Litchi pollination nutrient solution screening and application method and system integrated with unmanned aerial vehicle technology

Abstract

The invention relates to the technical field of unmanned aerial vehicle control, and discloses a litchi pollination nutrient solution screening and application method and system.The method comprises the steps that the optimal preparation concentration of a litchi pollination nutrient solution is screened, the prepared litchi pollination nutrient solution is added into a pollination device, and the optimal preparation concentration of the litchi pollination nutrient solution is obtained based on farmland layout data and flower distribution information; setting a flight path and a control target of the unmanned aerial vehicle, calculating ideal parameters of the unmanned aerial vehicle at different times by using a specific function, and initializing flight parameters of the unmanned aerial vehicle and pollination parameters of a pollination device; the unmanned aerial vehicle starts pollination operation in the pollination operation area and periodically collects environmental parameters and flower state data in the pollination operation process; based on the environment parameters and the flower state data, adjusting flight parameters of the unmanned aerial vehicle and pollination parameters of the pollination device, and dynamically adjusting the magnification times of an unmanned aerial vehicle controller. According to the invention, efficient and accurate pollination operation can be realized.

Description

Technical Field

[0001] The present application relates to the field of drone control technology, and in particular to a method and system for screening and applying litchi pollination nutrient solution that integrates drone technology. Background Art

[0002] Drones are increasingly used in agriculture, especially in crop pollination. Drone pollination can effectively improve pollination efficiency, reduce labor costs, and adapt to complex terrain and large-scale farmland operations. The accuracy and efficiency of drone pollination are affected by many factors, such as flight speed, altitude, spraying device parameters, and environmental conditions. Most existing drone pollination systems use fixed parameter control, which is difficult to adapt to different farmland environments and crop requirements, resulting in low pollination accuracy.

[0003] Similar prior art includes a Chinese patent application with publication number CN108353784A, which provides a drone pollination device and method thereof, wherein the device includes a drone, a rotor is arranged above the drone, an air outlet channel is suspended below, a powder outlet channel is arranged below the air outlet channel, the air outlet of the air outlet channel is arranged above the powder outlet of the powder outlet channel, the air outlet and the powder outlet are both arranged horizontally, the powder inlet of the powder outlet channel is provided with an air suction fan, and the air inlet of the air outlet channel is arranged below the rotor. This type of drone pollination device can suck in pollen and spray it horizontally to both sides of the drone. However, the application spreads pollen into a wider space through the airflow sprayed from the air outlet, resulting in pollen waste and low pollination accuracy and low pollination efficiency. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides a litchi pollination nutrient solution screening and application method and system integrating drone technology, which realizes efficient and accurate pollination operations by dynamically adjusting the magnification of the drone controller.

[0005] The present application provides a method for screening and applying litchi pollination nutrient solution by integrating drone technology, the method comprising:

[0006] Step S1: The screening of litchi pollination nutrient solution includes ingredient selection, formula optimization and experimental verification, wherein the ingredient selection also includes first selecting basic ingredients, and then adding nano titanium dioxide to the basic ingredients based on the growth characteristics and needs of litchi to form a preliminary litchi pollination nutrient solution, and then taking the pollen out of the low-temperature environment and placing it at room temperature for awakening, wherein the awakening time is determined based on the temperature of the day, the formula optimization refers to preparing a plurality of nutrient solutions of different concentrations based on the preliminary litchi pollination nutrient solution, and the experimental verification refers to adding the pollen to nutrient solutions of different concentrations respectively, and determining through experiments that the preparation concentration corresponding to the optimal litchi fruit setting rate is used as the optimal preparation concentration of the litchi pollination nutrient solution;

[0007] Step S2: preparing litchi pollination nutrient solution based on the optimal preparation concentration of the litchi pollination nutrient solution, adding the prepared litchi pollination nutrient solution to the pollination device, setting the flight path and control target of the UAV based on the farmland layout data and the flower distribution information, calculating the ideal parameters of the UAV at different times based on the flight path and the control target using a specific function, and initializing the flight parameters of the UAV and the pollination parameters of the pollination device based on the ideal parameters;

[0008] Step S3: Based on the flight path of the drone, the drone starts the pollination operation in the pollination operation area, and during the pollination operation, the environmental parameters and the flower status data are periodically collected through a sensor system, and the collected environmental parameters and the flower status data are transmitted to a control unit;

[0009] Step S4: The control unit adjusts the flight parameters of the UAV and the pollination parameters of the pollination device based on the environmental parameters and the flower status data, and dynamically adjusts the magnification of the UAV controller based on the difference between the actual parameters of the UAV and the ideal parameters.

[0010] The present application also provides a litchi pollination nutrient solution screening and application system integrating drone technology, including a drone platform and a sensor system, wherein the drone platform includes a GPS positioning system, a multispectral camera and a pollination device, wherein the pollination device also includes a spraying system and an adjustable nozzle, wherein the sensor system includes an environmental sensor and a crop status sensor, wherein the environmental sensor is used to measure environmental parameters, wherein the environmental parameters include temperature, humidity, wind speed and wind direction, wherein the crop status sensor obtains flower status data through the multispectral camera, wherein the flower status data includes flowering period status and flower density, and wherein the system further includes:

[0011] A nutrient solution screening unit, for screening litchi pollination nutrient solution, including ingredient selection, formula optimization and test verification, wherein the ingredient selection also includes first selecting basic ingredients, and then adding nano titanium dioxide to the basic ingredients based on the growth characteristics and needs of litchi to form a preliminary litchi pollination nutrient solution, and then taking the pollen out of the low-temperature environment and placing it at room temperature for awakening, wherein the awakening time is determined based on the temperature of the day, the formula optimization refers to preparing a plurality of nutrient solutions of different concentrations based on the preliminary litchi pollination nutrient solution, and the test verification refers to adding the pollen to nutrient solutions of different concentrations respectively, and determining through experiments that the preparation concentration corresponding to the optimal litchi fruit setting rate is used as the optimal preparation concentration of the litchi pollination nutrient solution;

[0012] an initialization unit, for preparing a litchi pollination nutrient solution based on the optimal preparation concentration of the litchi pollination nutrient solution, adding the prepared litchi pollination nutrient solution to a pollination device, setting a flight path and a control target of the drone based on farmland layout data and flower distribution information, calculating ideal parameters of the drone at different times based on the flight path and the control target using a specific function, and initializing flight parameters of the drone and pollination parameters of the pollination device based on the ideal parameters;

[0013] A collection unit, configured to start the pollination operation of the drone in the pollination operation area based on the flight path of the drone, and periodically collect the environmental parameters and the flower status data through the sensor system during the pollination operation, and transmit the collected environmental parameters and the flower status data to a control unit;

[0014] A control unit is used to adjust the flight parameters of the drone and the pollination parameters of the pollination device based on the environmental parameters and the flower status data, and dynamically adjust the magnification of the drone controller based on the difference between the actual parameters of the drone and the ideal parameters.

[0015] Compared with the prior art, the beneficial effects of the present invention are at least as follows:

[0016] In the technical solution provided by the present application, the concentration of litchi pollination nutrient solution with the best litchi fruit setting rate is screened out through the nutrient solution screening unit, and the litchi pollination nutrient solution is prepared based on the concentration, and then added to the pollination device of the drone; the initialization unit provides accurate initialization parameters for the flight and pollination tasks of the drone by accurately setting the flight path and control target of the drone and calculating the ideal parameters, thereby improving the accuracy and efficiency of task execution and ensuring that the drone is in the best state at the beginning of the pollination operation. The acquisition unit periodically collects environmental parameters and flower status data during the pollination operation, and transmits them to the control unit in real time, providing the control unit with real-time environmental and flower status information, so that the system can quickly respond to environmental changes and differences in flower status, thereby improving the success rate of pollination. Through the collected environmental parameters and flower status data, the control unit can dynamically adjust the flight parameters of the drone and the pollination parameters of the pollination device, and dynamically adjust the magnification of the drone controller according to the difference between the actual parameters and the ideal parameters, thereby improving the flight stability and pollination accuracy of the drone. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0018] Figure 1 This is a schematic diagram of an embodiment of a method for screening and applying nutrient solution for litchi pollination incorporating drone technology in an embodiment of the present application;

[0019] Figure 2 This is a schematic diagram of an embodiment of an initialization unit in an embodiment of the present application;

[0020] Figure 3 This is a schematic diagram of an embodiment of a litchi pollination nutrient solution screening and application system that integrates drone technology in an embodiment of the present application. DETAILED DESCRIPTION

[0021] The embodiments of the present application provide a method and system for screening and applying nutrient solution for litchi pollination that integrates drone technology. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0022] Embodiment 1:

[0023] The specific process of the embodiment of the present application is described below. Figure 1 In the embodiment of the present application, a method for screening and applying litchi pollination nutrient solution integrating drone technology includes:

[0024] Step S1: The screening of litchi pollination nutrient solution includes ingredient selection, formula optimization and experimental verification, wherein the ingredient selection also includes first selecting basic ingredients, and then adding nano titanium dioxide to the basic ingredients based on the growth characteristics and needs of litchi to form a preliminary litchi pollination nutrient solution, and then taking the pollen out of the low-temperature environment and placing it at room temperature for awakening, and the awakening time is determined based on the temperature of the day. Formula optimization refers to preparing a variety of nutrient solutions of different concentrations based on the preliminary litchi pollination nutrient solution, and experimental verification refers to adding pollen to nutrient solutions of different concentrations respectively, and determining through experiments that the preparation concentration corresponding to the optimal litchi fruit setting rate is the optimal preparation concentration of the litchi pollination nutrient solution.

[0025] Specifically, the basic ingredients of litchi pollination nutrient solution are selected, and the formula of fragrant pear pollination nutrient solution can be referred to, with water, xanthan gum, calcium, boron, white sugar and other ingredients. This formula can better dissolve pollen, prolong flowering period and increase pollination probability. Based on the growth characteristics and needs of litchi, nano titanium dioxide is added. Nano titanium dioxide can promote the germination of litchi pollen, prolong the opening time of female flowers, and increase the fruit setting rate. In addition, the pollen is taken out of the low temperature environment in advance and placed at room temperature for awakening. According to the ambient temperature, the awakening time generally takes about 8 hours. Based on the preliminary litchi pollination nutrient solution, a variety of nutrient solutions with different concentrations are prepared, for example, the concentration of nano titanium dioxide is prepared as 100, 300, 600 and 900 mg / L, and then the optimal concentration is determined by specific experiments. When preparing litchi pollination nutrient solution, nano titanium dioxide can be treated by ultrasonic dispersion and other methods to form a uniform solution. During the litchi flowering period, different varieties of litchi trees were selected for experiments to observe the effects of different nutrient solution formulas on the fruit setting rate and determine the optimal formula.

[0026] Step S2: Prepare litchi pollination nutrient solution based on the optimal preparation concentration of litchi pollination nutrient solution, and add the prepared litchi pollination nutrient solution to the pollination device, set the flight path and control target of the UAV based on the farmland layout data and flower distribution information, calculate the ideal parameters of the UAV at different times based on the flight path and control target using a specific function, and initialize the flight parameters of the UAV and the pollination parameters of the pollination device based on the ideal parameters.

[0027] Specifically, a litchi pollination nutrient solution is prepared based on the optimal formula, and then pollen is added to the nutrient solution and stirred evenly, and finally added to the pollination device to prepare for pollination operations. The geographical information system data of the farmland and the multispectral camera are used to collect flower distribution information, and the flight path of the drone is planned to ensure that the drone covers the entire farmland and accurately locates each flower to be pollinated. Based on the flight path and control objectives, a specific function (such as a transfer function) is used to calculate the ideal parameters of the drone at different time points. The ideal parameters refer to the flight speed, altitude and pollination amount. The ideal parameters are used to initialize the flight parameters of the drone and the pollination parameters of the pollination device. Initialization can improve the accuracy and efficiency of the drone's pollination operation.

[0028] Step S3: Based on the flight path of the UAV, the UAV starts pollination operation in the pollination operation area, and during the pollination operation, the sensor system periodically collects environmental parameters and flower status data, and transmits the collected environmental parameters and flower status data to the control unit.

[0029] Specifically, the collection unit is responsible for periodically collecting environmental parameters and flower status data during the pollination operation. The collection unit uses environmental sensors on the drone platform to measure environmental parameters such as temperature, humidity, wind speed and wind direction in real time. The flower status data is also obtained through a multispectral camera, including flowering status and flower density. The collection unit can adjust the flight parameters and pollination parameters of the drone based on the latest environmental and flower status information, enhance the flexibility of the drone pollination system, quickly respond to environmental changes and differences in flower status, and improve the success rate of pollination.

[0030] Step S4: The control unit adjusts the flight parameters of the drone and the pollination parameters of the pollination device based on the environmental parameters and the flower status data, and dynamically adjusts the magnification of the drone controller based on the difference between the actual parameters of the drone and the ideal parameters.

[0031] Specifically, the control unit is responsible for dynamically adjusting the flight parameters of the drone and the pollination parameters of the pollination device according to the environmental parameters and flower status data provided by the acquisition unit. The control unit first analyzes environmental parameters such as wind speed and direction as well as flower status and density. Based on the analysis results, the control unit adjusts the flight speed, altitude and direction of the drone, so that the drone can stably fly and locate each flower. The control unit also adjusts the pollination amount and spraying direction of the pollination device according to the state of the flower to achieve the best pollination effect. The control unit also monitors the difference between the actual and ideal parameters of the drone, and dynamically adjusts the magnification of the drone controller to optimize the control performance. Dynamic adjustment based on real-time data can not only improve the accuracy and efficiency of drone pollination operations, but also enhance the stability and reliability of the system, so that drones can fly accurately in complex farmland environments.

[0032] In the embodiments of the present application, efficient and accurate pollination operations can be achieved through the coordination of the above steps.

[0033] In one specific embodiment, see Figure 2 , step S2 further includes:

[0034] The farmland layout analysis unit obtains a high-definition map of the farmland layout through drone aerial photography before the pollination operation begins, and identifies the flower distribution locations from the high-definition map through image recognition technology. The pollination task planning unit obtains the pollination operation area based on the high-definition map and the flower distribution locations, and plans the flight path of the drone based on the GIS system.

[0035] Specifically, in the preparation stage of the drone pollination operation, as the basis of the entire pollination operation process, the farmland layout analysis unit and the pollination task planning unit work together. First, the farmland layout analysis unit uses drone aerial photography technology to obtain a high-definition map of the farmland. By carrying a high-resolution camera, the drone flies over the farmland and takes high-definition images covering the entire farmland. The image recognition algorithm can accurately identify the distribution of flowers from the high-definition map, including the specific coordinates and density information of each flower. This process improves the accuracy of flower positioning.

[0036] Based on the high-definition map and the location of the flower distribution, the pollination mission planning unit is further involved. This unit uses the power of the geographic information system (GIS) and combines the boundaries, terrain and flower distribution data of the farmland to accurately divide the pollination operation area. The GIS system can intelligently plan the flight path of the drone based on the density and distribution of the flowers. The planned path is designed to ensure that the drone can efficiently cover all the flowers while avoiding obstacles in the farmland, such as trees and telephone poles. In this way, the flight path of the drone not only optimizes the pollination efficiency, but also reduces energy consumption and flight time. The intelligent path planning method enables the drone to accurately and efficiently complete the pollination task in the complex and changing farmland environment, significantly improving the quality of pollination operations.

[0037] In one specific embodiment, see Figure 2 , step S2 further includes:

[0038] A specific function definition unit, the specific function is expressed by formula 1:

[0039]

[0040] Among them, s represents the complex frequency variable in the Laplace transform, b0 and b1 represent the coefficients of the numerator, and a0, a1 and a2 represent the coefficients of the denominator. The ideal parameter calculation unit presets the control target of the UAV, and calculates the ideal parameters of the UAV at different times based on the specific function and control target.

[0041] Specifically, in the initialization phase of the UAV pollination mission, the specific function definition unit and the ideal parameter calculation unit are the key parts to achieve precise control. The specific function definition unit is responsible for constructing a mathematical model, which is represented by Formula 1 and is used to describe the dynamic behavior of the UAV system. Formula 1 is a transfer function. The selection of coefficients is based on the physical characteristics and control requirements of the UAV, which determines the response characteristics of the system to the input signal. The ideal parameter calculation unit uses this specific function and the preset control target to calculate the ideal parameters of the UAV at different time points. The control target is set according to the mission requirements, for example, the UAV needs to reach a certain position at a specific time, fly at a specific speed, or reach a specific height. Based on the above goals, the ideal parameter calculation unit obtains the expected state of the UAV at each time point through mathematical calculations, such as the expected position, speed, altitude, and pollination amount. The ideal parameters refer to the reference of the UAV's flight control system, so that the control system can adjust the flight behavior of the UAV according to the above parameters to ensure that it performs the pollination mission according to the predetermined trajectory and parameters.

[0042] Through the collaborative work of the specific function definition unit and the ideal parameter calculation unit, the UAV control system can accurately plan the behavior at each time point before the pollination task begins, thereby improving the accuracy and efficiency of task execution. The parameter calculation method based on the mathematical model provides a theoretical basis for the intelligent and automated control of UAVs, and UAVs can stably and efficiently complete pollination tasks in complex and changeable farmland environments.

[0043] In one specific embodiment, see Figure 2 , calculating the ideal parameters of the drone at different times include:

[0044] The control targets include the drone's position target coordinates, speed target value, altitude target value, pollination target value and path target value. The pollination target value refers to the amount of pollen sprayed on the flowers, and the path target value refers to the planned flight path of the drone.

[0045] Specifically, the ideal parameter calculation unit is the core part of the UAV pollination control system, which is responsible for calculating the ideal parameters of the UAV at different time points according to the preset control objectives and specific functions (transfer functions). The above ideal parameters ensure that the UAV can perform the pollination task according to the predetermined objectives.

[0046] In a specific embodiment, calculating the ideal parameters of the drone at different times also includes:

[0047] Ideal parameters refer to ideal position coordinates, ideal speed, ideal height, ideal pollination amount and ideal path. Ideal parameters are the concretization of control objectives.

[0048] Specifically, the ideal parameter calculation unit concretizes the abstract control target into an operational ideal parameter, so that the UAV's flight control system has an accurate reference value. The ideal parameters include the ideal position coordinates, the ideal speed value, the ideal height value, the ideal pollination amount value and the ideal path value, which are calculated based on the control target and the specific function (transfer function) to ensure that the UAV can accurately perform every action in the pollination mission. Through the configuration of the ideal parameter calculation unit, the UAV pollination system can accurately plan the behavior at each time point before the mission begins, thereby improving the accuracy and efficiency of the pollination operation.

[0049] In a specific embodiment, calculating the ideal parameters of the drone at different times also includes:

[0050] Perform an inverse Laplace transform on a specific function based on Formula 2 to obtain the result in the time domain. Formula 2 is as follows:

[0051] v(t)=L -1 {G(s)*V(s)}(Formula 2)

[0052] Where v(t) represents the ideal speed value at time t, V(s) represents the Laplace transform of the speed target value, and L -1 represents the inverse Laplace transform; based on formula 2, the ideal value of position, ideal value of height, ideal value of pollination amount and ideal value of path at time t are calculated respectively.

[0053] Specifically, by converting the control target into specific values ​​in the time domain, the drone can perform tasks according to precise values ​​and reduce errors; by calculating the ideal path value, all flowers can be efficiently covered during pollination operations, reducing flight time and energy consumption; and by calculating the ideal pollination amount, pollen can be sprayed accurately according to the state and needs of the flowers, thereby improving the success rate and uniformity of pollination.

[0054] In a specific embodiment, step S3 further includes:

[0055] The environmental sensor periodically collects environmental parameters in the pollination operation area at preset time intervals, and the flower status sensor obtains flower status data through image acquisition, where image acquisition refers to taking crop growth images through a multispectral camera and obtaining flower status data from the crop growth images.

[0056] Specifically, through the collection unit, the drone pollination system can obtain the necessary environmental and flower status information in real time during the pollination operation, thereby achieving efficient and accurate pollination tasks.

[0057] In a specific embodiment, step S4 further includes:

[0058] Receive environmental parameters and flower status data, adjust the flight parameters of the UAV based on the wind speed and wind direction in the environmental parameters and the flower density in the flower status data, and adjust the pollination parameters of the pollination device based on the temperature and humidity in the environmental parameters and the flowering state and flower density in the flower status data, wherein the flight parameters include position coordinates, flight speed, flight altitude and flight path, and the pollination parameters include at least spraying amount and spraying angle, and may also include spraying frequency, spraying pressure, spraying mode and spraying interval, etc.

[0059] Specifically, the drone pollination system can adjust the flight and pollination parameters in real time during the pollination operation through the control unit to ensure efficient and accurate execution of the task. The dynamic adjustment mechanism is the basis of the intelligent and automated control of drones, enabling drones to stably and efficiently complete pollination tasks in complex and changing farmland environments.

[0060] In a specific embodiment, step S4 further includes:

[0061] A drone controller is introduced to obtain the actual parameters of the drone, and multiple differences between the actual parameters and the ideal parameters are calculated. When the differences are all less than or equal to a first threshold, the magnification of the drone controller is dynamically adjusted to minimize the difference between the actual parameters and the ideal parameters of the drone. When the difference is greater than the first threshold, it is determined that the drone is abnormal and the drone is controlled to return. The actual parameters of the drone include the flight parameters of the current drone and the pollination parameters of the pollination device. The drone controller consists of three parts: proportional, integral and differential. The magnification represents the response speed to the difference.

[0062] Specifically, by introducing a drone controller and dynamically adjusting the magnification, the control unit can more accurately control the behavior of the drone, ensuring that it can stably and efficiently complete pollination tasks in complex and changing farmland environments.

[0063] In a specific embodiment, step S4 further includes:

[0064] Initialize the magnification of the drone controller, calculate the difference between the actual parameters and the ideal parameters of the drone at each time point, calculate the control parameter value based on the difference using the drone controller formula, and dynamically adjust the magnification of the drone controller based on the control parameter value.

[0065] Specifically, by dynamically adjusting the magnification, the drone controller can quickly respond and minimize the difference between the actual parameters and the ideal parameters, improving control accuracy. By precisely controlling the flight and pollination behavior of the drone, the efficient and accurate execution of the task is ensured, and the success rate and uniformity of pollination are improved. The control unit can also monitor and adjust the behavior of the drone in real time to ensure that it always performs the task according to the predetermined goals and improve the efficiency of task execution.

[0066] Embodiment 2:

[0067] The above describes the method for screening and applying the nutrient solution for litchi pollination by integrating the drone technology in the embodiment of the present application. The following describes the system for screening and applying the nutrient solution for litchi pollination by integrating the drone technology in the embodiment of the present application. Figure 3 In the embodiment of the present application, an embodiment of the litchi pollination nutrient solution screening and application system integrating drone technology includes:

[0068] Prepare the drone platform and sensor system. The drone platform includes a GPS positioning system, a multispectral camera and a pollination device. The pollination device also includes a spraying system and an adjustable nozzle. The sensor system includes an environmental sensor and a crop status sensor. The environmental sensor is used to measure environmental parameters, including temperature, humidity, wind speed and wind direction. The crop status sensor obtains flower status data through a multispectral camera. The flower status data includes flowering period status and flower density. The system includes the following modules:

[0069] The nutrient solution screening unit is used for screening the litchi pollination nutrient solution, including ingredient selection, formula optimization and test verification, wherein the ingredient selection also includes first selecting the basic ingredients, and then adding nano titanium dioxide to the basic ingredients based on the growth characteristics and needs of litchi to form a preliminary litchi pollination nutrient solution, and then taking the pollen out of the low-temperature environment and placing it at room temperature for awakening, and the awakening time is determined based on the temperature of the day, and the formula optimization refers to preparing a variety of nutrient solutions of different concentrations based on the preliminary litchi pollination nutrient solution, and the test verification refers to adding pollen to nutrient solutions of different concentrations respectively, and determining through experiments that the concentration corresponding to the optimal litchi fruit setting rate is the optimal concentration of the litchi pollination nutrient solution;

[0070] an initialization unit, for preparing litchi pollination nutrient solution based on the optimal preparation concentration of the litchi pollination nutrient solution, adding the prepared litchi pollination nutrient solution to the pollination device, setting the flight path and control target of the UAV based on the farmland layout data and the flower distribution information, calculating the ideal parameters of the UAV at different times based on the flight path and the control target using a specific function, and initializing the flight parameters of the UAV and the pollination parameters of the pollination device based on the ideal parameters;

[0071] A collection unit is used for the UAV to start pollination in the pollination operation area based on the flight path of the UAV, and during the pollination operation, periodically collect environmental parameters and flower status data through the sensor system, and transmit the collected environmental parameters and flower status data to the control unit;

[0072] The control unit is used to adjust the flight parameters of the UAV and the pollination parameters of the pollination device based on the environmental parameters and the flower status data, and dynamically adjust the magnification of the UAV controller based on the difference between the actual parameters of the UAV and the ideal parameters.

[0073] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0074] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0075] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for screening and applying litchi pollination nutrient solution integrating drone technology, characterized in that: The method comprises: Step S1: The screening of litchi pollination nutrient solution includes ingredient selection, formula optimization and experimental verification, wherein the ingredient selection also includes first selecting basic ingredients, and then adding nano titanium dioxide to the basic ingredients based on the growth characteristics and needs of litchi to form a preliminary litchi pollination nutrient solution, and then taking the pollen out of the low-temperature environment and placing it at room temperature for awakening, wherein the awakening time is determined based on the temperature of the day, the formula optimization refers to preparing a plurality of nutrient solutions of different concentrations based on the preliminary litchi pollination nutrient solution, and the experimental verification refers to adding the pollen to nutrient solutions of different concentrations respectively, and determining through experiments that the preparation concentration corresponding to the optimal litchi fruit setting rate is used as the optimal preparation concentration of the litchi pollination nutrient solution; Step S2: preparing litchi pollination nutrient solution based on the optimal preparation concentration of the litchi pollination nutrient solution, adding the prepared litchi pollination nutrient solution to the pollination device, setting the flight path and control target of the UAV based on the farmland layout data and the flower distribution information, calculating the ideal parameters of the UAV at different times based on the flight path and the control target using a specific function, and initializing the flight parameters of the UAV and the pollination parameters of the pollination device based on the ideal parameters; Step S3: Based on the flight path of the drone, the drone starts the pollination operation in the pollination operation area, and during the pollination operation, the environmental parameters and the flower status data are periodically collected through a sensor system, and the collected environmental parameters and the flower status data are transmitted to a control unit; Step S4: The control unit adjusts the flight parameters of the UAV and the pollination parameters of the pollination device based on the environmental parameters and the flower status data, and dynamically adjusts the magnification of the UAV controller based on the difference between the actual parameters of the UAV and the ideal parameters.

2. The method according to claim 1, characterized in that The step S2 further comprises: Before the pollination operation begins, a high-definition map of the farmland layout is obtained by drone aerial photography, and the flower distribution positions are identified from the high-definition map by image recognition technology; Based on the high-definition map and the flower distribution positions, the pollination operation area is obtained, and the flight path of the UAV is planned based on the GIS system.

3. The method according to claim 1, characterized in that The step S2 further comprises: The specific function is expressed by Formula 1: Where s represents the complex frequency variable in the Laplace transform, b0 and b1 represent the coefficients of the numerator, and a0, a1, and a2 represent the coefficients of the denominator; A control target of the drone is preset, and ideal parameters of the drone at different times are calculated based on the specific function and the control target.

4. The method according to claim 3, characterized in that Calculation of the ideal parameters of the drone at different times includes: The control targets include the position target coordinates, speed target value, altitude target value, pollination amount target value and path target value of the UAV, the pollination amount target value refers to the spraying amount of pollen sprayed on the flowers, and the path target value refers to the planned flight path of the UAV.

5. The method according to claim 4, characterized in that Calculating the ideal parameters of the drone at different times also includes: The ideal parameters refer to the ideal coordinates of the position, the ideal value of the speed, the ideal value of the height, the ideal value of the pollination amount and the ideal value of the path, and the ideal parameters are the concretization of the control target.

6. The method according to claim 5, characterized in that Calculating the ideal parameters of the drone at different times also includes: The specific function is subjected to an inverse Laplace transform based on Formula 2 to obtain a result in the time domain. Formula 2 is as follows: v(t)=L -1 {G(s)*V(s)}(Formula 2) Wherein, v(t) represents the ideal speed value at time t, V(s) represents the Laplace transform of the speed target value, and L -1 represents the inverse Laplace transform; Based on Formula 2, the ideal value of position, ideal value of altitude, ideal value of pollination amount and ideal value of path at time t are calculated respectively.

7. The method according to claim 1, characterized in that The step S3 further comprises: The environmental sensor periodically collects environmental parameters in the pollination operation area at preset time intervals, and the flower status sensor obtains flower status data through image acquisition, wherein the image acquisition refers to taking crop growth images through a multispectral camera and obtaining the flower status data from the crop growth images.

8. The method according to claim 1, characterized in that The step S4 further comprises: Receive the environmental parameters and the flower status data, adjust the flight parameters of the UAV based on the wind speed and wind direction in the environmental parameters and the flower density in the flower status data, and adjust the pollination parameters of the pollination device based on the temperature and humidity in the environmental parameters and the flowering state and flower density in the flower status data, wherein the flight parameters include position coordinates, flight speed, flight altitude and flight path, and the pollination parameters include spraying amount and spraying angle.

9. The method according to claim 8, characterized in that The step S4 further comprises: A drone controller is introduced to obtain actual parameters of the drone, and multiple differences between the actual parameters and the ideal parameters are calculated. When the differences are all less than or equal to a first threshold, the magnification of the drone controller is dynamically adjusted to minimize the difference between the actual parameters of the drone and the ideal parameters. When the difference is greater than the first threshold, it is determined that the drone is abnormal and the drone is controlled to return. The actual parameters of the drone include the current flight parameters of the drone and the pollination parameters of the pollination device. The drone controller consists of three parts: proportional, integral and differential. The magnification represents the degree of response to the difference.

10. A litchi pollination nutrient solution screening and application system integrating drone technology, used to implement the litchi pollination nutrient solution screening and application method integrating drone technology as described in any one of claims 1 to 9, characterized in that: The system comprises: A nutrient solution screening unit, for screening litchi pollination nutrient solution, including ingredient selection, formula optimization and test verification, wherein the ingredient selection also includes first selecting basic ingredients, and then adding nano titanium dioxide to the basic ingredients based on the growth characteristics and needs of litchi to form a preliminary litchi pollination nutrient solution, and then taking the pollen out of the low-temperature environment and placing it at room temperature for awakening, wherein the awakening time is determined based on the temperature of the day, the formula optimization refers to preparing a plurality of nutrient solutions of different concentrations based on the preliminary litchi pollination nutrient solution, and the test verification refers to adding the pollen to nutrient solutions of different concentrations respectively, and determining through experiments that the preparation concentration corresponding to the optimal litchi fruit setting rate is used as the optimal preparation concentration of the litchi pollination nutrient solution; an initialization unit, for preparing a litchi pollination nutrient solution based on the optimal preparation concentration of the litchi pollination nutrient solution, adding the prepared litchi pollination nutrient solution to a pollination device, setting a flight path and a control target of the drone based on farmland layout data and flower distribution information, calculating ideal parameters of the drone at different times based on the flight path and the control target using a specific function, and initializing flight parameters of the drone and pollination parameters of the pollination device based on the ideal parameters; A collection unit, configured to start the pollination operation of the drone in the pollination operation area based on the flight path of the drone, and periodically collect the environmental parameters and the flower status data through the sensor system during the pollination operation, and transmit the collected environmental parameters and the flower status data to a control unit; A control unit is used to adjust the flight parameters of the drone and the pollination parameters of the pollination device based on the environmental parameters and the flower status data, and dynamically adjust the magnification of the drone controller based on the difference between the actual parameters of the drone and the ideal parameters.

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