Agricultural precision spraying method and system based on RFID positioning model

Abstract

The present invention relates to the field of modern agricultural technology, and more particularly to a method and system for agricultural precision spraying based on an RFID positioning model. The method comprises the following steps: S1, generating a prescription map with prescription values ​​for each layer of pre-sprayed tree plantings; S2, placing RFID tags on the pre-sprayed tree plantings within the pre-sprayed area; S3, constructing an RFID-based RSSI positioning model; S4, having a spray device identify the pre-sprayed tree plantings; and S5, having the spray device spray the pre-sprayed tree plantings in layers. The system can precisely target each layer of tree plantings, effectively avoiding the overspray and waste associated with traditional spraying methods, saving spray volume, improving spray efficiency, and reducing labor and time costs, thereby reducing agricultural production costs overall.

Description

Technical Field

[0001] The present application relates to the field of modern agricultural technology, and in particular to a method and system for agricultural precision spraying based on an RFID positioning model. Background Art

[0002] Variable-speed spraying, combining spray technology, sensors, and automatic control, enables precise prescription of pesticides based on crop characteristics during plant protection. This is a core technology for improving pesticide utilization. The key to achieving precise variable-speed spraying is how to accurately interpret established spray prescriptions in real time based on existing positioning conditions. Absolute positioning technologies such as the US Global Positioning System (GPS) and China's BeiDou, widely used in agriculture, are susceptible to signal instability in orchards due to obstruction by tree canopies, making them difficult to meet the requirements of precise spraying.

[0003] Radio Frequency Identification (RFID) is a positioning technology. Wireless signals are affected by multipath during propagation, resulting in large fluctuations in signal strength (RSSI). Direct use of RFID cannot meet the accuracy requirements for orchard positioning. In actual spraying operations, the movement of the sprayer and the complexity of the environment create multi-tag reflections, which can easily lead to misreading of information from non-target canopy tags.

[0004] Current RFID-based spraying methods primarily rely on handheld spraying, which doesn't allow for autonomous sprayer operation. Given the diverse growth patterns of trees and the varying canopy widths at different heights, existing technologies suffer from insufficient positioning accuracy and delayed control system response. This can lead to over- or under-application of pesticides, or even cause the sprayer to become detached from the tree canopy, compromising spray effectiveness and pesticide utilization. Summary of the Invention

[0005] (1) Technical issues to be resolved

[0006] The main purpose of the present invention is to propose a method and system for agricultural precision spraying based on RFID positioning model to solve the above problems.

[0007] (2) Technical solution

[0008] To achieve the above objectives, the present invention provides a method for agricultural precision spraying based on an RFID positioning model, comprising the following steps:

[0009] S1, generate a prescription map with the prescription values ​​of each layer of pre-spray tree planting, including:

[0010] S11, obtaining a three-dimensional point cloud map of the pre-spray area based on a multi-sensor scanning device;

[0011] S12, processing by a point cloud processing algorithm to obtain a point cloud of a single pre-sprayed tree value;

[0012] S13, stratifying the pre-sprayed trees according to the set heights, obtaining information on the volume and canopy width of each layer, and deriving prescription values ​​for each layer of a single tree using a spray unit model;

[0013] S14, number all pre-sprayed trees to form an ordered prescription map code;

[0014] S2, placing RFID tags on the pre-spray trees in the pre-spray area, including: writing the number of the pre-spray tree, prescription information for each layer, and the volume of each layer into the RFID tag; wherein each pre-spray tree is assigned an RFID tag, and the RFID tags are at the same level as the RFID reader;

[0015] S3, builds an RFID-based RSSI positioning model, including:

[0016] S31, constructing an RSSI-distance relationship model;

[0017] S32, RSSI data collection and analysis;

[0018] S33, RSSI data filtering and tag model fitting; the RSSI data obtained in step S32 is subjected to Gaussian filtering and mean filtering, and the RSSI logarithmic ranging model of n tags is fitted using the least squares method;

[0019] S34 uses the loss function to measure the difference between the RSSI value predicted by the model and the actual measured RSSI value, calculates the gradient of the loss function, and optimizes the model parameters to obtain the final positioning model:

[0020]

[0021] in, is the distance between the reader and the tag; is the attenuation factor of the RF signal based on the pre-spray area environment; This is the intensity information obtained by the reader when the distance between the reader and the tag is 1m based on the pre-spray area environment; It is the strength RSSI information;

[0022] S4, the spraying device identifies the pre-sprayed tree. During the spraying operation, the spraying device uses the RFID reader / writer to obtain the tree corresponding to the RFID tag with the smallest distance value as the target tree based on the RFID-based RSSI positioning model, and obtains the information in the RFID tag.

[0023] S5, the spray equipment sprays the pre-spray tree planting layer, according to the information in the RFID tag card of the target tree planting, based on the duty cycle sequence and crown width sequence information of each layer of the target tree planting, when the sensors of each layer corresponding to the spray equipment sense the tree crown, spraying is performed according to the corresponding duty cycle information, and when the sensors of each layer sense that they have left the tree crown, delayed spraying is entered until it stops and moves to the next working position; wherein, the duration of the delayed spray is calculated by the crown width sequence information.

[0024] Preferably, the step S13 specifically includes:

[0025] S131, single pre-spray tree value point cloud layering:

[0026] The single pre-sprayed tree planting point cloud is divided into u layers according to height, and the volume of each layer is , the maximum crown width of each layer is ;

[0027] S132, spray volume calculation:

[0028]

[0029] in, is the target spray volume of the i-th layer; is the spray volume per unit time; is the target canopy width of the i-th layer; is the forward speed of the spray system; is the canopy volume of the i-th layer; The spray volume required per unit canopy volume;

[0030] S133, based on the nozzle flow control relationship, calculate the PWM duty cycle under the prescription information

[0031]

[0032] in, is the spray volume per unit time; is the PWM duty cycle; is the scaling factor of the nozzle flow expression; is the intercept constant;

[0033]

[0034] is the PWM duty cycle of the i-th layer; is the volume of the i-th layer, is the maximum width of the i-th layer; is the scaling factor of the nozzle flow expression; is the intercept constant.

[0035] Preferably, the RSSI-distance relationship model in step S31 includes:

[0036]

[0037] in, is the received signal strength value; is the attenuation factor of the RF signal; is the distance between the RFID reader and the RFID tag; The strength information obtained by the RFID reader when the distance between the RFID reader and the RFID tag is 1m.

[0038] Preferably, step S32 specifically includes: maintaining the RFID reader and the RFID tag at the same horizontal height in the pre-spray area, setting multiple sampling points, and collecting a sufficient number of RSSI values ​​within a GPIO trigger window time at the sampling points to obtain a set of original RSSI sequences:

[0039]

[0040] in, A frame of RSSI strength information set; is the RSSI value sequence of tag n; is the RSSI value of tag n received by the reader at time t within the GPIO trigger window.

[0041] Preferably, the step S33 includes:

[0042] Perform Gaussian filtering on the RSSI value data:

[0043]

[0044] in, is the Gaussian probability density function; is the Gaussian cumulative distribution function; and Represents a set of RFID original strength information The respective means and variances of Indicates intensity information;

[0045] The RSSI values ​​with confidence values ​​within the set interval are retained, and the rest are discarded;

[0046]

[0047] in, is the filtered RSSI strength information set; is the RSSI value of the tag after Gaussian filtering;

[0048] The intensity values ​​of each group after Gaussian filtering are processed by mean filtering to obtain:

[0049]

[0050] in For the collected data set, is the RSSI value sequence of tag n after processing, is the value of tag 1 at 1 meter after being processed by the original data processing algorithm. is the value of tag n at 10 meters after being processed by the original data processing algorithm;

[0051] The n RSSI logarithmic ranging models corresponding to n tags are fitted using the least squares method, as shown in the following formula:

[0052]

[0053] in, It represents the strength information obtained by the reader when the distance between the reader and tag 1 is 1m. Indicates the attenuation factor of the RF signal fitted by tag 1; It represents the intensity information obtained by the reader when the distance between the reader and tag N is 1m. Indicates the attenuation factor of the RF signal fitted by tag N.

[0054] Preferably, the loss function and the gradient of the loss function in step S34 are as shown below:

[0055]

[0056] in, represents the loss function based on the orchard logarithmic ranging model; represents the gradient of the loss function; Indicates the number of RFID tags; Indicates the The actual RSSI strength value measured at each sampling point; The first RSSI strength value of each sampling point is the partial derivative of the loss function with respect to A; Represents the loss function The partial derivative of

[0057] when After reaching the most suitable value, the final positioning model is determined.

[0058] Preferably, the delayed spray time in step S5 is:

[0059]

[0060] in: represents the spray delay time of the i-th layer, represents the area of ​​the spray region of the i-th layer, v represents the moving speed of the spray device, and b is the overlap rate.

[0061] The present invention also provides an agricultural precision spraying system based on an RFID positioning model, comprising a multi-sensor scanning device, a variable spraying device, and a computer system; wherein,

[0062] The multi-sensor scanning device includes an IMU sensor, a 3D laser radar sensor, and a handheld bracket; the IMU sensor is fixed above the 3D laser radar sensor and installed together on the handheld bracket to form a handheld multi-sensor scanning device;

[0063] The variable spray device includes a variable spray execution unit, an information collection unit, an energy supply unit and a spray structure;

[0064] The computer system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for controlling agricultural precision spraying based on the RFID positioning model as described in any one of the above are implemented.

[0065] Preferably, the information collection unit includes: an RFID UHF reader / writer, an RFID tag, an infrared sensor array trigger group and an infrared sensor array control group;

[0066] The infrared sensor array trigger group includes a plurality of infrared sensors arranged vertically at intervals to determine the canopy layer and trigger the RFID reader to determine the target tree planting and obtain prescription information;

[0067] The infrared sensor array control group includes n infrared sensors, where n is the number of set layers, which are used to detect canopy triggering judgment to achieve stratified spraying.

[0068] Preferably, the variable spray execution unit includes a nozzle group, which is provided with n nozzles, and the n nozzles are arranged vertically and spaced apart to spray each set layer, wherein n is the number of set layers;

[0069] The spacing between the nozzles is ;

[0070]

[0071] in, The tree height is the height of the target spraying area; is the spray distance of the spray system, is the nozzle spacing; The spray angle of the nozzle; is the spraying width of a single nozzle; r is the overlap rate of the spraying areas of two adjacent nozzles, ; n is the number of set layers.

[0072] (3) Beneficial effects

[0073] The present invention configures RFID tags for pre-spray trees and realizes accurate identification of target trees and non-target trees through an RSSI positioning model based on RFID. The target trees are layered according to their height, and the prescription values ​​of each layer are calculated based on the spray unit model based on the crown width, and accurate layered spraying is performed based on the prescription values ​​of each layer. When the sensor senses that it has left the crown, it starts delayed spraying, and the time of the delayed spray is calculated based on the crown width information; the edge areas of the fruit tree canopy are usually the most difficult places to spray, because these areas may not be within the direct detection range of the sensor. The delayed stop stage ensures that these edge areas are also fully sprayed by additionally extending the spray time.

[0074] The present invention uses a multi-sensor scanning device to obtain a three-dimensional point cloud map of the pre-spraying area, thereby quickly obtaining relevant information such as the volume and crown width of the pre-sprayed trees.

[0075] The invention of this application adopts an agricultural precision spraying system based on an RFID positioning model, and the variable spraying device is easy to deploy, easy to maintain, and has a fast response speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 A schematic diagram of a flow chart of a method for agricultural precision spraying based on an RFID positioning model provided in this embodiment;

[0077] Figure 2 Schematic diagram of the deployment of RFID tags for pre-spraying trees in the pre-spraying area in a method of agricultural precision spraying based on an RFID positioning model provided in this embodiment

[0078] Figure 3 Schematic diagram of the system operation of agricultural precision spraying based on RFID positioning model provided in this embodiment

[0079] Figure 4 A schematic diagram of the RFID reader-writer interaction process for an agricultural precision spraying system based on an RFID positioning model provided in this embodiment;

[0080] Figure 5A schematic diagram of the spray equipment identification and pre-spraying tree planting process of an agricultural precision spraying system based on an RFID positioning model provided in this embodiment;

[0081] Figure 6 A schematic diagram of the spraying process of a pre-sprayed tree planting layer by a spraying device of an agricultural precision spraying system based on an RFID positioning model provided in this embodiment;

[0082] Figure 7 A schematic diagram of the layered spray spacing of a precision agricultural spray system based on an RFID positioning model provided in this embodiment;

[0083] Figure 8 This is a schematic diagram of a multi-sensor scanning device and a variable spray device of an agricultural precision spraying system based on an RFID positioning model provided in this embodiment.

[0084] [Description of Reference Numerals]

[0085] Figure 8 Attached with marking instructions: 1: IMU sensor; 2: 3D lidar sensor; 3: microcomputer; 4: handheld bracket; 5: PC; 6: six-way relay; 7: medicine box; 8: one-way valve; 9: diaphragm pump; 10: three-way overflow valve; 11: digital pressure transmitter; 12: vortex flowmeter; 13: nozzle group; 14: two-way solenoid valve group; 15: explosion-proof water pipe; 16: RFID ultra-high frequency reader; 17: RFID tag; 18: infrared sensor array trigger group; 19: infrared sensor array control group; 20: STM32 controller; 21: aluminum profile frame; 22: crawler chassis; 23: dual-channel DC brushless motor driver. DETAILED DESCRIPTION

[0086] In order to better explain the present invention and facilitate understanding, the present invention is described in detail below through specific implementation methods in conjunction with the accompanying drawings.

[0087] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0088] In addition, in the present invention, the terms "first," "second," etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly specifying the number of the technical features indicated. Therefore, features specified as "first" or "second" may explicitly or implicitly include at least one of such features. In the description of the present invention, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0089] In the present invention, unless otherwise specified or limited, the terms "connection" and "fixation" should be understood in a broad sense. For example, "fixation" can refer to fixed connection, detachable connection, or integration; "connection" can refer to mechanical connection or electrical connection; it can refer to direct connection or indirect connection through an intermediate medium; it can refer to internal communication between two elements or interaction between two elements, unless otherwise specified. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0090] like Figure 1 As shown, this embodiment provides a method for agricultural precision spraying based on an RFID positioning model, including steps S1-S5.

[0091] S1. Generate a prescription map containing prescription values ​​for each pre-spray tree planting layer. The prescription map is a diagram used to guide the spraying of water, pesticides, fertilizers, or other agricultural chemicals. This map precisely divides the spray area and sets different spray amounts and spray patterns for different farmland areas based on factors such as the pre-spray tree planting volume, thereby achieving precision agriculture management.

[0092] The step S1 specifically includes S11-S14:

[0093] S11, obtaining a three-dimensional point cloud map of the pre-spray area based on a multi-sensor scanning device.

[0094] S12, processing is performed through a point cloud processing algorithm to obtain a single pre-spray tree planting point cloud.

[0095] S13, the pre-spray trees are layered according to the set height. The volume and crown width of each layer are obtained, and the prescription values ​​of each layer of a single tree are obtained through the spray unit model. The location of the layering can be selected according to the actual situation, for example, the entire tree exposed on the surface can be layered or the crown of the tree can be layered. Specifically, in this embodiment, the layering part is the layering of the crown. The number of layers can be selected according to the actual situation, for example, two layers, three layers or even more than three layers. Specifically, in this embodiment, the number of layers is four layers. In reality, there are certain differences in the crown width of trees at different heights. Layering the pre-spray trees can more accurately obtain the spray volume required for the pre-spray trees. The spray unit model comprehensively considers the information of each layer of the pre-spray trees (including volume and crown width), the forward speed and the nozzle flow control relationship, and calculates the target spray volume and the corresponding PWM (pulse width modulation) duty cycle value.

[0096] S14, numbering all pre-sprayed trees to form an ordered prescription map code. The prescription map coding method includes: Figure 2 As shown, the code num for the pre-spray tree prescription unit in the lower left corner of the prescription map is 1. The code increases gradually along the direction of the spray equipment's movement, with the number increasing with each additional pre-spray tree prescription unit. During the coding process, the spray equipment in odd-numbered rows and even-numbered rows moves in opposite directions, i.e., odd-numbered rows are numbered from left to right, while even-numbered rows are numbered from right to left. In other embodiments, the spray equipment in odd-numbered rows and even-numbered rows moves in the same direction, and the coding direction of the odd-numbered and even-numbered rows remains the same.

[0097] S2, arranging RFID tag cards for the pre-spray trees in the pre-spray area, specifically including: writing the number of the pre-spray trees, the prescription information of each layer and the volume of each layer into the RFID tag card; wherein, each pre-spray tree is configured with an RFID tag card, and the horizontal heights of the RFID tag cards are the same. The RFID tag should have the characteristics of being waterproof, UV-resistant, and heat-resistant to adapt to the outdoor environment. The format of writing data into the RFID tag card is: writing the pre-spray tree planting code into the EPC (electronic product code) area of ​​the RFID tag memory, and changing the EPC number of the tag to the pre-spray tree planting code to achieve a one-to-one mapping between the RFID tag and the pre-spray tree planting; the prescription information and width information of each layer are written into the user area of ​​the tag memory according to a predetermined format. The specific example format is: " ”;

[0098] S3, builds an RFID-based RSSI positioning model, including:

[0099] S31, constructing an RSSI-distance relationship model; the RSSI-distance relationship model refers to the relationship equation between the RSSI intensity information obtained by the RFID reader and the distance d in a lightweight application scenario, as shown in the following formula:

[0100]

[0101] in, is the received signal strength value, dBm; is the attenuation factor of the RF signal, reflecting the attenuation rate of the signal during propagation; is the distance between the reader and the tag, m; The intensity information obtained by the reader when the distance between the reader and the tag is 1m, in dBm.

[0102] S32, collecting and analyzing RSSI data: collecting RSSI values ​​of a sufficient number of RFID tags at different sampling points.

[0103] S33, RSSI data filtering and tag model fitting: The RSSI data obtained in step S32 is processed by Gaussian filtering and mean filtering, and the least squares method is used to fit the RSSI logarithmic ranging model of a sufficient number of RFID tags. This reduces noise interference and further improves positioning accuracy.

[0104] S34 uses the loss function to measure the difference between the RSSI value predicted by the model and the actual measured RSSI value, calculates the gradient of the loss function, and optimizes the model parameters to obtain the final positioning model:

[0105]

[0106] in, is the distance between the reader and the tag, m; is the attenuation factor of the RF signal based on the orchard environment, which is a fitting constant; is the intensity information obtained by the reader when the distance between the reader and the tag is 1m in the orchard environment, which is a fitting constant; RSSI information, dBm.

[0107] The RFID-based RSSI positioning model can solve the problem of multi-tag reflection by comparing the tags with the closest distance to identify the target tree.

[0108] S4. The spraying device identifies the pre-spray tree. During the spraying operation, the spraying device uses an RFID reader / writer, based on the RFID-based RSSI positioning model, to identify the tree corresponding to the RFID tag with the smallest distance value as the target tree, and retrieves the information on the RFID tag. In this embodiment, the spraying device also identifies the pre-spray tree by obtaining a trigger read signal, detecting the tree crown via a trigger sensor, and initiating RFID identification.

[0109] S5, the spraying equipment sprays the pre-spray tree planting layer, according to the information in the RFID tag card of the target tree planting, based on the duty cycle sequence and crown width sequence information of each layer of the target tree planting, when the corresponding sensors of each layer set by the spraying equipment sense the tree crown, spraying is performed according to the corresponding duty cycle information. When the sensors of each layer sense that they have left the tree crown, they enter delayed spraying until they stop and move to the next working position; wherein, the duration of the delayed spraying is calculated by the crown width sequence information. The edge areas of the fruit tree canopy are usually the most difficult places to spray, because these areas may not be within the direct detection range of the sensor. The delayed stop stage ensures that these edge areas are also fully sprayed by additionally extending the spraying time. In other embodiments, when the sensors of each layer sense that they have left the tree crown, the spraying stops immediately.

[0110] Specifically, in this embodiment, step S13 specifically includes:

[0111] S131, single pre-spray tree value point cloud layering:

[0112] The single pre-sprayed tree planting point cloud is divided into u layers according to height, and the volume of each layer is , the maximum crown width of each layer is ;

[0113] S132, spray volume calculation:

[0114]

[0115] in, is the target spray volume of the i-th layer; is the spray volume per unit time; is the target canopy width of the i-th layer; is the forward speed of the spray system; is the canopy volume of the i-th layer; The spray volume required per unit canopy volume;

[0116] S133, when the nozzle structure, model and spray pressure are determined, the PWM duty cycle under the prescription information is calculated based on the nozzle flow control relationship

[0117]

[0118] in, is the spray volume per unit time, L / min; is the PWM duty cycle, %; is the proportional factor of the nozzle flow expression, L / min / %; is the intercept constant;

[0119] By combining the spray volume calculation formula with the nozzle flow control relationship, when the pre-spray tree planting information (V and S) is obtained, the corresponding PWM duty cycle can be calculated:

[0120]

[0121] in, is the PWM duty cycle of the i-th layer; is the volume of the i-th layer, is the maximum width of the i-th layer; is the scaling factor of the nozzle flow expression; is the intercept constant;

[0122] In this embodiment, the calculation formula for the spraying amount for a single pre-spray tree is as follows:

[0123]

[0124] in, 、 、 and are the target spray volumes for the first, second, third and fourth layers of a single fruit tree, L; 、 、 and These are the canopy widths of the first, second, third and fourth layers of a single fruit tree, ; 、 、 and are the canopy volumes of the first, second, third and fourth layers of a single fruit tree, ;

[0125] The corresponding PWM duty cycle values ​​under the prescription information are as follows:

[0126]

[0127] in, 、 、 and Corresponding to the PWM duty cycle of the first, second, third and fourth layers in a single fruit tree, %; is the spray volume required per unit canopy volume, L / m3; is the scaling factor of the nozzle flow expression; The intercept constant in the nozzle flow rate expression.

[0128] Preferably, the RSSI-distance relationship model in step S31 includes:

[0129]

[0130] in, is the received signal strength value, dBm; is the attenuation factor of the RF signal, reflecting the attenuation rate of the signal during propagation; is the distance between the RFID reader and the RFID tag, m; The intensity information (dBm) obtained by the RFID reader when the distance between the RFID reader and the RFID tag is 1m.

[0131] Specifically, the step S32 includes: keeping the RFID reader and the RFID tag at the same level in the pre-spray area to reduce signal transmission loss and interference caused by height differences, so that the collected RSSI values ​​are more comparable. Figure 2 As described above, multiple sampling points are set at different locations to achieve a more comprehensive understanding of the distribution of RFID signals in the pre-spray area, which is helpful for subsequent data analysis and processing. Specifically, the locations of the sampling points can be, for example, Figure 2 The position of the reference point of the positioning model is determined; the distance interval between the sampling points can be set according to actual conditions, for example, 0.5m, 1m or 2m, etc. Specifically, in this embodiment, the distance interval between the sampling points is 0.5m; a sufficient number of RSSI values ​​are collected at the sampling points within a GPIO trigger window time, and the sufficient number of RSSI values ​​can be set to a certain number according to actual conditions to obtain a set of original RSSI sequences:

[0132]

[0133] in, A frame of RSSI strength information set; is the RSSI value sequence of tag n; is the RSSI value of tag n received by the reader at time t during the GPIO trigger window. Specifically, in this embodiment, a GPIO trigger window lasts for 1 minute, the RFID reader's transmit power is -33dBm, and the sampling distance range is 0.1 to 10 meters. Sampling within this range ensures that the system can accurately measure and process RSSI values ​​at different distances. By appropriately selecting transmit power and filtering methods, RSSI fluctuations can be reduced and measurement accuracy can be improved, thereby enhancing positioning precision.

[0134] As a preferred embodiment of the present invention, step S33 includes:

[0135] Perform Gaussian filtering on the RSSI value data:

[0136]

[0137] in, is the Gaussian probability density function; is the Gaussian cumulative distribution function; and Represents a set of RFID original strength information The respective means and variances of Indicates intensity information;

[0138] The RSSI values ​​with confidence values ​​within the set interval are retained, and the rest are discarded;

[0139]

[0140] in, is the filtered RSSI strength information set, dBm; is the RSSI value of the tag after Gaussian filtering, dBm; in this embodiment, the interval of the retained confidence value can be set according to the actual situation. Specifically, in this embodiment, the interval of the confidence value is [0.15, 0.83], and unreliable data is filtered to enhance positioning accuracy.

[0141] The intensity values ​​of each group after Gaussian filtering are processed by mean filtering to obtain:

[0142]

[0143] in For the collected data set, is the RSSI value sequence of tag n after processing, is the value of tag 1 at 1 meter after being processed by the original data processing algorithm. is the value of tag n at 10 meters after being processed by the original data processing algorithm.

[0144] The n RSSI logarithmic ranging models corresponding to n tags are fitted using the least squares method, as shown in the following formula:

[0145]

[0146] in, It indicates the strength information obtained by the reader when the distance between the reader and tag 1 is 1m. Indicates the attenuation factor of the RF signal fitted by tag 1; It represents the intensity information obtained by the reader when the distance between the reader and tag N is 1m. Indicates the attenuation factor of the RF signal fitted by tag N.

[0147] Furthermore, in this embodiment, the loss function and the gradient of the loss function in step S34 are as follows:

[0148]

[0149] in, represents the loss function based on the orchard logarithmic ranging model; represents the gradient of the loss function; Indicates the number of RFID tags; Indicates the The actual RSSI strength value measured at each sampling point; The first RSSI strength value of each sampling point is the partial derivative of the loss function with respect to A; Represents the loss function The partial derivative of

[0150] when After reaching the most suitable value, in this embodiment, when When it is closest to 0 (that is, the error is the smallest), the final positioning model is determined:

[0151]

[0152] in, is the distance between the reader and the tag, m; is the attenuation factor of the RF signal based on the orchard environment, which is a fitting constant; is the intensity information obtained by the reader when the distance between the reader and the tag is 1m in the orchard environment, which is a fitting constant; RSSI information, dBm.

[0153] Optionally, the delayed spray time in step S5 is:

[0154]

[0155] in: represents the spray delay time of the i-th layer, represents the spray area of ​​layer i, represents the moving speed of the spray device, and b is the overlap rate. Specifically in this embodiment, the overlap rate of the sprayed area should be controlled between 0.25-0.3, and the overlap rate b is set to 0.3. The extended spray time of each layer is shown as follows:

[0156]

[0157] in, 、 、 and are the spray delay times of the first, second, third and fourth layers, s.

[0158] This embodiment also provides an agricultural precision spraying system based on an RFID positioning model, including a multi-sensor scanning device, a variable spraying device, and a computer system; wherein,

[0159] The multi-sensor scanning device includes an IMU sensor, a 3D laser radar sensor, and a handheld bracket; the IMU sensor is fixed above the 3D laser radar sensor and installed together on the handheld bracket to form a handheld multi-sensor scanning device; it is used to obtain basic information of pre-spray tree planting, perform pre-spray tree planting stratification and obtain prescription values.

[0160] The variable spray device includes a variable spray execution unit, an information collection unit, an energy supply unit and a spray structure; and is used to accurately spray pre-sprayed tree planting.

[0161] The computer system is the computer system part in the operation process of the agricultural precision spraying system based on the RFID positioning model, and is not limited to a single computer entity. The computer system includes a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, the steps of the control method of the agricultural precision spraying based on the RFID positioning model as described in any one of the above items are implemented.

[0162] Preferably, the information collection unit includes: an RFID UHF reader / writer, an RFID tag, an infrared sensor array trigger group and an infrared sensor array control group;

[0163] The infrared sensor array trigger group is arranged relative to the infrared sensor array control group and is arranged in front of the infrared sensor array control group.

[0164] The infrared sensor array trigger group includes multiple infrared sensors, which are arranged vertically at intervals to determine the canopy and trigger the RFID reader to start, determine the target tree planting, and obtain prescription information; the number of the infrared sensors can be set according to actual conditions, for example, two, three, or more than three, and the spacing between each sensor is set according to actual conditions, without specific restrictions, as long as it can ensure that the canopy can be effectively detected.

[0165] The infrared sensor array control group includes n infrared sensors, where n is the number of layers set to detect the canopy layer and trigger judgment to achieve stratified spraying. In this embodiment, n is 4. In other embodiments, the number of layers can be set according to actual conditions.

[0166] Optionally, the variable spray execution unit includes a nozzle group, which is provided with n nozzles, and the n nozzles are arranged vertically and spaced apart to spray each set layer, wherein n is the number of set layers;

[0167] The spacing between the nozzles is :

[0168]

[0169] in, The tree height is the height of the target spraying area; is the spray distance of the spray system; is the nozzle spacing; The spray angle of the nozzle; The spray width of a single nozzle; is the overlap rate of the spray areas of two adjacent nozzles, While ensuring the effectiveness of edge spray, it also ensures the system's drug-saving situation. n is the number of set layers.

[0170] Among them, the above It is obtained by synthesizing the following formula.

[0171]

[0172] in, is the tree height, i.e. the height of the target spraying area, m; is the spray distance of the spray system, m; is the nozzle spacing, m; is the nozzle spray angle, °; h is the spray width of a single nozzle, m; a is the width of the spray overlap area of ​​two adjacent nozzles, m; r is the overlap rate of the spray areas of two adjacent nozzles.

[0173] The sprayer structure preferably includes a frame with a motor-driven mobile device installed beneath it. An operator can remotely control the robot's movement or autonomously navigate the variable-variable sprayer within the pre-spray area. The frame is constructed of aluminum profiles and can be customized based on factors such as the structure, size, and height of the pre-sprayed trees, ensuring the variable-variable sprayer can adapt to various orchard environments and provide optimal operation results. The mobile chassis utilizes a tracked chassis powered by a dual-channel brushless DC motor.

[0174] The following describes a specific operation process to illustrate an agricultural precision spraying system based on an RFID positioning model in this embodiment.

[0175] like Figure 3 - Figure 8 As shown, a system for agricultural precision spraying based on an RFID positioning model includes a multi-sensor scanning device and a variable spraying device;

[0176] like Figure 8As shown, the multi-sensor scanning device primarily consists of an IMU sensor 1, a 3D LiDAR sensor 2, an embedded computer 3, a handheld bracket 4, and a PC client 5. The IMU sensor 1 is fixed above the 3D LiDAR sensor 2 and mounted together on the handheld bracket 4, forming a handheld multi-sensor scanning device. The 3D LiDAR sensor 2 and the IMU sensor 1 communicate with the embedded computer via Ethernet and RS232 serial ports, respectively. The embedded computer receives sensor information and displays the collected point cloud and IMU information in real time on the PC client 5 using a Wi-Fi signal network. Control commands can also be sent to the embedded computer through the command window of the PC client 5.

[0177] The variable-variable spray device primarily consists of a variable-variable spray actuator unit, an information collection unit, an information processing unit, and a spray architecture. The variable-variable spray actuator unit includes a six-way relay 6, a medicine box 7, a one-way valve 8, a diaphragm pump 9, a three-way relief valve 10, a digital pressure transmitter 11, a vortex flowmeter 12, a nozzle assembly 13, a two-way solenoid valve assembly 14, and an explosion-proof water pipe 15. The information collection unit includes an RFID ultra-high frequency reader / writer 16, an RFID tag 17, an infrared sensor array trigger assembly 18, and an infrared sensor array control assembly 19. The information processing unit includes an STM32 controller 20 and a host computer (PC). The spray architecture comprises an aluminum profile frame 21, a tracked chassis 22, and a dual-channel brushless DC motor driver 23.

[0178] Furthermore, the infrared sensor array trigger group 18 comprises three trigger infrared sensors arranged vertically, with each sensor spaced approximately 10 centimeters apart and positioned perpendicular to the ground. This arrangement is designed to cover the wider canopy area in the middle of the fruit tree canopy. The three trigger sensors can most effectively detect key locations in the canopy, ensuring triggering efficiency.

[0179] Furthermore, the infrared sensor array control group 19 is composed of 4 control infrared sensors, the nozzle group 13 is composed of 4 conical nozzles; and the solenoid valve group is composed of 4 solenoid valves.

[0180] like Figure 7 As shown, the fruit trees are divided into 4 areas according to their height. 、 、 and , spraying range Controlled by the corresponding infrared sensor, the corresponding solenoid valve and the corresponding nozzle spray; 、 、 And so on. for Points on one side of the region boundary, for points on the other side of the region boundary; for Points on one side of the region boundary, for points on the other side of the region boundary; for Points on one side of the region boundary, for points on the other side of the region boundary; for Points on one side of the region boundary, for The point on the other side of the region boundary.

[0181] Each spray head, a solenoid valve and a control infrared sensor together form a spraying unit. The spray head is clipped onto the solenoid valve, and the infrared sensor is fixed above the solenoid valve. The four spraying units are independent of each other and arranged vertically with a spacing of the spray head spacing. .

[0182] During system operation, the variable-speed sprayer advances through the orchard at a preset speed. The infrared sensor array triggers group 18 to detect the tree canopy, triggering the RFID UHF reader 16 to collect the EPC and RSSI intensity information from the RFID tags 17 in the tree canopy and transmit it to the information processing unit. After receiving the tag information, the host computer 5 first pre-processes each set of raw intensity information using a filtering algorithm to eliminate singular values ​​and derive a representative RSSI intensity value for each tag in that frame. Each intensity value is then substituted into the RSSI logarithmic ranging positioning model to calculate the distance between each tag and the RFID reader, and the distance values ​​between each tag and the RFID reader are compared. The fruit tree corresponding to the tag with the smallest distance value is identified as the target tree. The system then obtains the EPC information of the target tag and the prescription information stored in the user area, and transmits this information to the STM32 controller 20 via serial communication.

[0183] Specifically, the initialization content of the RFID reader includes defining the RFID reader client object, setting related macro definitions, and declaring the function interface required for the reader operation; by declaring and using four callback functions (i.e., start reading, stop reading, RFID reader GPIO trigger start, and RFID reader GPIO trigger stop), the reading and trigger control events of the RFID reader are realized. Specifically, the start reading callback function is used to start the reading function of the RFID reader, the stop reading callback function is used to terminate the reading operation of the reader, the GPI trigger start callback function is used to respond to the GPIO trigger signal to start the reading operation, and the GPI trigger stop callback function is used to respond to the GPIO trigger signal to terminate the reading operation. It should be noted that, if Figure 4As shown, various control instructions of the RFID reader must be sent and received in sequence, otherwise the RFID reader cannot be controlled correctly.

[0184] When the RFID tag information returned by the callback function is first received, the program creates a structure stack to manage the received information. The received RFID tag 17 information is saved in the host computer's buffer and parsed. The parsed data is pushed into the structure stack to form a complete frame of prescription map interpretation information. The prescription map interpretation information frame is dynamically managed through the pointer (Ptr). In order to ensure that a frame of prescription map interpretation information contains at least 30 intensity information (including at least 10 target canopy information), a GPIO trigger window time is set to 400ms.

[0185] Optionally, the specific steps for interpreting information for a frame of prescription image are:

[0186] Prescription interpretation information call: call the structure stack through the Ptr pointer to extract all EPC values ​​and their corresponding RSSI strength information in the prescription map interpretation information of the frame; based on the extracted EPC information, classify all RSSI data in the frame interpretation information to form the original strength information group of each tag;

[0187] Each set of raw intensity information is preprocessed using a Gaussian filter and a mean filter to obtain the RSSI intensity value represented by each tag. These intensity values ​​are then substituted into the aforementioned RSSI logarithmic ranging positioning model to calculate the distance between each tag and the RFID reader. The distance values ​​between each tag and the RFID reader are compared. The fruit tree corresponding to the tag with the smallest distance value is identified as the target tree, and the EPC information for that tag is obtained.

[0188] Based on the EPC information of the target tag, quickly extract the information of the user area in the tag memory and send it to the lower computer in the corresponding format;

[0189] Use the pointer (Ptr) to clear all prescription map interpretation information in the structure stack and prepare for the next trigger window cycle;

[0190] Before the spray execution unit can perform variable-speed spraying, it must first activate the diaphragm pump 9 to draw liquid medicine from the medicine tank 7. The diaphragm pump 9's water pressure regulation relies on the reading of a digital pressure transmitter 11. The water pressure in the pipeline between the diaphragm pump 9 and the two-way solenoid valve assembly 14 is maintained through the control of a check valve 8, ensuring that the required pressure for the spraying operation is met. Furthermore, explosion-proof water pipes 15 connect the various components, ensuring stable transmission of high-pressure water flow, preventing safety incidents caused by pipe rupture or leakage, and ensuring stable fluid pressure during the spraying process, ensuring optimal spraying results.

[0191] When the STM32 controller 20 receives the information, it divides the information into a duty cycle sequence and a crown width sequence. The duty cycle sequence is used to control the spray flow rate; the crown width sequence is used to calculate the delay sequence, thereby extending the spray time. When each sensor in the infrared sensor array control group 19 detects the crown of the target fruit tree, the system generates a signal to start spraying and enters the precision spraying stage; the STM32 controller 20 determines which infrared sensor the signal comes from, activates the relay 6, and transmits the duty cycle signal to the two-way solenoid valve in the corresponding area; the solenoid valve controls the opening and closing according to the received duty cycle signal, thereby adjusting the flow of the liquid medicine and starting the spray; and atomizes through the nozzle group 13 to form fine spray droplets, which are accurately sprayed to the target canopy; when each sensor of the infrared sensor array control group 19 leaves the corresponding regional canopy, a signal to extend the stop spraying is generated, and the system enters the delayed stop stage; the STM32 determines the source of the detection signal and transmits the delay information to the preset timer, and the system continues to spray until the timing ends; the spraying stops, and the system's spray equipment sprays the pre-sprayed tree planting layer. The process diagram is as shown below. Figure 6 .

[0192] After the sprayer completes the spraying of one target fruit tree, it continues to move forward in the preset direction. The system waits for the signal from the infrared sensor array trigger group 18 to start the spraying operation of the next target fruit tree.

[0193] The above are merely specific application examples of the present invention and do not constitute any limitation on the scope of protection of the present invention. In addition to the above embodiments, the present invention may also have other implementations. Any technical solution formed by equivalent replacement or equivalent transformation falls within the scope of protection claimed by the present invention.

Claims

1. A method for agricultural precision spraying based on RFID positioning model, characterized in that: Including steps: S1, generate a prescription map with the prescription values ​​of each layer of pre-spray tree planting, including: S11, obtaining a three-dimensional point cloud map of the pre-spray area based on a multi-sensor scanning device; S12, processing the point cloud using a point cloud processing algorithm to obtain a single pre-sprayed tree planting point cloud; S13, stratifying the pre-sprayed trees according to the set heights, obtaining information on the volume and canopy width of each layer, and deriving prescription values ​​for each layer of a single tree using a spray unit model; S14, number all pre-sprayed trees to form an ordered prescription map code; S2, placing RFID tags on the pre-spray trees in the pre-spray area, including: writing the number of the pre-spray tree, prescription information for each layer, and the volume of each layer into the RFID tags; wherein each pre-spray tree is assigned one RFID tag, and the RFID tags are at the same height; S3, builds an RFID-based RSSI positioning model, including: S31, constructing an RSSI-distance relationship model; S32, RSSI data collection and analysis; S33, RSSI data filtering and tag model fitting; the RSSI data obtained in step S32 is subjected to Gaussian filtering and mean filtering, and the RSSI logarithmic ranging model of n tags is fitted using the least squares method; S34 uses the loss function to measure the difference between the RSSI value predicted by the model and the actual measured RSSI value, calculates the gradient of the loss function, and optimizes the model parameters to obtain the final positioning model: in, is the distance between the reader and the tag; is the attenuation factor of the RF signal based on the pre-spray area environment; This is the intensity information obtained by the reader when the distance between the reader and the tag is 1m based on the pre-spray area environment; It is the strength RSSI information; S4, the spraying device identifies the pre-sprayed tree. During the spraying operation, the spraying device uses the RFID reader / writer to obtain the tree corresponding to the RFID tag with the smallest distance value as the target tree based on the RFID-based RSSI positioning model, and obtains the information in the RFID tag. S5, the spray equipment sprays the pre-spray tree planting layer; according to the information in the RFID tag card of the target tree planting, based on the duty cycle sequence and crown width sequence information of each layer of the target tree planting, when the sensors of each layer corresponding to the spray equipment sense the tree crown, spraying is performed according to the corresponding duty cycle information. When the sensors of each layer sense that they have left the tree crown, they enter delayed spraying until they stop and move to the next working position; wherein, the duration of the delayed spraying is calculated by the crown width sequence information.

2. The method for agricultural precision spraying based on RFID positioning model according to claim 1, characterized in that: The step S13 specifically includes: S131, single pre-spray tree value point cloud layering: The single pre-sprayed tree planting point cloud is divided into u layers according to height, and the volume of each layer is , the maximum crown width of each layer is ; S132, spray volume calculation: in, is the target spray volume of the i-th layer; is the spray volume per unit time; is the target canopy width of the i-th layer; is the forward speed of the spray system; is the canopy volume of the i-th layer; The spray volume required per unit canopy volume; S133, based on the nozzle flow control relationship, calculate the PWM duty cycle under the prescription information in, is the spray volume per unit time; is the PWM duty cycle; is the scaling factor of the nozzle flow expression; is the intercept constant; in, is the PWM duty cycle of the i-th layer; is the volume of the i-th layer, is the maximum width of the i-th layer; is the scaling factor of the nozzle flow expression; is the intercept constant.

3. The method for agricultural precision spraying based on RFID positioning model according to claim 1, characterized in that: The RSSI-distance relationship model in step S31 includes: in, is the received signal strength value; is the attenuation factor of the RF signal; is the distance between the RFID reader and the RFID tag; The strength information obtained by the RFID reader when the distance between the RFID reader and the RFID tag is 1m.

4. The method for agricultural precision spraying based on RFID positioning model according to claim 3, characterized in that: The step S32 specifically includes: keeping the RFID reader and the RFID tag at the same level in the pre-spray area, setting multiple sampling points, collecting a sufficient number of RSSI values ​​within a GPIO trigger window time at the sampling points, and obtaining a set of original RSSI sequences: in, A frame of RSSI strength information set; is the RSSI value sequence of tag n; is the RSSI value of tag n received by the reader at time t within the GPIO trigger window.

5. The method for agricultural precision spraying based on RFID positioning model according to claim 4, characterized in that: The step S33 includes: Perform Gaussian filtering on the RSSI value data: in, is the Gaussian probability density function; is the Gaussian cumulative distribution function; and Represents a set of RFID original strength information The respective means and variances of Indicates intensity information; The RSSI values ​​with confidence values ​​within the set interval are retained, and the rest are discarded; in, is the filtered RSSI strength information set; is the RSSI value of the tag after Gaussian filtering; The intensity values ​​of each group after Gaussian filtering are processed by mean filtering to obtain: in For the collected data set, is the RSSI value sequence of tag n after processing, is the value of tag 1 at 1 meter after being processed by the original data processing algorithm. is the value of tag n at 10 meters after being processed by the original data processing algorithm; The n RSSI logarithmic ranging models corresponding to n tags are fitted using the least squares method, as shown in the following formula: in, It indicates the strength information obtained by the reader when the distance between the reader and tag 1 is 1m. Indicates the attenuation factor of the RF signal fitted by tag 1; It represents the strength information obtained by the reader when the distance between the reader and tag N is 1m. Indicates the attenuation factor of the RF signal fitted by tag N.

6. The agricultural precision spraying method based on RFID positioning model according to claim 5, characterized in that: The loss function and the gradient of the loss function in step S34 are shown in the following formula: in, represents the loss function based on the orchard logarithmic ranging model; represents the gradient of the loss function; Indicates the number of RFID tags; Indicates the The RSSI strength value actually measured at each sampling point; The first RSSI strength value of each sampling point is the partial derivative of the loss function with respect to A; Represents the loss function The partial derivative of when After reaching the most suitable value, the final positioning model is determined.

7. The method for agricultural precision spraying based on RFID positioning model according to claim 1, characterized in that: The delayed spraying time in step S5 is: in: represents the spray delay time of the i-th layer, represents the spray area of ​​the i-th layer, Indicates the speed of the spray device, is the overlap rate.

8. An agricultural precision spraying system based on RFID positioning model, characterized in that: It includes a multi-sensor scanning device, a variable spray device and a computer system; wherein, The multi-sensor scanning device includes an IMU sensor, a 3D laser radar sensor, and a handheld bracket; the IMU sensor is fixed above the 3D laser radar sensor and installed together on the handheld bracket to form a handheld multi-sensor scanning device; The variable spray device includes a variable spray execution unit, an information collection unit, an energy supply unit and a spray structure; The computer system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for agricultural precision spraying based on the RFID positioning model as described in any one of claims 1 to 7 are implemented.

9. The agricultural precision spraying system based on RFID positioning model according to claim 8, characterized in that: The information collection unit includes: an RFID UHF reader / writer, an RFID tag, an infrared sensor array trigger group and an infrared sensor array control group; The infrared sensor array trigger group includes a plurality of infrared sensors arranged vertically at intervals to determine the canopy layer and trigger the RFID reader to determine the target tree planting and obtain prescription information; The infrared sensor array control group includes n infrared sensors, where n is the number of set layers, which are used to detect canopy triggering judgment to achieve stratified spraying.

10. The agricultural precision spraying system based on RFID positioning model according to claim 9, characterized in that: The variable spray execution unit includes a nozzle group, which is provided with n nozzles, and the n nozzles are arranged vertically at intervals to spray each set layer, wherein n is the number of set layers; The spacing between the nozzles is d ; in, The tree height is the height of the target spraying area; is the spray distance of the spray system, is the nozzle spacing; The spray angle of the nozzle; is the spraying width of a single nozzle; r is the overlap rate of the spraying areas of two adjacent nozzles, ; n To set the number of layers.

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