Intelligent agricultural machinery remote control system

Abstract

The present invention discloses an intelligent agricultural machinery remote control system, including a data input unit, a flight planning unit, a data processing unit, a data display unit, and a data control unit, and the present invention relates to the field of intelligent agricultural machinery technology. The intelligent agricultural machinery remote control system, the present invention ensures that pesticides or fertilizers can cover the entire target farmland more evenly and accurately by intelligently planning the flight route and spraying strategy of the plant protection UAV. It improves the efficiency of crop protection and nutrient supply, and reduces the waste of resources caused by excessive or insufficient spraying; it realizes the automation and remote control of agricultural spraying operations, greatly reducing the physical labor of farmers or operators. By accurately calculating the flight route and rotation angle, and setting the spraying positioning node, the system ensures that the plant protection UAV can fly stably and spray accurately in a complex farmland environment, reducing the risk of safety accidents that may occur during the operation.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent agricultural machinery, and in particular to a remote control system for intelligent agricultural machinery. Background Art

[0002] In modern agricultural production, the concepts of precision agriculture and smart agriculture are gaining more and more attention. With the advancement of technology, unmanned aerial vehicles (UAVs) are increasingly used in agriculture, especially in plant protection operations. UAVs have become an important tool for spraying pesticides and fertilizers with their high efficiency and flexibility. Traditional plant protection operations often rely on manual labor or ground machinery, which is not only inefficient, but also may affect the health of operators due to long-term exposure to pesticides.

[0003] However, despite the many advantages of drones in plant protection, how to accurately plan their flight routes and spraying patterns to improve coverage and reduce pesticide waste remains a problem. In addition, for farmlands of different shapes and sizes, how to adjust the flight plan of drones to suit specific operational needs is also a challenge. Therefore, developing a system that can remotely control and intelligently plan the flight routes and spraying strategies of plant protection drones is of great significance for improving agricultural production efficiency, reducing labor intensity, reducing the use of pesticides, and protecting the environment.

[0004] In view of the problems and challenges of existing plant protection UAVs in farmland spraying operations, an intelligent and automated remote control solution is proposed, aiming to improve operation efficiency, accuracy and safety while reducing labor costs and environmental risks. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides an intelligent agricultural machinery remote control system, which automatically plans the optimal flight route and spraying scheme for farmland of specific shapes based on the input farmland information and the spraying parameters of the plant protection drone. Through comprehensive analysis of the shape and size of the farmland and the spraying capacity of the drone, the system can calculate the most effective spraying path and the number of spraying passes required to ensure uniform coverage of the pesticide and minimize overlapping spraying; in addition, the system can also calculate the key parameters of the plant protection drone, such as the travel speed and filling times, to provide detailed operation guidance for operators.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent agricultural machinery remote control system, comprising:

[0007] A data input unit is used to input the farmland information of the target farmland and the spraying information of the plant protection drone; wherein the farmland information includes the side length value of the target farmland, the side length values ​​corresponding to the two relatively parallel opposite sides are recorded as the two farmland lengths, and the other two opposite sides are recorded as the farmland width; the spraying information includes the pesticide filling capacity of the plant protection drone, the spraying radius, the required spraying amount of the target farmland, and the maximum spraying rate;

[0008] The flight planning unit is used to plan the route of the plant protection UAV based on the farmland information and derive the flight route and total travel distance of the plant protection UAV;

[0009] A data processing unit is used to perform operations based on the spraying information and the processing results of the flight planning unit, and obtain the driving planning parameters of the plant protection UAV, wherein the driving planning parameters include the number of fillings, the total spraying time, the travel speed, the travel distance of a single tank, and the first rotation angle and the second rotation angle corresponding to the two sides of the target farmland when the plant protection UAV performs spraying operations according to the S-shaped route;

[0010] A data display unit is used to display the driving planning parameters to the operator;

[0011] The data control unit is used by operators to control the plant protection UAV according to the driving planning parameters.

[0012] Preferably, the farmland is in a rectangular shape, and two opposite sides of the farmland are relatively parallel, and the two relatively parallel opposite sides are convenient for mechanical tillage of crops in the farmland, and the plant protection UAV performs spraying operations in an S-shaped route along the length of the farmland.

[0013] Preferably, the pesticide filling capacity refers to the maximum load weight of the pesticide mixed water that the plant protection UAV loads each time; the spraying radius refers to the coverage range when the plant protection UAV sprays the pesticide mixed water at a specified height; the required spraying amount refers to the weight of the pesticide mixed water that needs to be sprayed on the target farmland; the maximum spraying rate refers to the maximum spraying amount of the plant protection UAV in unit time.

[0014] Preferably, the line planning method is as follows:

[0015] SF1. Calculate the difference between the lengths of two fields in the target field by subtracting the length of the shortest field from the length of the longest field, and mark it as the length difference;

[0016] SF2, construct a triangle based on the length difference and the width of the two fields;

[0017] Then draw a perpendicular line from the point where the widths of the two farmlands intersect in the triangle to the side corresponding to the length difference in the triangle;

[0018] Then the vertical line length is calculated by Heron's formula and area formula, wherein the vertical line length is the height of the triangle with the side corresponding to the length difference in the triangle as the base, and the height is the shortest distance between the two farmland lengths;

[0019] SF3, by using the spraying number = vertical line length / (2 * spraying radius), calculate the number of round trips required for the plant protection drone to spray the pesticide mixed with water in the target farmland, that is, the number of spraying trips;

[0020] SF4. Draw a corresponding number of perpendicular lines with equal spacing on the perpendicular line in the triangle according to the number of spraying passes, and divide it into several triangles;

[0021] At the same time, according to the vertical line division length = vertical line length value / spraying number of times, width division length = farmland width / spraying number of times, the vertical line length value and the vertical line division length of two farmland widths and two width division lengths are calculated respectively;

[0022] And several divided triangles are respectively established based on the multiples of the corresponding two width division lengths as the side lengths, and the multiples of the vertical line division lengths are respectively the height values ​​of the other unknown side lengths of the corresponding several divided triangles;

[0023] SF5, according to the ratio of the vertical line length value to the length difference obtained in step SF1, and then through the height value of the other unknown side length in each triangle and the ratio, calculate the value of the other unknown side length in each triangle;

[0024] SF6, then calculate the angle of a triangle using the cosine theorem formula, and then use the perpendicular line to divide the triangle into two right triangles;

[0025] Then, the angle value of the other angle in the two right triangles is calculated by the angle value of the triangle, and this angle value is recorded as the analysis angle; the side corresponding to the analysis angle is the side length corresponding to the length difference of the triangle;

[0026] SF7. At the same time, according to the vertical line, each triangle is divided into two split sides corresponding to another unknown side length, that is, the other side of the two right triangles except the vertical line length and the width of the farmland;

[0027] Then, according to the length of the perpendicular line of the right triangle, the width of the farmland and the analysis angle, two segmentation edge values ​​are calculated through trigonometric functions and bundled into a group of segmentation edge value data packets;

[0028] And so on, multiple segmentation edge value data packets are calculated in sequence;

[0029] SF8. Establish a rectangle based on the shortest length of the target farmland and the vertical length, and then set a corresponding number of flight preset paths in the rectangle according to the direction of the farmland length based on the number of spraying passes;

[0030] Then, according to the direction from the shortest farmland length to the longest farmland length, in the order of the split edge values ​​analyzed on the same side of the target farmland in each split edge value data packet from small to large, two split edge values ​​are added to the two ends of each flight preset path in sequence, and the result is recorded as the flight number path;

[0031] Then the flight paths are connected end to end in an S-shaped direction to obtain the flight route;

[0032] SF9. At the same time, by multiplying the number of spraying trips by the length of the smallest farmland in the target farmland and adding all the unknown side length values ​​obtained in SF5, the distance that the plant protection drone needs to travel when spraying the pesticide mixed with water in the target farmland is calculated, that is, the total travel distance.

[0033] Preferably, the specific calculation method of step SF2 is as follows:

[0034] First, mark the length difference of the triangle and the lengths of the two sides corresponding to the width of the farmland as a, b, and c respectively;

[0035] Then through , calculate the semi-perimeter p of the triangle;

[0036] Then, through Heron's formula , calculate the area S of the triangle;

[0037] Then the area formula Reverse the process, that is, through Calculate the length of the vertical line h a .

[0038] Preferably, in step SF3, when the value calculated by the above formula is not an integer, the value is rounded up and the integer result is used as the number of spraying passes;

[0039] The number of round trips is counted as follows: the distance to one farmland length is counted as 1 time, and the distance back to one farmland length is counted as 1 time.

[0040] Preferably, in step SF4, the plurality of triangles are similar triangles.

[0041] Preferably, the specific operation process is as follows:

[0042] S1. Calculate the number of times the target farmland needs to be filled with pesticide mixed water by the plant protection drone through filling times = required spraying amount / pesticide filling capacity, that is, filling times;

[0043] S2, total spraying time = required spraying amount / maximum spraying rate, calculate the time required to spray the target farmland with the mixed water when the spraying rate is fixed, that is, the total spraying time;

[0044] S3. Calculate the speed required for the plant protection drone to spray the pesticide mixed with water in the target farmland by using the formula: travel speed = total travel distance / total spraying time, i.e., travel speed;

[0045] S4. Calculate the distance that the plant protection drone can travel with a load of pesticide mixed water, i.e., the single tank travel distance, by using the formula single tank travel distance = travel speed * (pharmaceutical filling capacity / spraying rate);

[0046] S5. Perform a U-turn analysis on the S-shaped route during the spraying operation, and based on the analysis results, calculate the corresponding first rotation angle and second rotation angle when the plant protection UAV performs spraying operations according to the S-shaped route and flies to both sides of the target farmland; among which, the first rotation angle is used for the plant protection UAV to fly to the next adjacent spraying pass, and the second rotation angle is used for the plant protection UAV to spray the next adjacent spraying pass.

[0047] Preferably, the method of step S5 is as follows:

[0048] Then, the first turning angle of the UAV during the S-shaped route spraying operation is calculated by the first turning angle = 90°-analysis angle, that is, the first turning angle;

[0049] Then, the second U-turn angle, that is, the second rotation angle, is calculated when the UAV performs S-shaped route spraying operations through the second rotation angle = 360° - the first rotation angle or the second rotation angle = 180° + the analysis angle.

[0050] Preferably, it also includes:

[0051] The positioning analysis unit is used to set a number of nodes with a single tank travel distance as the interval distance in the S-shaped route of the spraying operation, and use the node as the spraying positioning node; the spraying positioning node is used for the plant protection UAV to add pesticide mixed water, and is also used for the plant protection UAV after adding pesticide mixed water to continue spraying operations at the corresponding position of the target farmland.

[0052] The present invention provides an intelligent agricultural machinery remote control system. Compared with the prior art, it has the following beneficial effects:

[0053] Improve spraying efficiency and accuracy: This invention ensures that pesticides or fertilizers can cover the entire target farmland more evenly and accurately by intelligently planning the flight route and spraying strategy of the plant protection drone. This not only improves the efficiency of crop protection and nutrient supply, but also reduces the waste of resources caused by excessive or insufficient spraying.

[0054] Reducing manual labor intensity: The present invention realizes the automation and remote control of agricultural spraying operations, greatly reducing the physical labor of farmers or operators, while also avoiding their health risks of direct contact with pesticides.

[0055] Data-driven decision support: The data display unit and data processing unit provided by the present invention can provide operators with detailed spraying information and drone status, helping them make more reasonable operation decisions, such as adjusting the travel speed, filling times, etc.

[0056] Improve operation safety: By accurately calculating the flight route and rotation angle, and setting the spraying positioning nodes, the system ensures that the plant protection UAV can fly stably and spray accurately in complex farmland environments, reducing the risk of safety accidents that may occur during the operation.

[0057] Environmentally friendly: Precise control of spraying volume helps reduce the pollution of pesticides and fertilizers to the environment, which is in line with the concept of sustainable agricultural development.

[0058] Strong adaptability: The design of the present invention takes into account farmlands of different shapes and sizes, so that it can be widely used in a variety of agricultural scenarios, enhancing its practicality and market competitiveness.

[0059] Promoting agricultural modernization: The implementation of this invention will help promote the transformation from traditional agriculture to smart agriculture and improve the scientific and technological content and modernization level of agricultural production.

[0060] In general, the present invention provides an efficient, precise, safe and environmentally friendly agricultural spraying solution, which is of great significance for improving agricultural productivity and achieving sustainable agricultural development. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Embodiment 1

[0063] See also Figure 1 , the present invention provides a technical solution: an intelligent agricultural machinery remote control system, which is used for remote control of a plant protection drone that applies fertilizer in a target area;

[0064] A data input unit, used to input the farmland information of the target farmland and the spraying information of the plant protection drone;

[0065] In this embodiment, the farmland is in a rectangular shape, and two opposite sides of the farmland are relatively parallel, and the two relatively parallel opposite sides are convenient for mechanical cultivation of crops planted in the farmland;

[0066] Among them, farmland information includes the side length of the target farmland. The side lengths of the two relatively parallel opposite sides are recorded as the lengths of the two farmlands, and the other two opposite sides are recorded as the width of the farmland. Spraying information includes the pesticide filling capacity of the plant protection drone, the spraying radius, the required spraying amount of the target farmland, and the maximum spraying rate.

[0067] In this embodiment, the target farmland is rectangular in shape, and the plant protection drone performs an S-shaped route spraying operation along the length of the farmland;

[0068] The filling capacity of the pesticide refers to the maximum loading weight of the pesticide mixed water loaded by the plant protection drone each time;

[0069] The spraying radius refers to the coverage area when the crop protection drone sprays the pesticide mixed with water at a specified height;

[0070] The amount to be sprayed refers to the weight of the pesticide mixed with water that needs to be sprayed on the target farmland;

[0071] The maximum spraying rate refers to the maximum spraying volume of the plant protection drone per unit time;

[0072] The flight planning unit is used to plan the route of the plant protection UAV based on the farmland information;

[0073] The specific method is as follows:

[0074] SF1. Calculate the difference between the lengths of two fields in the target field by subtracting the length of the shortest field from the length of the longest field, and mark it as the length difference;

[0075] SF2, construct a triangle based on the length difference and the width of the two fields;

[0076] Then draw a perpendicular line from the point where the widths of the two farmlands intersect in the triangle to the side corresponding to the length difference in the triangle;

[0077] Then the vertical line length is calculated by Heron's formula and area formula, wherein the vertical line length is the height of the triangle with the side corresponding to the length difference in the triangle as the base, and the height is the shortest distance between the two farmland lengths;

[0078] The specific calculation method is as follows:

[0079] First, mark the length difference of the triangle and the lengths of the two sides corresponding to the width of the farmland as a, b, and c respectively;

[0080] Then through , calculate the semi-perimeter p of the triangle;

[0081] Then, through Heron's formula , calculate the area S of the triangle;

[0082] Then the area formula Reverse the process, that is, through Calculate the length of the vertical line h a ;

[0083] SF3, by using the spraying number = vertical line length / (2 * spraying radius), calculate the number of round trips required for the plant protection drone to spray the pesticide mixed with water in the target farmland, that is, the number of spraying trips;

[0084] In this embodiment, when the value calculated by the above formula is not an integer, the value is rounded up and the integer result is used as the number of spraying passes;

[0085] The round trip times are counted as follows: the route to a farm length is counted as 1 time, and the route back to a farm length is counted as 1 time;

[0086] SF4. Draw a corresponding number of perpendicular lines with equal spacing on the perpendicular line in the triangle according to the number of spraying passes, and divide it into several triangles;

[0087] Wherein, the plurality of triangles are similar triangles;

[0088] At the same time, according to the vertical line division length = vertical line length value / spraying number of times, width division length = farmland width / spraying number of times, the vertical line length value and the vertical line division length of two farmland widths and two width division lengths are calculated respectively;

[0089] And several divided triangles are respectively established based on the multiples of the corresponding two width division lengths as the side lengths, and the multiples of the vertical line division lengths are respectively the height values ​​of the other unknown side lengths of the corresponding several divided triangles;

[0090] SF5, according to the ratio of the vertical line length value to the length difference obtained in step SF1, and then through the height value of the other unknown side length in each triangle and the ratio, calculate the value of the other unknown side length in each triangle;

[0091] SF6, then calculate the angle of a triangle using the cosine theorem formula, and then use the perpendicular line to divide the triangle into two right triangles;

[0092] Then, the angle value of the other angle in the two right triangles is calculated by the angle value of the triangle, and this angle value is recorded as the analysis angle; the side corresponding to the analysis angle is the side length corresponding to the length difference of the triangle;

[0093] SF7. At the same time, according to the vertical line, each triangle is divided into two split sides corresponding to another unknown side length, that is, the other side of the two right triangles except the vertical line length and the width of the farmland;

[0094] Then, according to the length of the perpendicular line of the right triangle, the width of the farmland and the analysis angle, two segmentation edge values ​​are calculated through trigonometric functions and bundled into a group of segmentation edge value data packets;

[0095] And so on, multiple segmentation edge value data packets are calculated in sequence;

[0096] SF8. Establish a rectangle based on the shortest length of the target farmland and the vertical length, and then set a corresponding number of flight preset paths in the rectangle according to the direction of the farmland length based on the number of spraying passes;

[0097] Then, according to the direction from the shortest farmland length to the longest farmland length, in the order of the split edge values ​​analyzed on the same side of the target farmland in each split edge value data packet from small to large, two split edge values ​​are added to the two ends of each flight preset path in sequence, and the result is recorded as the flight number path;

[0098] Then the flight paths are connected end to end in an S-shaped direction to obtain the flight route;

[0099] SF9, at the same time, by multiplying the number of spraying trips by the length of the smallest farmland in the target farmland, and adding all the unknown side length values ​​obtained in SF5, calculate the distance that the plant protection drone needs to travel when spraying the pesticide mixed water in the target farmland, that is, the total travel distance;

[0100] This embodiment ensures that the pesticide can evenly cover the entire target farmland by accurately calculating the number of spraying passes and flight routes, reducing the possibility of missed spraying or repeated spraying; by calculating the optimal flight route and spraying strategy, it reduces the waste of pesticides, while improving the operating efficiency of the drone, saving energy and time; the data display and processing unit provided by the system can provide operators with detailed spraying information and drone status, helping them make more reasonable operating decisions. Embodiment 2

[0101] As the second embodiment of the present invention, when the present application is implemented, compared with the first embodiment, the technical solution of the present embodiment is different from that of the first embodiment only in that the present embodiment further includes:

[0102] A data processing unit is used to perform operations based on the spraying information and the processing results of the flight planning unit, and obtain the driving planning parameters of the plant protection UAV, wherein the driving planning parameters include the number of fillings, the total spraying time, the travel speed, the travel distance of a single tank, and the first rotation angle and the second rotation angle corresponding to the two sides of the target farmland when the plant protection UAV performs spraying operations according to the S-shaped route;

[0103] S2, total spraying time = required spraying amount / maximum spraying rate, calculate the time required to spray the target farmland with the mixed water when the spraying rate is fixed, that is, the total spraying time;

[0104] S3. Calculate the speed required for the plant protection drone to spray the pesticide mixed with water in the target farmland by using the formula: travel speed = total travel distance / total spraying time, i.e., travel speed;

[0105] S4. Calculate the distance that the plant protection drone can travel with a load of pesticide mixed water, i.e., the single tank travel distance, by using the formula single tank travel distance = travel speed * (pharmaceutical filling capacity / spraying rate);

[0106] S5. Perform a U-turn analysis on the S-shaped route during the spraying operation, and based on the analysis results, calculate the first turning angle and the second turning angle corresponding to the two sides of the target farmland when the plant protection UAV performs the spraying operation according to the S-shaped route;

[0107] The specific method is as follows:

[0108] Take the case where the plant protection drone flies to one side of the target farmland and needs to turn around:

[0109] Then, the first turning angle of the UAV during the S-shaped route spraying operation is calculated by the first turning angle = 90°-analysis angle, that is, the first turning angle;

[0110] Then, the second U-turn angle, i.e., the second turning angle, is calculated by the second turning angle = 360° - the first turning angle or the second turning angle = 180° + the analysis angle when the UAV performs the S-shaped route spraying operation;

[0111] The first turning angle is used for the plant protection drone to fly to the next spraying pass, and the second turning angle is used for the plant protection drone to spray the next spraying pass;

[0112] A data display unit is used to display the driving planning parameters to the operator;

[0113] The data control unit is used by operators to control the plant protection UAV according to the driving planning parameters.

[0114] By accurately calculating the flight route and rotation angle, and setting the spraying positioning node, the system of this embodiment ensures the stable flight of the plant protection UAV in the complex farmland environment, reducing the safety accidents that may occur during the operation; accurately controlling the spraying amount helps to reduce the pollution of pesticides to the environment, which is in line with the concept of sustainable agricultural development; by reducing resource waste, improving operation efficiency and reducing labor costs, the system may reduce the overall agricultural production cost and improve economic benefits; the user interface design of the data display unit and the data control unit may be simple and intuitive, which is convenient for operators to quickly master and operate; Embodiment 3

[0115] As the third embodiment of the present invention, when the present application is implemented, compared with the first and second embodiments, the technical solution of this embodiment is to combine the solutions of the first and second embodiments, and the difference between the technical solution of this embodiment and the first and second embodiments is that this embodiment also includes:

[0116] The positioning analysis unit is used to set a number of nodes in the flight route with the travel distance of a single tank as the interval distance, and use the node as the spraying positioning node; the spraying positioning node is used for the plant protection UAV to add pesticide mixed water, and at the same time, it is used for the plant protection UAV after adding pesticide mixed water to continue spraying operations at the corresponding position of the target farmland.

[0117] By calculating the travel distance of a single tank to set nodes, it helps to accurately estimate the amount of medicine required for each spraying task, thereby reducing the waste of medicine and the number of loading times, saving resources and costs; by setting spraying positioning nodes in the flight route, the plant protection drone can add medicine mixed water at these preset points, thus ensuring that the drone can continue to spray without returning to the starting point or going to a distant supply point. This can greatly save round-trip time and improve work efficiency.

[0118] By reasonably setting the spraying positioning nodes, the UAV can replenish the pesticide in time before it is exhausted, ensuring the continuity and stability of the pesticide supply during the spraying process, thereby ensuring a more uniform coverage of the pesticide on the crops in the farmland; when operating in complex terrain or large areas of farmland, the setting of spraying positioning nodes enables the UAV to flexibly adjust the operation route and spraying plan according to the actual terrain and spraying needs, thereby improving the adaptability and efficiency of the operation. Embodiment 4

[0119] As the fourth embodiment of the present invention, when the present application is implemented, compared with the first, second and third embodiments, the difference between this embodiment and the first, second and third embodiments is that in this embodiment, the data processing unit is also used to calculate the number of times the target farmland needs to be filled with pesticide mixed water by the plant protection drone through the number of fillings = required spraying amount / pesticide filling capacity, that is, the number of fillings, and then display the results to the operating personnel through the data display unit.

[0120] The data processing unit can accurately calculate the number of times the pesticide is filled to complete the entire farmland spraying task based on the amount of spraying required on the farmland and the pesticide filling capacity of the drone. This helps operators better arrange the spraying plan and ensure a balance between pesticide supply and demand.

[0121] Optimize resource management: By accurately calculating the number of filling times, over-preparation or under-preparation of pesticides can be avoided, thereby reducing resource waste and potential pesticide shortages. At the same time, this also helps to reduce ineffective drone flights and save energy consumption; knowing the required number of filling times in advance allows operators to prepare in advance and reduce the time the drone waits for pesticide filling, thereby improving overall operation efficiency; the data display unit intuitively displays the calculation results to operators, improving the comprehensibility and ease of use of information. Operators can quickly grasp the key information of the spraying operation and make corresponding operational decisions. Embodiment 5

[0122] As the fifth embodiment of the present invention, when the present application is specifically implemented, compared with the first, second, third and fourth embodiments, the technical solution of this embodiment is to combine and implement the solutions of the above-mentioned first, second, third and fourth embodiments.

[0123] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0124] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0125] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. Intelligent agricultural machinery remote control system, characterized by: include: A data input unit is used to input the farmland information of the target farmland and the spraying information of the plant protection drone; wherein the farmland information includes the side length value of the target farmland, the side length values ​​corresponding to the two relatively parallel opposite sides are recorded as the two farmland lengths, and the other two opposite sides are recorded as the farmland width; the spraying information includes the pesticide filling capacity of the plant protection drone, the spraying radius, the required spraying amount of the target farmland, and the maximum spraying rate; The flight planning unit is used to plan the route of the plant protection UAV based on the farmland information and derive the flight route and total travel distance of the plant protection UAV; A data processing unit is used to perform operations based on the spraying information and the processing results of the flight planning unit, and obtain the driving planning parameters of the plant protection UAV, wherein the driving planning parameters include the number of fillings, the total spraying time, the travel speed, the travel distance of a single tank, and the first rotation angle and the second rotation angle corresponding to the two sides of the target farmland when the plant protection UAV performs spraying operations according to the S-shaped route; A data display unit is used to display the driving planning parameters to the operator; The data control unit is used by operators to control the plant protection drone according to the driving planning parameters; The line planning method is as follows: SF1. Calculate the difference between the lengths of two fields in the target field by subtracting the length of the shortest field from the length of the longest field, and mark it as the length difference; SF2, construct a triangle based on the length difference and the width of the two fields; Then draw a perpendicular line from the point where the widths of the two farmlands intersect in the triangle to the side corresponding to the length difference in the triangle; Then the vertical line length is calculated by Heron's formula and area formula, wherein the vertical line length is the height of the triangle with the side corresponding to the length difference in the triangle as the base, and the height is the shortest distance between the two farmland lengths; SF3, by using the spraying number = vertical line length / (2 * spraying radius), calculate the number of round trips required for the plant protection drone to spray the pesticide mixed with water in the target farmland, that is, the number of spraying trips; SF4. Draw a corresponding number of perpendicular lines with equal spacing on the perpendicular line in the triangle according to the number of spraying passes, and divide it into several triangles; At the same time, according to the vertical line division length = vertical line length value / spraying number of times, width division length = farmland width / spraying number of times, the vertical line length value and the vertical line division length of two farmland widths and two width division lengths are calculated respectively; And several divided triangles are respectively established based on the multiples of the corresponding two width division lengths as the side lengths, and the multiples of the vertical line division lengths are respectively the height values ​​of the other unknown side lengths of the corresponding several divided triangles; SF5, according to the ratio of the vertical line length value to the length difference obtained in step SF1, and then through the height value of the other unknown side length in each triangle and the ratio, calculate the value of the other unknown side length in each triangle; SF6, then calculate the angle of a triangle using the cosine theorem formula, and then use the perpendicular line to divide the triangle into two right triangles; Then, the angle value of the other angle in the two right triangles is calculated by the angle value of the triangle, and this angle value is recorded as the analysis angle; the side corresponding to the analysis angle is the side length corresponding to the length difference of the triangle; SF7. At the same time, according to the vertical line, each triangle is divided into two split sides corresponding to another unknown side length, that is, the other side of the two right triangles except the vertical line length and the width of the farmland; Then, according to the length of the perpendicular line of the right triangle, the width of the farmland and the analysis angle, two segmentation edge values ​​are calculated through trigonometric functions and bundled into a group of segmentation edge value data packets; And so on, multiple segmentation edge value data packets are calculated in sequence; SF8. Establish a rectangle based on the shortest length of the target farmland and the vertical length, and then set a corresponding number of flight preset paths in the rectangle according to the direction of the farmland length based on the number of spraying passes; Then, according to the direction from the shortest farmland length to the longest farmland length, in the order of the split edge values ​​analyzed on the same side of the target farmland in each split edge value data packet from small to large, two split edge values ​​are added to the two ends of each flight preset path in sequence, and the result is recorded as the flight number path; Then the flight paths are connected end to end in an S-shaped direction to obtain the flight route; SF9. At the same time, by multiplying the number of spraying trips by the length of the smallest farmland in the target farmland and adding all the unknown side length values ​​obtained in SF5, the distance that the plant protection drone needs to travel when spraying the pesticide mixed with water in the target farmland is calculated, that is, the total travel distance.

2. The intelligent agricultural machinery remote control system according to claim 1, characterized in that: in, The farmland is rectangular in shape, and its two opposite sides are relatively parallel, which is convenient for mechanical cultivation of crops in the farmland. The plant protection UAV conducts spraying operations in an S-shaped route along the length of the farmland.

3. The intelligent agricultural machinery remote control system according to claim 1, characterized in that: The pesticide filling capacity refers to the maximum load weight of the pesticide mixed water that the plant protection drone can load each time; the spraying radius refers to the coverage range when the plant protection drone sprays the pesticide mixed water at a specified height; the required spraying amount refers to the weight of the pesticide mixed water that needs to be sprayed on the target farmland; the maximum spraying rate refers to the maximum spraying amount of the plant protection drone in unit time.

4. The intelligent agricultural machinery remote control system according to claim 1, characterized in that: The specific calculation method of step SF2 is as follows: First, mark the length difference of the triangle and the lengths of the two sides corresponding to the width of the farmland as a, b, and c respectively; Then through , calculate the semi-perimeter p of the triangle; Then, through Heron's formula , calculate the area S of the triangle; Then the area formula Reverse the process, that is, through Calculate the length of the vertical line h a .

5. The intelligent agricultural machinery remote control system according to claim 1, characterized in that: In step SF3, when the value calculated by the above formula is not an integer, the value is rounded up and the integer result is used as the number of spraying passes; The number of round trips is counted as follows: the distance to one farmland length is counted as 1 time, and the distance back to one farmland length is counted as 1 time.

6. The intelligent agricultural machinery remote control system according to claim 1, characterized in that: In step SF4 , the plurality of triangles are similar triangles.

7. The intelligent agricultural machinery remote control system according to claim 1, characterized in that: The specific operation processing methods are as follows: S1. Calculate the number of times the target farmland needs to be filled with pesticide mixed water by the plant protection drone through filling times = required spraying amount / pesticide filling capacity, that is, filling times; S2, total spraying time = required spraying amount / maximum spraying rate, calculate the time required to spray the target farmland with the mixed water when the spraying rate is fixed, that is, the total spraying time; S3. Calculate the speed required for the plant protection drone to spray the pesticide mixed with water in the target farmland by using the formula: travel speed = total travel distance / total spraying time, i.e., travel speed; S4. Calculate the distance that the plant protection drone can travel with a load of pesticide mixed water, i.e., the single tank travel distance, by using the formula single tank travel distance = travel speed * (pharmaceutical filling capacity / spraying rate); S5. Perform a U-turn analysis on the S-shaped route during the spraying operation, and based on the analysis results, calculate the corresponding first rotation angle and second rotation angle when the plant protection UAV performs spraying operations according to the S-shaped route and flies to both sides of the target farmland; among which, the first rotation angle is used for the plant protection UAV to fly to the next adjacent spraying pass, and the second rotation angle is used for the plant protection UAV to spray the next adjacent spraying pass.

8. The intelligent agricultural machinery remote control system according to claim 7, characterized in that: The method of step S5 is as follows: The first turning angle of the UAV during the S-shaped spraying operation is calculated by the first turning angle = 90°-analysis angle, that is, the first turning angle; Then, the second U-turn angle, that is, the second rotation angle, is calculated when the UAV performs S-shaped route spraying operations through the second rotation angle = 360° - the first rotation angle or the second rotation angle = 180° + the analysis angle.

9. The intelligent agricultural machinery remote control system according to claim 1, characterized in that: Also includes: The positioning analysis unit is used to set a number of nodes with a single tank travel distance as the interval distance in the S-shaped route of the spraying operation, and use the node as the spraying positioning node; the spraying positioning node is used for the plant protection UAV to add pesticide mixed water, and is also used for the plant protection UAV after adding pesticide mixed water to continue spraying operations at the corresponding position of the target farmland.

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