the crop row has a bend, the agricultural machinery may run over the crops and drive towards the feature point. In order to avoid damaging the crops, the curvature of the crop row under the extreme working conditions is taken. When the planting agricultural machinery travels with the minimum turning radius, the distance between its outermost planting point and the steering center is taken as R, and the distance between the two adjacent planting points of the agricultural machinery is taken as L. This is the maximum bending angle of the crop row planted by the intelligent agricultural machinery. At this bending angle, the agricultural machinery's travel wheels start to move towards the next feature point at the midpoint of the two crop rows. If it does not touch the crops, its maximum driving angle appears when the driving direction is tangent to the outermost crop row, that is, the maximum straight-line distance between the feature points can be taken as By selecting and rearranging the feature points of the operation trajectory information at intervals of this distance, an operation path suitable for intelligent agricultural machinery in the management and harvesting stages can be generated.

[0051] See also Figure 3 The green thick curve represents two adjacent crop strips, the dotted line represents the operation path of the planting agricultural machinery, and the feature points are taken from the operation path. The blue thin solid line is the driving line of the management agricultural machinery, that is, the maximum distance between the two feature points can be D. At this time, the driving line of the management agricultural machinery will be tangent to the crop strip. If the feature points are farther away, the driving line of the management agricultural machinery will be compared with the crop strip, which will cause crop damage.

[0052] In step five, the intelligent agricultural machinery in the management and harvesting phase completes the re-tracking operation based on the adapted operation trajectory information. The embedded board sequentially uses the coordinates of the feature points arranged in the adapted operation trajectory information as the target coordinate points of the intelligent agricultural machinery. When the intelligent agricultural machinery reaches a target point, it uses the next feature point as the new target point until the re-tracking operation is completed. While the intelligent agricultural machinery in the management and harvesting phase is re-tracking, the RTK module on the machine receives its real-time operation trajectory information. This information is also transmitted to the visualization terminal via the embedded board and stored in the cloud server via the 4G module in the form of geodetic coordinates in the form of longitude and latitude.

[0053] Step six: After the intelligent agricultural machinery completes the same-track operation, the operation trajectories of the early stage of crop planting and the later stage of management and harvesting can be compared, and data such as the overlap of the operation trajectories and the trajectory deviation can be analyzed. Based on the data, the operation speed of the intelligent agricultural machinery, the selection of operation trajectory feature points and other aspects can be optimized to further improve the degree of refinement of crop planting management using the same-track operation method.

[0054] The above is a preferred embodiment of the present invention, but the embodiment of the present invention is not limited to the above content. Any other changes, modifications, substitutions, combinations, and simplifications made without departing from the spirit and principles of the present invention should be considered as equivalent replacement methods and are included in the scope of protection of the present invention.

Claims

1. A method for simultaneously planting and managing crops with intelligent agricultural machinery, characterized in that: The following steps are involved: Step 1: Building a system for planting, managing and tracking plants in the same track. The system includes a terminal unit and a backend server. The terminal unit is connected to the backend server via a network and includes a navigation and positioning module, a display module, a data transmission module and a processor module. Step 2: Install the terminal unit of the planting, management and tracking system on the intelligent agricultural machine; perform planting through the intelligent agricultural machine, record the trajectory information of the planting operation, and upload it to the backend server; Step 3: When the crops are planted and enter the later stage of field management or harvesting, the intelligent agricultural machinery performing field management or harvesting is equipped with the terminal unit of the planting, management and tracking system. Before entering the designated field for operation, the intelligent agricultural machinery connects to the backend server and downloads the operation trajectory information of the designated field in the planting stage stored in the backend server; Step 4: If the operation trajectory of the intelligent agricultural machinery in the planting stage is inconsistent with the operation trajectory of the intelligent agricultural machinery in the later field management or harvesting stage, the intelligent agricultural machinery in the later field management or harvesting stage needs to adjust the operation trajectory information to obtain the operation trajectory information that is compatible with the intelligent agricultural machinery in the later field management or harvesting stage; Let the number of rows operated by the intelligent agricultural machinery in the early planting phase be a, the number of rows operated by the intelligent agricultural machinery in the later field management or harvesting phase be b, and the distance between crop rows be d. With the original operation trajectory information as the center, parallel trajectories are calculated to the left and right sides respectively. The number and spacing of these parallel trajectories depend on the number of rows operated by the agricultural machinery in the two phases: When a / b is an odd number, the original trajectory is retained as one of the rows of the new trajectory, and n = (a / b-1) / 2 parallel trajectories are calculated to the left and right sides respectively, and the distance between adjacent parallel trajectories is P = b*d; When a / b is an even number, the original trajectory is not retained, and it is used as the basis for calculation to both sides. The number of parallel trajectories on both sides is The distance between the original track and its two adjacent parallel tracks is P1 = b*d / 2, and the distance between the remaining parallel tracks is P2 = b*d. Based on the original track as a reference, the above numbers and distances can be used to complete the calculation. After the calculation is completed, the reconstructed trajectory information is converted from plane coordinates to geodetic coordinates in latitude and longitude format for the intelligent agricultural machinery to complete the navigation operation; Step 5: In the later management or harvesting stages, the intelligent agricultural machinery completes the same operation based on the adapted operation trajectory information obtained through adjustment.

2. The intelligent agricultural machinery planting and management method according to claim 1 is characterized in that: In step one, the positioning module is an RTK module of the Beidou navigation satellite system, which is connected to the processor module via a data cable; the RTK module sends the received positioning information to the processor module. After receiving the positioning information from the two RTK modules, the processor module calculates the real-time positioning coordinates of the center point of the intelligent agricultural machinery, the azimuth of the fuselage direction, and the driving speed, and at the same time sets the target coordinate point for the intelligent agricultural machinery, and navigates the intelligent agricultural machinery to the target point based on the distance and heading between the current position of the machine and the target point.

3. The intelligent agricultural machinery planting and management method according to claim 2 is characterized in that: Two RTK modules are mounted on the frame of the intelligent agricultural machinery at the left and right ends in a manner symmetrical to the central axis of the fuselage. The connection line between the two RTK modules is perpendicular to the forward direction of the intelligent agricultural machinery. The RTK module establishes a real-time data connection with the Beidou navigation satellite and multiple base stations to receive positioning information.

4. The intelligent agricultural machinery planting and management method according to claim 1 is characterized in that: In step one, the processor module is connected to the display module, and the positioning data processing results, machine operation status, and field operation completion rate are displayed through the display module; after the intelligent agricultural machinery completes the operation of the designated field, the positioning information of the entire operation process of the intelligent agricultural machinery is recorded and a set of field operation trajectory information is temporarily stored in the display module in the form of a series of coordinate points.

5. The intelligent agricultural machinery planting and management method according to claim 1 is characterized in that: In step 1, the display module is connected to the data transmission module, and is connected to the background server through the data transmission module to upload the operation track information to the background server or download the operation track information from the background server.

6. The intelligent agricultural machinery planting and management method according to claim 1 is characterized in that: In step 2, before planting, a straight line is marked at points A and B at both ends of the field, and the field path is planned based on this line; the path planning is performed by the processor module; During the planting operation, the real-time positioning information of the intelligent agricultural machinery passing by is transmitted to the processor module through the positioning module, and the processor module processes the positioning information and controls the intelligent agricultural machinery to perform navigation operations; the processed positioning information is transmitted and temporarily stored in the form of a set of geodetic coordinates. After the intelligent agricultural machinery completes the operation of any field, the field will be marked with a designated number and its corresponding operation trajectory information will be connected to the background server through the data transmission module, and the operation trajectory information in the geodetic coordinate format will be uploaded to the background server for storage, so that other intelligent agricultural machinery can download the operation trajectory information.

7. The intelligent agricultural machinery planting and management method according to claim 1 is characterized in that: In step 4, the method for adjusting the operation trajectory information is as follows: Convert the operation trajectory information from geodetic coordinates to the plane coordinates of the earth projection, and then use all the positioning coordinate points in the original trajectory information as the reference to calculate the new operation path coordinates in the plane coordinate system according to the azimuth and distance; Assume that the coordinates of the original trajectory point A are (Xa, Ya), and the coordinates of the coordinate point B to be determined are (Xb, Yb). The straight-line distance between point B and point A is L, and the azimuth of point B relative to point A is M, with the true north direction as 0 degrees. The coordinates of B can be obtained by the following formula: Xb=Xa+(L*cos(M)); Yb=Ya+(L*sin(M)).

8. The intelligent agricultural machinery planting and management method according to claim 1 is characterized in that: The operation trajectory information recorded during the early planting phase is a series of dense positioning coordinate points. Feature points need to be selected from the original trajectory information. The standard for selecting feature points is to ensure that the intelligent agricultural machinery does not touch or damage the crops during operation. The method is as follows: When the crop row has a bend, the curvature of the crop row under the extreme working condition is taken, and the intelligent agricultural machine is made to travel at the minimum turning radius. The distance between its outermost planting point and the steering center is taken as R, and the distance between two adjacent planting points of the agricultural machine is taken as L. This is the maximum bend angle of the crop row planted by the intelligent agricultural machine. At this bend angle, the intelligent agricultural machine's travel wheels start to move toward the next feature point at the midpoint between the two crop rows. If the crop is not touched, the maximum driving angle occurs when the driving direction is tangent to the outermost crop row, that is, the maximum straight-line distance between feature points can be taken as By selecting and rearranging the feature points of the operation trajectory information at intervals of this distance, an operation path that is compatible with intelligent agricultural machinery for subsequent field management or harvesting can be generated.

9. The intelligent agricultural machinery planting and management method according to any one of claims 1 to 8, characterized in that: In step 5, during the same-track operation, the processor module sequentially arranges the coordinates of the feature points arranged in the adapted operation trajectory information as the target coordinate points of the intelligent agricultural machinery. When the intelligent agricultural machinery reaches a target point, the next feature point is used as the new target point until the same-track operation of the field is completed. During the same-track operation, the real-time trajectory information of the operation is received through the positioning module, and the geodetic coordinates in the form of longitude and latitude are stored in the background server through the data transmission module.

Images