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

Abstract

The application relates to the technical field of unmanned aerial vehicle control, and discloses a litchi pollination nutrient solution screening and application method and system fusing unmanned aerial vehicle technology, which comprises the following steps: screening the optimal preparation concentration of a litchi pollination nutrient solution, adding the prepared litchi pollination nutrient solution into a pollination device, setting the flight path and control target of an unmanned aerial vehicle based on farmland layout data and flower distribution information, calculating the ideal parameters of the unmanned aerial vehicle at different times by using a specific function, and initializing the flight parameters of the unmanned aerial vehicle and the pollination parameters of the pollination device; the unmanned aerial vehicle starts pollination operation in a pollination operation area, and periodically collects environmental parameters and flower state data during the pollination operation; the flight parameters of the unmanned aerial vehicle and the pollination parameters of the pollination device are adjusted based on the environmental parameters and the flower state data, and the amplification multiple of the unmanned aerial vehicle controller is dynamically adjusted. The application can realize efficient and accurate pollination operation.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) control technology, and in particular to a method and system for screening and applying litchi pollination nutrient solution that integrates UAV technology. Background Technology

[0002] The application of drones in agriculture is becoming increasingly widespread, 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 various factors, such as flight speed, altitude, spraying device parameters, and environmental conditions. Most existing drone pollination systems use fixed parameter control, making it difficult to adapt to different farmland environments and crop needs, resulting in low pollination accuracy.

[0003] A similar prior art is disclosed in Chinese patent application CN108353784A, which provides a drone pollination device and method. The device includes a drone with a rotor above it and an air outlet channel suspended below it. A pollen outlet channel is located below the air outlet channel, with its outlet positioned above the pollen outlet channel. Both the air outlet and pollen outlet are horizontally aligned. An air intake fan is installed at the pollen inlet of the pollen outlet channel, and the air intake is located below the rotor. This drone pollination device can draw in pollen and spray it horizontally to the sides of the drone. However, this application diffuses the pollen over a wider area through the airflow from the outlet, resulting in pollen waste, low pollination precision, and low pollination efficiency. Summary of the Invention

[0004] To address the aforementioned technical issues, this application provides a method and system for screening and applying litchi pollination nutrient solution that integrates drone technology. By dynamically adjusting the magnification of the drone controller, efficient and precise pollination operations can be achieved.

[0005] This application provides a method for screening and applying litchi pollination nutrient solution that integrates drone technology. The method includes:

[0006] Step S1: The screening of litchi pollination nutrient solution includes component selection, formula optimization, and experimental verification. The component selection includes first selecting basic components, and then adding nano-titanium dioxide to the basic components based on the growth characteristics and needs of litchi to form a preliminary litchi pollination nutrient solution. After that, the pollen is taken out from the low temperature environment and placed at room temperature for pollen awakening. The pollen awakening time is determined based on the temperature of the day. The formula optimization refers to preparing a variety of nutrient solutions with different concentrations based on the preliminary litchi pollination nutrient solution. The experimental verification refers to adding the pollen to nutrient solutions of different concentrations and determining the optimal concentration of litchi pollination nutrient solution through experiments.

[0007] Step S2: Prepare the litchi pollination nutrient solution based on the optimal concentration of the litchi pollination nutrient solution, add the prepared litchi pollination nutrient solution to the pollination device, set the flight path and control target of the UAV based on farmland layout data and flower distribution information, calculate the ideal parameters of the UAV at different times using a specific function based on the flight path and the control target, and initialize 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 UAV, the UAV begins pollination in the pollination area, and during the pollination process, it periodically collects the environmental parameters and flower status data through the sensor system, and transmits the collected environmental parameters and flower status data to the control unit.

[0009] 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.

[0010] This application also provides a litchi pollination nutrient solution screening and application system integrating drone technology, including a drone platform and a sensor system. The drone platform includes a GPS positioning system, a multispectral camera, and a pollination device. The pollination device further includes a spraying system and adjustable nozzles. 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 acquires flower status data through the multispectral camera, including flowering period status and flower density. The system also includes:

[0011] The nutrient solution screening unit for litchi pollination nutrient solution includes component selection, formula optimization, and experimental verification. The component selection includes first selecting basic components, and then adding nano-titanium dioxide to the basic components based on the growth characteristics and needs of litchi to form a preliminary litchi pollination nutrient solution. After that, the pollen is taken out from the low temperature environment and placed at room temperature for pollen awakening. The pollen awakening time is determined based on the temperature of the day. The formula optimization refers to preparing a variety of nutrient solutions with different concentrations based on the preliminary litchi pollination nutrient solution. The experimental verification refers to adding the pollen to different concentrations of nutrient solution and determining the optimal concentration of litchi pollination nutrient solution through experiments.

[0012] An initialization unit is used to prepare litchi pollination nutrient solution based on the optimal concentration of the litchi pollination nutrient solution, add the prepared litchi pollination nutrient solution to the pollination device, set the flight path and control target of the UAV based on farmland layout data and flower distribution information, calculate the ideal parameters of the UAV at different times using a specific function based on the flight path and the control target, and initialize the flight parameters of the UAV and the pollination parameters of the pollination device based on the ideal parameters.

[0013] The data acquisition unit is used to collect environmental parameters and flower status data periodically through the sensor system during the pollination operation, based on the flight path of the UAV, when the UAV starts pollination operation in the pollination operation area, and transmits the collected environmental parameters and flower status data to the control unit.

[0014] The 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 to 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] The technical solution provided in this application uses a nutrient solution screening unit to select the optimal concentration of lychee pollination nutrient solution for achieving the best fruit setting rate. Based on this concentration, the lychee pollination nutrient solution is prepared and then added to the pollination device of the drone. An initialization unit precisely sets the drone's flight path and control target, and calculates ideal parameters to provide accurate initialization parameters for the drone's flight and pollination tasks, improving the accuracy and efficiency of task execution and ensuring the drone is in optimal condition at the start of the pollination operation. A data acquisition unit periodically collects environmental parameters and flower status data during the pollination process and transmits this data to the control unit in real time, providing the control unit with real-time environmental and flower status information. This allows the system to quickly respond to environmental changes and differences in flower status, thereby improving the pollination success rate. Using the collected environmental parameters and flower status data, the control unit can dynamically adjust the drone's flight parameters and the pollination device's pollination parameters, and dynamically adjust the drone controller's magnification based on the difference between actual and ideal parameters, improving the drone's flight stability and pollination accuracy. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of an embodiment of a method for screening and applying litchi pollination nutrient solution that integrates drone technology, as described in this application.

[0019] Figure 2 This is a schematic diagram of one embodiment of the initialization unit in this 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, as described in this application. Detailed Implementation

[0021] This application provides 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 present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; 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 explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0022] Example 1:

[0023] The specific process of the embodiments of this application is described below, please refer to... Figure 1 The present application embodiment of 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 component selection, formula optimization, and experimental verification. Component selection includes first selecting basic components, and then adding nano-titanium dioxide to the basic components based on the growth characteristics and needs of litchi to form a preliminary litchi pollination nutrient solution. After that, the pollen is taken out from the low-temperature environment and placed at room temperature for pollen awakening. The pollen awakening time is determined based on the temperature of the day. Formula optimization refers to preparing a variety of nutrient solutions with different concentrations based on the preliminary litchi pollination nutrient solution. Experimental verification refers to adding pollen to nutrient solutions of different concentrations and determining the optimal concentration of litchi pollination nutrient solution through experiments.

[0025] Specifically, the basic components of the litchi pollination nutrient solution can be selected by referring to the formula of the pear pollination nutrient solution, which includes water, xanthan gum, calcium, boron, and sugar. This formula can better dissolve pollen, prolong the flowering period, and increase the pollination rate. Based on the growth characteristics and needs of litchi, nano-titanium dioxide is added. Nano-titanium dioxide can promote litchi pollen germination, prolong the opening time of female flowers, and increase the fruit set rate. In addition, the pollen should be removed from the low-temperature environment in advance and placed at room temperature for aging, which generally takes about 8 hours depending on the ambient temperature. Based on the preliminary litchi pollination nutrient solution, various concentrations of nutrient solution are prepared, such as 100, 300, 600, and 900 mg / L of nano-titanium dioxide. The optimal concentration is then determined through specific experiments. When preparing the litchi pollination nutrient solution, nano-titanium dioxide can be treated with methods such as ultrasonic dispersion to form a homogeneous solution. During the litchi flowering period, experiments were conducted on different varieties of litchi trees to observe the effects of different nutrient solution formulations on fruit set rate and determine the optimal formulation.

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

[0027] Specifically, a nutrient solution for lychee pollination is prepared based on an optimal formula. Pollen is then added to the nutrient solution and stirred thoroughly before being added to the pollination device, preparing for the pollination operation. Geographic Information System (GIS) data of the farmland and multispectral cameras 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, ideal parameters for the drone at different time points are calculated using a specific function (such as a transfer function). These ideal parameters refer to flight speed, altitude, and pollination amount. These ideal parameters are used to initialize the drone's flight parameters and the pollination device's pollination parameters, improving the accuracy and efficiency of the drone pollination operation.

[0028] Step S3: Based on the drone's flight path, the drone begins pollination operations in the pollination area. During the pollination process, the drone periodically collects environmental parameters and flower status data through a sensor system and transmits the collected environmental parameters and flower status data to the control unit.

[0029] Specifically, the data acquisition unit is responsible for periodically collecting environmental parameters and flower status data during drone pollination operations. Utilizing environmental sensors on the drone platform, the unit measures environmental parameters such as temperature, humidity, wind speed, and wind direction in real time. It also acquires flower status data, including flowering stage and flower density, through a multispectral camera. Based on the latest environmental and flower status information, the acquisition unit can adjust the drone's flight and pollination parameters, enhancing the flexibility of the drone pollination system, enabling rapid response to environmental changes and differences in flower status, and improving the pollination success rate.

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

[0031] Specifically, the control unit is responsible for dynamically adjusting the drone's flight parameters and the pollination device's parameters based on 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 this analysis, the control unit adjusts the drone's flight speed, altitude, and direction, enabling the drone to fly stably and locate each flower. The control unit also adjusts the pollination amount and spraying direction of the pollination device according to the flower's status to achieve optimal pollination results. The control unit also monitors the difference between the drone's actual parameters and ideal parameters, dynamically adjusting the drone controller's magnification to optimize control performance. This dynamic adjustment based on real-time data not only improves the accuracy and efficiency of drone pollination operations but also enhances the system's stability and reliability, enabling the drone to fly accurately even in complex farmland environments.

[0032] In this embodiment of the application, the coordination between the above steps can achieve efficient and accurate pollination operations.

[0033] In one specific embodiment, see Figure 2 Step S2 also includes:

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

[0035] Specifically, in the preparation phase of drone pollination operations, the farmland layout analysis unit and the pollination task planning unit work collaboratively, forming the foundation of the entire pollination process. First, the farmland layout analysis unit uses drone aerial photography technology to acquire high-resolution maps of the farmland. Equipped with a high-resolution camera, the drone flies over the farmland, capturing high-resolution images covering the entire area. Image recognition algorithms can accurately identify the distribution of flowers from the high-resolution map, including the specific coordinates and density information of each flower. This process improves the accuracy of flower positioning.

[0036] Based on high-definition maps and flower distribution data, the pollination task planning unit further intervenes. This unit utilizes the powerful capabilities of a Geographic Information System (GIS), combining data on farmland boundaries, topography, and flower distribution to precisely delineate the pollination operation area. The GIS system can intelligently plan the drone's flight path based on flower density and distribution. The planned path aims to ensure the drone efficiently covers all flowers while avoiding obstacles in the farmland, such as trees and utility poles. In this way, the drone's flight path not only optimizes pollination efficiency but also reduces energy consumption and flight time. This intelligent path planning method enables the drone to accurately and efficiently complete the pollination task in complex and changing farmland environments, significantly improving the quality of pollination operations.

[0037] In one specific embodiment, see Figure 2 Step S2 also includes:

[0038] A specific function is defined as a unit, and the specific function is represented by Formula 1:

[0039]

[0040] 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; the ideal parameter calculation unit, with a preset control target for the UAV, calculates the ideal parameters of the UAV at different times based on a specific function and the control target.

[0041] Specifically, in the initialization phase of a drone pollination mission, the specific function definition unit and the ideal parameter calculation unit are crucial for achieving precise control. The specific function definition unit is responsible for constructing a mathematical model, represented by Equation 1, to describe the dynamic behavior of the drone system. Equation 1 is a transfer function; the coefficients are chosen based on the drone's physical characteristics and control requirements, determining the system's response characteristics to input signals. The ideal parameter calculation unit then uses this specific function and preset control objectives to calculate the ideal parameters of the drone at different time points. The control objectives are set according to mission requirements, such as the drone needing to reach a certain location at a specific time, fly at a specific speed, or reach a specific altitude. Based on these objectives, the ideal parameter calculation unit uses mathematical calculations to derive the drone's desired state at each time point, such as the desired position, speed, altitude, and pollen volume. Ideal parameters serve as a reference for the drone's flight control system, enabling the system to adjust the drone's flight behavior according to these parameters, ensuring it performs the pollination task according to the predetermined trajectory and parameters.

[0042] Through the collaborative work of specific function definition units and ideal parameter calculation units, the UAV control system can precisely 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 mathematical models provides the theoretical foundation for the intelligent and automated control of UAVs, enabling them to stably and efficiently complete pollination tasks in complex and ever-changing farmland environments.

[0043] In one specific embodiment, see Figure 2 The ideal parameters for calculating drones at different times include:

[0044] The control objectives 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 onto 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 component of the UAV pollination control system. It is responsible for calculating the ideal parameters of the UAV at different time points based on the preset control objectives and a specific function (transfer function). These ideal parameters ensure that the UAV can perform the pollination task according to the predetermined objectives.

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

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

[0048] Specifically, the ideal parameter calculation unit concretizes the abstract control objective into operable ideal parameters, thus providing the UAV's flight control system with precise reference values. These ideal parameters include ideal position coordinates, ideal velocity values, ideal altitude values, ideal pollination amount values, and ideal path values. They are calculated based on the control objective and a specific function (transfer function), ensuring that the UAV can accurately execute every action during the pollination mission. Through the configuration of the ideal parameter calculation unit, the UAV pollination system can precisely plan its behavior at each time point before the mission begins, thereby improving the accuracy and efficiency of the pollination operation.

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

[0050] Based on Equation 2, an inverse Laplace transform is performed on a specific function to obtain the result in the time domain. Equation 2 is as follows:

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

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

[0053] Specifically, by converting control targets into specific values ​​in the time domain, drones can perform tasks according to precise values, reducing errors; by calculating ideal path values, pollination operations can efficiently cover all flowers, reducing flight time and energy consumption; and by calculating ideal pollination amounts, pollen can be sprayed precisely according to the condition and needs of the flowers, improving the success rate and uniformity of pollination.

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

[0055] The environmental sensor periodically collects environmental parameters within the pollination area at preset time intervals, while the flower status sensor acquires flower status data through image acquisition. Image acquisition refers to capturing crop growth images using a multispectral camera and obtaining flower status data from the crop growth images.

[0056] Specifically, the drone pollination system can acquire necessary environmental and flower status information in real time during the pollination process, enabling efficient and accurate pollination.

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

[0058] The system receives environmental parameters and flower status data. Based on wind speed and direction in the environmental parameters and flower density in the flower status data, it adjusts the flight parameters of the drone. It also adjusts the pollination parameters of the pollination device based on temperature and humidity in the environmental parameters and flowering period and flower density in the flower status data. The flight parameters include position coordinates, flight speed, flight altitude and flight path. The pollination parameters include at least the spray volume and spray angle, and may also include spray frequency, spray pressure, spray mode and spray interval.

[0059] Specifically, the control unit of the drone pollination system can adjust flight and pollination parameters in real time during pollination operations, ensuring efficient and precise task execution. This dynamic adjustment mechanism is the foundation of the drone's intelligent and automated control, enabling the drone to stably and efficiently complete pollination tasks in complex and ever-changing farmland environments.

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

[0061] A drone controller is introduced to acquire the actual parameters of the drone and calculate multiple differences between the actual and ideal parameters. When all differences are less than or equal to a first threshold, the amplification factor of the drone controller is dynamically adjusted to minimize the difference between the actual and ideal parameters. When the difference is greater than the first threshold, the drone is deemed to have malfunctioned and 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 derivative. The amplification factor represents the response speed to differences.

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

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

[0064] Initialize the amplification factor 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 values ​​using the drone controller formula based on the difference, and dynamically adjust the amplification factor of the drone controller based on the control parameter values.

[0065] Specifically, by dynamically adjusting the magnification, the drone controller can quickly respond and minimize the difference between actual and ideal parameters, improving control accuracy. By precisely controlling the drone's flight and pollination behavior, it ensures efficient and accurate mission execution, improving pollination success rate and uniformity. The control unit can also monitor and adjust the drone's behavior in real time, ensuring it consistently performs tasks according to predetermined objectives, thus improving mission efficiency.

[0066] Example 2:

[0067] The above describes the method for screening and applying litchi pollination nutrient solution using drone technology in the embodiments of this application. The following describes the system for screening and applying litchi pollination nutrient solution using drone technology in the embodiments of this application. Please refer to [link to relevant documentation]. Figure 3 One embodiment of the litchi pollination nutrient solution screening and application system integrating drone technology in this application includes:

[0068] Prepare a 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 adjustable nozzles. The sensor system includes environmental sensors and crop status sensors. The environmental sensors measure environmental parameters, including temperature, humidity, wind speed, and wind direction. The crop status sensors acquire flower status data through the multispectral camera, including flowering period and flower density. The system includes the following modules:

[0069] The nutrient solution screening unit for litchi pollination nutrient solutions includes component selection, formula optimization, and experimental verification. Component selection involves first selecting basic components, and then adding nano-titanium dioxide to the basic components based on the growth characteristics and needs of litchi to form a preliminary litchi pollination nutrient solution. After that, the pollen is taken out from the low-temperature environment and placed at room temperature for pollen awakening. The pollen awakening time is determined based on the temperature of the day. Formula optimization refers to preparing various nutrient solutions of different concentrations based on the preliminary litchi pollination nutrient solution. Experimental verification involves adding pollen to nutrient solutions of different concentrations and determining the optimal concentration of litchi pollination nutrient solution through experiments.

[0070] The initialization unit is used to prepare litchi pollination nutrient solution based on the optimal concentration of litchi pollination nutrient solution, add the prepared litchi pollination nutrient solution to the pollination device, set the flight path and control target of the UAV based on farmland layout data and flower distribution information, calculate the ideal parameters of the UAV at different times using a specific function based on the flight path and control target, and initialize the flight parameters of the UAV and the pollination parameters of the pollination device based on the ideal parameters.

[0071] The data acquisition unit is used to collect environmental parameters and flower status data periodically through the sensor system during the pollination operation, based on the flight path of the UAV. The UAV starts pollination operation in the pollination operation area and transmits 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 drone and the pollination parameters of the pollination device based on environmental parameters and flower status data, and to dynamically adjust the magnification of the drone controller based on the difference between the actual parameters and the ideal parameters of the drone.

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

[0074] If the integrated unit is implemented as 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 this application, in essence, 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0075] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for screening and applying litchi pollination nutrient solution integrating drone technology, characterized in that, The method includes: Step S1: The screening of litchi pollination nutrient solution includes component selection, formula optimization, and experimental verification. The component selection includes first selecting basic components, and then adding nano-titanium dioxide to the basic components based on the growth characteristics and needs of litchi to form a preliminary litchi pollination nutrient solution. After that, the pollen is taken out from the low temperature environment and placed at room temperature for pollen awakening. The pollen awakening time is determined based on the temperature of the day. The formula optimization refers to preparing a variety of nutrient solutions with different concentrations based on the preliminary litchi pollination nutrient solution. The experimental verification refers to adding the pollen to nutrient solutions of different concentrations and determining the optimal concentration of litchi pollination nutrient solution through experiments. Step S2: Prepare the litchi pollination nutrient solution based on the optimal concentration of the litchi pollination nutrient solution, add the prepared litchi pollination nutrient solution to the pollination device, set the flight path and control target of the UAV based on farmland layout data and flower distribution information, calculate the ideal parameters of the UAV at different times using a specific function based on the flight path and the control target, and initialize 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 UAV, the UAV begins pollination in the pollination area and, during the pollination process, periodically collects environmental parameters and flower status data through the sensor system, and transmits the collected environmental parameters and flower status data to the control unit. Step S3 further includes: an environmental sensor periodically collecting environmental parameters within the pollination operation area at preset time intervals, while a flower status sensor acquires flower status data through image acquisition, wherein the image acquisition refers to capturing crop growth images through a multispectral camera and acquiring flower status data from the crop growth images. 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. Step S4 further includes: receiving the environmental parameters and the flower status data; adjusting 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 adjusting the pollination parameters of the pollination device based on the temperature and humidity in the environmental parameters and the flowering period status and flower density in the flower status data. The flight parameters include position coordinates, flight speed, flight altitude and flight path, and the pollination parameters include spraying amount and spraying angle.

2. The method according to claim 1, characterized in that, Step S2 further includes: Before the pollination operation begins, a high-resolution map of the farmland layout is obtained by drone aerial photography, and the distribution location of flowers is identified from the high-resolution map by image recognition technology. Based on the high-definition map and the distribution location of the flowers, 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, Step S2 further includes: The specific function is represented by Formula 1: (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; The control target of the UAV is preset, and the ideal parameters of the UAV at different times are calculated based on the specific function and the control target.

4. The method according to claim 3, characterized in that, Calculating the ideal parameters of the UAV at different times includes: The control objectives include the UAV's position target coordinates, speed target value, altitude target value, pollination amount target value, and path target value. The pollination amount target value refers to the amount of pollen sprayed onto 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 velocity, the ideal value of the altitude, the ideal value of the pollination amount, and the ideal value of the path. 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: Based on Equation 2, an inverse Laplace transform is performed on the specific function to obtain the result in the time domain. Equation 2 is as follows: (Formula 2) Where v(t) represents the ideal velocity value at time t, V(s) represents the Laplace transform of the target velocity value, and L -1 Indicates the inverse Laplace transform; Based on Formula 2, the ideal values ​​for position, height, pollination amount, and path at time t are calculated respectively.

7. The method according to claim 1, characterized in that, Step S4 further includes: A drone controller is introduced to acquire the actual parameters of the drone, calculate multiple differences between the actual parameters and the ideal parameters, and dynamically adjust the amplification factor of the drone controller when all differences are less than or equal to a first threshold, so that the difference between the actual parameters and the ideal parameters is minimized. When the difference is greater than the first threshold, it is determined that the drone has malfunctioned 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 derivative. The amplification factor represents the degree of response to the differences.

8. A lychee pollination nutrient solution screening and application system integrating drone technology, used to implement the lychee pollination nutrient solution screening and application method integrating drone technology as described in any one of claims 1-7, characterized in that, The system includes: The nutrient solution screening unit for litchi pollination nutrient solution includes component selection, formula optimization, and experimental verification. The component selection includes first selecting basic components, and then adding nano-titanium dioxide to the basic components based on the growth characteristics and needs of litchi to form a preliminary litchi pollination nutrient solution. After that, the pollen is taken out from the low temperature environment and placed at room temperature for pollen awakening. The pollen awakening time is determined based on the temperature of the day. The formula optimization refers to preparing a variety of nutrient solutions with different concentrations based on the preliminary litchi pollination nutrient solution. The experimental verification refers to adding the pollen to different concentrations of nutrient solution and determining the optimal concentration of litchi pollination nutrient solution through experiments. An initialization unit is used to prepare litchi pollination nutrient solution based on the optimal concentration of the litchi pollination nutrient solution, add the prepared litchi pollination nutrient solution to the pollination device, set the flight path and control target of the UAV based on farmland layout data and flower distribution information, calculate the ideal parameters of the UAV at different times using a specific function based on the flight path and the control target, and initialize the flight parameters of the UAV and the pollination parameters of the pollination device based on the ideal parameters. The data acquisition unit is configured as follows: based on the flight path of the UAV, the UAV begins pollination operations in the pollination area, and during the pollination operation, it periodically collects environmental parameters and flower status data through the sensor system, and transmits the collected environmental parameters and flower status data to the control unit; the environmental sensor periodically collects environmental parameters in the pollination area at preset time intervals, while the flower status sensor acquires flower status data through image acquisition, wherein the image acquisition refers to capturing crop growth images through a multispectral camera and obtaining flower status data from the crop growth images; The control unit is configured 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 amplification factor of the drone controller based on the difference between the actual parameters of the drone and the ideal parameters; receive the environmental parameters and the flower status data; adjust the flight parameters of the drone 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 period status and flower density in the flower status data. The flight parameters include position coordinates, flight speed, flight altitude, and flight path, and the pollination parameters include spray volume and spray angle.

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