An adjustable spray width unmanned aerial vehicle variable spraying system and method

Abstract

The present invention discloses an adjustable spray width unmanned aerial vehicle variable spraying system and method. The system includes an unmanned aerial vehicle, a spraying execution mechanism, and a spraying control module; the spraying control module includes an on-board control module and a remote control module; the on-board control module includes an information collector and an on-board processor; agricultural information data of crops obtained through the information collection module is processed to obtain a pest and disease distribution map, the theoretical recommended grid size is calculated through the pest and disease distribution map, an ideal grid prescription map is obtained through the theoretical recommended grid size, and the pest and disease distribution map and the ideal grid prescription map are sent to the remote control module; a variable grid prescription map is determined according to the pest and disease distribution map and the ideal grid prescription map and sent back to the on-board control module, and a time signal, a displacement signal, and a prescription value are generated and transmitted to the spraying execution mechanism. The present invention can adjust the size of the spray width, adapt to spraying with different scale fields and grid size divisions, and adapt to more complex situations.

Description

Technical Field

[0001] The present invention relates to an unmanned aerial vehicle (UAV) variable spraying device and method, and particularly to a UAV variable spraying system and method with adjustable spraying width. Background Art

[0002] Existing variable spraying is carried out according to agricultural information, images, and prescription maps determined by dividing grid sizes. There are good researches and achievements in both changing spraying variables and building variable spraying systems and processing variable spraying information. However, less consideration is given to the selection of grid sizes in grid size division, and it is relatively single. At the same time, less consideration is given to the influence of the canopy volume and pore distribution of typical hot area crops on precise spraying. It is difficult to adjust the size of the spraying width according to the relevant information of the crop canopy, which may cause over-spraying in some areas or under-spraying in some areas, and it is difficult to be used in complex situations. Summary of the Invention

[0003] The purpose of the present invention is to overcome the above-mentioned existing problems, and provide a UAV variable spraying system and method with adjustable spraying width. The UAV variable spraying system and method adjust the size of the spraying width according to the relevant information of the crop obtained by on-site detection, can adapt to spraying with different scale fields and grid size divisions, and can also spray on the changing grids of the same spraying field, and can adapt to more complex situations.

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

[0005] A UAV variable spraying system with adjustable spraying width includes a UAV, a spraying execution mechanism, and a spraying control module arranged on the UAV;

[0006] The spraying execution mechanism includes at least two groups of spraying components and a lateral driving mechanism for adjusting the lateral distance between the spraying components;

[0007] The spraying control module includes an on-board control module and a remote control module; the on-board control module is connected to the remote control module through a wireless network. The on-board control module includes an information collector and an on-board processor; the information collector includes a visual sensor for acquiring crop image information;

[0008] The on-board processor is used to obtain a pest and disease distribution map with a pre-established model for the information acquired by the information collection module, calculate the theoretically recommended grid size through the pest and disease distribution map according to the spatial statistics algorithm, obtain an ideal grid prescription map through the theoretically recommended grid size, and send the pest and disease distribution map and the ideal grid prescription map to the remote control module; when the on-board processor receives a changing grid prescription map, it generates a time signal, a displacement signal, and a prescription value according to the changing grid prescription map and transmits them to the spraying execution mechanism;

[0009] The remote control module is used for allowing the staff to determine a variable grid prescription map according to the pest distribution map and the ideal grid prescription map, and sending the variable grid prescription map back to the airborne processor of the airborne control module.

[0010] In a preferred embodiment of the present invention, the information collection module further includes a GNSS / INS positioning module for obtaining the geographical information of the crops and a three-dimensional lidar for obtaining the three-dimensional point cloud information of the crops; by combining the image information obtained by the vision sensor and the three-dimensional point cloud information obtained by the three-dimensional lidar, the canopy volume and pore distribution of the crops are obtained.

[0011] In a preferred embodiment of the present invention, a memory is provided on the airborne control module or the remote control module, and the memory is used for storing the data obtained by the information collector, the ideal grid prescription map, the variable grid prescription map, the data of the flow sensor and the data of the displacement sensor. In this way, on the one hand, it can be used for multi-scale and multi-angle evaluation after spraying, and on the other hand, if an optimized spraying algorithm is installed in the computer, it can be used for optimizing the next spraying.

[0012] In a preferred embodiment of the present invention, the spraying assembly includes a spray pipe and a spray head, and the spray head is fixedly connected to the spray pipe; the spray pipe is communicated with the medicine tank, and the spray pipe is fixedly connected to the driving end of the transverse driving mechanism.

[0013] Furthermore, the spraying assembly further includes an electromagnetic valve for controlling the spraying amount of the spray head, and the electromagnetic valve is arranged on the spray pipe; the electromagnetic valve is electrically connected to the airborne processor. In this way, the electromagnetic valve is controlled by the airborne processor. The adjustment range of the electromagnetic valve should not be too large, and the spraying width will be affected by the spraying pressure. However, within a certain range of change of the spraying pressure, the spraying width of the spray head will not change.

[0014] Furthermore, the spraying assembly further includes a flow sensor for monitoring the spraying amount of the spray head, and the flow sensor is arranged on the spray pipe; the flow sensor is electrically connected to the airborne processor. In this way, the flow is monitored by the flow sensor and the data is transmitted to the airborne processor for recording, and the electromagnetic valve can also be feedback-adjusted to adjust the spraying amount.

[0015] In a preferred embodiment of the present invention, the transverse driving mechanism is arranged on the mounting frame, and the transverse driving mechanism includes a transverse moving frame, a transverse driving motor and a transverse transmission assembly; the transverse transmission assembly includes a lead screw and a lead screw nut; the lead screw nut is fixedly connected to the transverse moving frame;

[0016] The spraying assembly is arranged on the transverse moving frame.

[0017] Further, a horizontally arranged guiding groove is provided on the mounting frame; a guiding portion cooperating with the guiding groove is provided on the horizontally moving frame.

[0018] Further, there are two horizontally moving frames; the horizontal driving mechanism and the spraying assembly are both provided with two groups; the two groups of spraying assemblies are respectively arranged on the two horizontally moving frames;

[0019] Each group of spraying assemblies includes at least two spraying assemblies, and the spraying assemblies in the same group are arranged on the same horizontally moving frame.

[0020] Further, the horizontal driving mechanism further includes a displacement sensor for detecting the moving distance of the spraying assembly, and the displacement sensor is electrically connected to the on-board processor.

[0021] Further, the horizontally moving frame includes a fixed moving member and a moving swing member, and the fixed moving member is connected to the driving end of the horizontal driving mechanism; the moving swing member is rotatably connected to the lower end of the fixed moving member;

[0022] The spraying execution mechanism further includes a swing driving mechanism for driving the spraying assembly to swing. The swing driving mechanism includes a swing driving motor. The housing of the swing driving motor is fixed on the fixed moving member, and the output shaft of the swing driving motor is fixedly connected to the moving swing member; the output shaft of the swing driving motor coincides with the rotation center of the moving swing member. Through the above structure, the spraying assembly can be driven to swing, so as to change the spraying angle of the nozzle, and the fixed-point spraying from the side of the tree can be realized.

[0023] A method for variable spraying of an unmanned aerial vehicle with adjustable spraying width includes the following steps:

[0024] Collect data of crops in the operation area by an information collector carried by the unmanned aerial vehicle; the collected data includes the distribution of pests and diseases;

[0025] Process the collected data by the on-board processor to obtain a pest and disease distribution map; combine the spatial statistics algorithm, calculate the theoretical recommended grid according to the pest and disease distribution map, and then generate an ideal grid prescription map from the theoretical recommended grid; send the pest and disease distribution map and the ideal grid prescription map to the remote control module;

[0026] Determine the variable grid prescription map by the staff on the remote control module in combination with the pest and disease distribution map and the ideal grid prescription map, and send the variable grid prescription map to the on-board processor of the on-board control module;

[0027] Obtain the spraying width and spraying amount of each grid according to the variable grid prescription map by the on-board processor, and generate corresponding working instructions to send to the spraying execution mechanism;

[0028] During the spraying operation, the unmanned aerial vehicle sails along a set path while executing corresponding work instructions. The spray width of the spraying component is adjusted in real time through a lateral drive mechanism to adapt to the amplitudes of different grids. The spray volume of its own nozzles is adjusted through the spraying component to perform differential spraying on different grids until all spraying operations are completed.

[0029] A preferred embodiment of the present invention, wherein the collected data further includes the canopy volume and pore distribution information of the crops.

[0030] Furthermore, the canopy volume is obtained by the following method:

[0031] Visible light images are obtained through an information collector, orthophotos are obtained by processing the visible light images, and dense point clouds are generated; the point cloud data is denoised and ground point classification is performed;

[0032] A digital elevation model and a digital surface model are generated from the ground points. The total pixel area of the canopy height model is calculated by the formula CHM = DSM - DEM. This total pixel area is the canopy area of the corresponding crop. The canopy volume of the crop is obtained by substituting the canopy area into the following formula:

[0033]

[0034] wherein, V is the canopy volume of the crop; Hi is the pixel height intensity value in the pixel CHM; GSD is the ground sampling distance, that is, the CHM resolution of 0.05 m.

[0035] A preferred embodiment of the present invention, wherein, in the case where the spraying amplitude remains unchanged, only considering the pore distribution and not considering the canopy volume, the pore compensation spray volume of a single nozzle is:

[0036] q1 = -αρq;

[0037] wherein, the pore compensation spray volume of a single nozzle is q1, α is the pore compensation coefficient, and the value range is 0 < α < 1; the spray volume of a single nozzle in the ideal grid prescription map is q, and the internal porosity of the grid is ρ.

[0038] A preferred embodiment of the present invention, wherein, in the case where the spraying amplitude remains unchanged, only considering the canopy volume and not considering the pore distribution, the canopy volume compensation spray volume of a single nozzle is:

[0039]

[0040] wherein, the canopy volume compensation spray volume of a single nozzle is q2, β is the canopy volume compensation coefficient, and the value range is 0 < β < 1; the spray volume of a single nozzle in the ideal grid prescription map is q, V is the canopy volume within the grid, and V avg is the average value of the canopy volumes of all grids.

[0041] A preferred embodiment of the present invention, wherein the spraying amount of a single nozzle is calculated by the following formula model:

[0042]

[0043] The original spraying width is L, and the changed spraying width is L′; the spraying amount of a single nozzle in the ideal grid prescription map is q, and the spraying amount of a single nozzle in the changed grid prescription map is q res ; the pore compensation spraying amount in the ideal grid prescription map is q1, and the pore compensation spraying amount in the changed grid prescription map is q′1; the volume compensation spraying amount in the ideal grid prescription map is q2, and the canopy volume compensation spraying amount in the changed grid prescription map is q′2; the porosity in the ideal grid prescription map is ρ, and the porosity in the changed grid prescription map is ρ′; the canopy volume in the ideal grid prescription map is V, and the canopy volume in the changed grid prescription map is V′, where V avg is the average value of all canopy volumes or a reference value set artificially; α is the pore compensation coefficient, and its value range is 0 < α < 1; β is the canopy volume compensation coefficient, and its value range is 0 < β < 1; both α and β are optimized and adjusted according to the spraying effect.

[0044] The present invention has the following beneficial effects compared with the prior art:

[0045] The present invention adjusts the spraying width and spraying amount according to the pest and disease distribution map of the crops obtained by implementation detection, can adapt to spraying with different scales of fields and grid size divisions, and can simultaneously spray on the changed grids of the same spraying field, and can adapt to more complex situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a three-dimensional structural schematic diagram of the spraying execution mechanism of the present invention.

[0047] Figure 2 is a side view of the spraying execution mechanism of the present invention.

[0048] Figure 3 is a working flow chart of the variable spraying system of the unmanned aerial vehicle with adjustable spraying width of the present invention.

[0049] Figure 4 are Digital Surface Model (DSM), Digital Elevation Model (DEM), and Canopy Height Model (CHM) images.

[0050] Figure 5 is a relationship diagram of the canopy volume obtained by the unmanned aerial vehicle of the present invention and the canopy volume obtained by the ground lidar.

[0051] Figure 6 Schematic diagram of the ideal grid size prescription map and flight path of the variable spraying method of the drone with adjustable spraying width according to the present invention.

[0052] Figure 7 Schematic diagram of the variable grid size prescription map and flight path of the variable spraying method of the drone with adjustable spraying width according to the present invention. Detailed implementation manners

[0053] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described below in conjunction with embodiments and drawings, but the implementation manners of the present invention are not limited thereto.

[0054] The variable spraying system of the drone with adjustable spraying width in this embodiment includes a drone (not shown in the figure), a spraying execution mechanism and a spraying control module provided on the drone; the spraying execution mechanism includes at least two groups of spraying components and a lateral driving mechanism for adjusting the lateral distance between the spraying components.

[0055] The spraying control module includes an on-board control module and a remote control module; the on-board control module is connected to the remote control module through a wireless network, and the on-board control module includes an information collector and an on-board processor; the information collector includes a GNSS / INS positioning module for obtaining geographical information of crops, a vision sensor for obtaining crop image information, and a three-dimensional lidar for obtaining three-dimensional point cloud information of crops; the on-board processor is used to obtain a pest and disease distribution map with a pre-established model for the information obtained by the information collection module, calculate the theoretical recommended grid size through the pest and disease distribution map according to the spatial statistics algorithm, obtain an ideal grid prescription map through the theoretical recommended grid size, and send the pest and disease distribution map and the ideal grid prescription map to the remote control module; when the on-board processor receives the variable grid prescription map, it generates a time signal, a displacement signal and a prescription value according to the variable grid prescription map and transmits them to the spraying execution mechanism, and the prescription value refers to the spraying amount of each grid corresponding to the prescription map.

[0056] The remote control module is used for the staff to determine the variable grid prescription map according to the pest and disease distribution map and the ideal grid prescription map, and send the variable grid prescription map back to the on-board processor of the on-board control module. Specifically, the remote control module can adopt a mobile device such as a tablet computer.

[0057] A memory is provided on the on-board control module or the remote control module, and the memory is used to store the data obtained by the information collector, the ideal grid prescription map, the variable grid prescription map, the data of the flow sensor and the data of the displacement sensor. In this way, on the one hand, it can be used for multi-scale and multi-angle evaluation after spraying, and on the other hand, if an optimized spraying algorithm is installed in the computer, it can be used to optimize the next spraying.

[0058] See Figure 1-2 , the spraying assembly includes a spray pipe 1 and a spray head 2, and the spray head 2 is fixedly connected to the spray pipe 1; the spray pipe 1 is communicated with a medicine box (not shown in the figure), and the spray pipe 1 is fixedly connected to the driving end of the transverse driving mechanism.

[0059] See Figure 1-2 , the spraying assembly further includes an electromagnetic valve 3 for controlling the spraying amount of the spray head 2, and the electromagnetic valve 3 is arranged on the spray pipe 1; the electromagnetic valve 3 is electrically connected to the airborne processor. In this way, the electromagnetic valve 3 is controlled by the airborne processor. The adjustment range of the electromagnetic valve 3 should not be too large. The spraying width will be affected by the spraying pressure, but at the same time, the spraying width of the spray head 2 will not change when the spraying pressure changes within a certain range.

[0060] See Figure 1-2 , the spraying assembly further includes a flow sensor 4 for monitoring the spraying amount of the spray head 2, and the flow sensor 4 is arranged on the spray pipe 1; the flow sensor 4 is electrically connected to the airborne processor. In this way, the flow rate is monitored by the flow sensor 4 and the data is transmitted to the airborne processor for recording, and the electromagnetic valve 3 can also be feedback-regulated to adjust the spraying amount.

[0061] See Figure 1-2 , the transverse driving mechanism is arranged on the mounting frame 5, and the transverse driving mechanism includes a transverse moving frame, a transverse driving motor 6 and a transverse transmission assembly; the transverse transmission assembly includes a lead screw 7 and a lead screw nut 8; the lead screw nut 8 is fixedly connected to the transverse moving frame; the spraying assembly is arranged on the transverse moving frame.

[0062] Further, a horizontally arranged guide groove is provided on the mounting frame 5; a guiding portion cooperating with the guide groove is provided on the transverse moving frame.

[0063] Further, there are two transverse moving frames; there are two sets of the transverse driving mechanism and the spraying assembly; the two sets of spraying assemblies are respectively arranged on the two transverse moving frames; each set of spraying assemblies includes three spraying assemblies, and the spraying assemblies in the same set are arranged on the same transverse moving frame.

[0064] See Figure 1-2 , the transverse driving mechanism further includes a displacement sensor 9 for detecting the moving distance of the spraying assembly, and the displacement sensor 9 is electrically connected to the airborne processor. Through the displacement sensor 9 and the flow sensor 4, not only can feedback regulation be used to achieve more accurate spraying, but also the real spraying data can be recorded, which is convenient for subsequent evaluation and optimization.

[0065] See Figure 1-2The lateral movable frame includes a fixed movable part 10 and a movable swinging part 11, wherein the fixed movable part 10 is connected to the driving end of the lateral driving mechanism; the movable swinging part 11 is rotatably connected to the lower end of the fixed movable part 10; the spraying actuator also includes a swinging driving mechanism for driving the spraying assembly to swing, and the swinging driving mechanism includes a swinging driving motor 12, the housing of the swinging driving motor 12 is fixed on the fixed movable part 10, and the output shaft of the swinging driving motor 12 is fixedly connected to the movable swinging part 11; the output shaft of the swinging driving motor 12 coincides with the rotation center of the movable swinging part 11. Through the above structure, the spraying assembly can be driven to swing, thereby changing the spraying angle of the spray head 2, and spraying at a fixed point from the side of the tree can be achieved.

[0066] See also Figures 3-7 The variable spraying method of the drone with adjustable spray width of this embodiment comprises the following steps:

[0067] Step 1: Use an information collector mounted on a drone to collect agricultural information data on crops in the operation area; the collected agricultural information data includes the distribution of pests and diseases, crop canopy volume and pore distribution information.

[0068] Step 2: Process the distribution of pests and diseases through the onboard processor to obtain a pest and disease distribution map; combine the image information obtained by the visual sensor and the three-dimensional point cloud information obtained by the three-dimensional lidar to obtain the canopy volume and pore distribution of the crop.

[0069] Further, the canopy volume is obtained by the following method:

[0070] (1) Obtain visible light images through visual sensors, process the visible light images to obtain orthophotos, and generate dense point clouds.

[0071] (2) The point cloud data is denoised and the ground points are classified. The digital elevation model (DEM) and digital surface model (DSM) are generated from the ground points. The canopy height model (CHM) is calculated and output using the following formula. The CHM resolution is 0.05 m, and the height information contained in the CHM is not affected by background color, shadows, or infected plants. Figure 4 From left to right: DSM, DEM, and CHM images.

[0072] CHM = DSM-DEM;

[0073] (3) Extract canopy information by separating the pixel intensities of individual trees. Select the target tree to be measured by choosing the ROI. Consider the pixel with the maximum intensity in the Region of Interest (ROI) as the height of the specific tree, and consider the total pixel area of the ROI as the canopy area of the specific tree.

[0074] (4) Multiply the height of all pixels in a single ROI by the ground sampling distance and sum them to calculate the total intensity height of all pixels within the ROI, so as to measure the canopy volume. The canopy volume of the target tree is calculated by summing the areas obtained by multiplying the total height of all pixel intensities by the square of the ground sampling distance (Ground Sample Distance, GSD). The calculation formula is:

[0075]

[0076] Where V is the crop canopy volume; Hi is the pixel height intensity value in the pixel CHM; GSD is the ground sampling distance, which is the CHM resolution of 0.05 m.

[0077] Step 3: Combine the spatial statistics algorithm, calculate the theoretical recommended grid based on the pest and disease distribution map, and then generate an ideal grid prescription map from the theoretical recommended grid; send the pest and disease distribution map and the ideal grid prescription map to the remote control module;

[0078] Step 4: Determine the variable grid prescription map by the staff on the remote control module in combination with the pest and disease distribution map and the ideal grid prescription map, and send the variable grid prescription map to the airborne processor of the airborne control module.

[0079] Agricultural information includes crop canopy volume, pore distribution, and pest and disease information distribution. Pest and disease information directly affects the change in the decision-making spraying volume, and the canopy volume and pore distribution affect the change in the decision-making spraying volume compensation.

[0080] The fixed grid size divides most of the agricultural information well, with small differences within the grid cells and large differences between the grid cells. However, there are still some cases where some agricultural information will be lost when generating the prescription map after grid division, resulting in a mismatch between the spraying prescription in some areas and the spraying volume required by the agricultural information.

[0081] See Figure 7 For Figure 6The change grid diagram of 3a x 3b at the bottom left corner. There are some problems with the theoretically recommended grid size calculated by the algorithm. The fixed grid size and raster aggregation method pursue overall comprehensive spraying for the entire crop field. However, when refined to each grid, there may be a problem of mismatched spraying levels in some areas of a single grid. For example, after dividing the fixed grid size, a certain grid is designated as spraying level M, but based on the agricultural information data of the adjacent areas of this grid and other grids, spraying level N should be adopted. At this time, if spraying is carried out according to the prescription map divided by the fixed grid size, the spraying effect may be poor or pesticides may be wasted. If M < N, the spraying effect in this area will be poor due to insufficient pesticide spraying. If M > N, the spraying amount exceeding the original spraying level will result in wasted pesticides. Wasted pesticides only refer to a single grid, and the impact on the variable pesticide spraying amount of the entire crop field may be small and can basically be ignored. However, the poor spraying effect caused by insufficient spraying amount may not effectively target pests and diseases, resulting in adverse effects such as crop yield reduction. Therefore, the situation of M < N should be dealt with. At the same time, in order to maintain the spraying path of the original ideal grid prescription map, the spraying amplitude and amount can be appropriately changed at appropriate time nodes. For example Figure 7 Regarding the adjustment of the fixed grid size, there are two cases. The first case is that the grid size perpendicular to the flight direction of the drone changes. At this time, it is necessary to increase the spraying amplitude when the drone flies to node 1, restore the original spraying amplitude when the drone flies to node 2, decrease the spraying amplitude when the drone flies to node 3, and restore the original spraying amplitude when the drone flies to node 4. The second case is that the grid size parallel to the flight direction of the drone changes. At this time, it is necessary to change the moment of spraying level change. The original spraying amount was to be changed at time t1, and now it is adjusted to time t2 (in the illustrated case, t2 > t1).

[0082] Step Five: Through the on-board processor, obtain the spraying amplitude and spraying amount of each grid according to the change grid prescription map, and generate corresponding working instructions to send to the spraying execution mechanism.

[0083] Step Six: During the spraying operation, the drone sails along the set path, and at the same time executes the corresponding working instructions. The spraying amplitude of the spraying component is adjusted in real time through the lateral drive mechanism to adapt to the amplitudes of different grids; the spraying amount of the nozzle 2 of the spraying component itself is adjusted to implement differential spraying for different grids until all spraying operations are completed.

[0084] Furthermore, in the case where the spraying amplitude remains unchanged, only considering the pore distribution and not considering the canopy volume, the pore compensation spraying amount of a single nozzle is

[0085] q1 = -αρq;

[0086] Among them, the pore compensation spraying amount of a single nozzle is q1, α is the pore compensation coefficient, and the value range is 0 < α < 1; the spraying amount of a single nozzle in the ideal grid prescription map is q, and the internal porosity of the grid is ρ.

[0087] Furthermore, in the case where the spraying amplitude remains unchanged, only considering the canopy volume and not considering the pore distribution, the canopy volume compensation spraying amount of a single nozzle is:

[0088]

[0089] Among them, the canopy volume compensation spraying amount of a single nozzle is q2, β is the canopy volume compensation coefficient, and the value range is 0 < β < 1; the spraying amount of a single nozzle in the ideal grid prescription map is q, V is the canopy volume within the grid, and V avg is the average value of the canopy volumes of all grids.

[0090] Furthermore, the spraying amount of a single nozzle 2 is calculated through the following formula model:

[0091]

[0092] The original spraying width is L, and the changed spraying width is L′; the spraying amount of a single nozzle 2 in the ideal grid prescription map is q, and the spraying amount of a single nozzle 2 in the changed grid prescription map is q res ; the pore compensation spraying amount in the ideal grid prescription map is q1, and the pore compensation spraying amount in the changed grid prescription map is q′1; the volume compensation spraying amount in the ideal grid prescription map is q2, and the canopy volume compensation spraying amount in the changed grid prescription map is q′2; the porosity in the ideal grid prescription map is ρ, and the porosity in the changed grid prescription map is ρ′; the canopy volume in the ideal grid prescription map is V, and the canopy volume in the changed grid prescription map is V′, and V avg is the average value of all canopy volumes or a reference value set artificially; α is the pore compensation coefficient, and the value range is 0 < α < 1; β is the canopy volume compensation coefficient, and the value range is 0 < β < 1; both α and β are optimized and adjusted according to the spraying effect.

[0093] The above is a preferred embodiment of the present invention, but the embodiments of the present invention are not limited by the above content. Any other changes, modifications, substitutions, combinations, and simplifications made without departing from the spirit and principle of the present invention shall be equivalent replacement methods and are all included in the protection scope of the present invention.

Claims

1. An adjustable spray width unmanned aerial vehicle variable spraying method, characterized in that, Including the following steps: Using a drone carrying an information collector to collect agricultural information data of crops in the operation area; the collected agricultural information data includes the distribution of pests and diseases, the canopy volume of the crops, and the pore distribution information; Processing the distribution of pests and diseases through an on-board processor to obtain a pest and disease distribution map; combining the image information obtained by a vision sensor and the three-dimensional point cloud information obtained by a three-dimensional lidar to obtain the canopy volume and pore distribution of the crops; Combining a spatial statistics algorithm, calculating a theoretical recommended grid based on the pest and disease distribution map, and then generating an ideal grid prescription map from the theoretical recommended grid; sending the pest and disease distribution map and the ideal grid prescription map to the remote control module; The staff determines a variable grid prescription map on the remote control module by combining the pest and disease distribution map and the ideal grid prescription map, and sends the variable grid prescription map to the on-board processor of the on-board control module; The on-board processor obtains the spraying width and spraying amount of each grid according to the variable grid prescription map, and generates a corresponding work instruction to send to the spraying execution mechanism; During the spraying operation, the drone sails along the set path, and at the same time executes the corresponding work instructions. The spraying width of the spraying component is adjusted in real time through the lateral drive mechanism to adapt to the amplitude of different grids; the spraying amount of its own nozzles is adjusted through the spraying component to perform differential spraying on different grids until all spraying operations are completed; The canopy volume is obtained by the following method: Obtaining a visible light image through the information collector, processing the visible light image to obtain an orthoimage, and generating a dense point cloud; denoising the point cloud data and performing ground point classification; Generating a digital elevation model and a digital surface model from the ground points, calculating and outputting the total pixel area of the canopy height model through the formula CHM = DSM - DEM. This total pixel area is the canopy area of the corresponding crop, and substituting the canopy area into the following formula to obtain the canopy volume of the crop: ； Where, V is the canopy volume of the crop; Hi is the pixel height intensity value in the pixel CHM; GSD is the ground sampling distance, and the CHM resolution is 0.05m.

2. The variable spraying method for an unmanned aerial vehicle with adjustable spraying width according to claim 1, wherein In the case where the spraying width remains unchanged, only considering the pore distribution and not considering the canopy volume, the pore compensation spraying amount of a single nozzle is: ； Among them, the pore compensation spray volume of a single nozzle is , is the pore compensation coefficient, and its value range is ; the spray volume of a single nozzle in the ideal grid prescription diagram is , and the internal porosity of the grid is .

3. The variable spraying method of the drone with adjustable spraying width according to claim 1, wherein, In the case where the spraying width remains unchanged, only considering the canopy volume and not considering the pore distribution, the canopy volume compensation spraying amount of a single nozzle is: ； Among them, the spraying amount for canopy volume compensation of a single nozzle is , is the canopy volume compensation coefficient, and its value range is ; the spraying amount of a single nozzle in the ideal grid prescription map is , is the canopy volume within the grid, is the average value of the canopy volumes of all grids.

4. The variable spraying method of the drone with adjustable spraying width according to claim 1, characterized in that The spraying amount of a single nozzle is calculated through the following formula model: ； ； The original spray width is , and the spray width after change is ; The spray volume of a single nozzle in the ideal grid prescription diagram is , and the spray volume of a single nozzle in the changed grid prescription diagram is ; The pore compensation spray volume in the ideal grid prescription diagram is , and the pore compensation spray volume in the changed grid prescription diagram is ; The volume compensation spray volume in the ideal grid prescription diagram is , and the canopy volume compensation spray volume in the changed grid prescription diagram is ; The porosity in the ideal grid prescription diagram is , and the porosity in the changed grid prescription diagram is ; The canopy volume in the ideal grid prescription diagram is , and the canopy volume in the changed grid prescription diagram is , is the average value of all canopy volumes or a reference value set artificially; is the pore compensation coefficient, and its value range is ; is the canopy volume compensation coefficient, and its value range is ; and are both optimized and adjusted according to the spraying effect.

5. A variable spraying system for an unmanned aerial vehicle applying the method for variable spraying of an unmanned aerial vehicle with adjustable spraying width according to any one of claims 1-4, characterized in that, Including a drone and a spraying execution mechanism and a spraying control module arranged on the drone; The spraying execution mechanism includes at least two groups of spraying components and a lateral drive mechanism for adjusting the lateral distance between the spraying components; The spraying control module includes an on-board control module and a remote control module; the on-board control module is connected to the remote control module through a wireless network. The on-board control module includes an information collector and an on-board processor; the information collector includes a vision sensor for obtaining crop image information, a GNSS / INS positioning module for obtaining the geographical information of the crops, and a three-dimensional lidar for obtaining the three-dimensional point cloud information of the crops; The airborne processor is used to obtain a pest and disease distribution map from the agricultural information data collected by the information collection module by using a pre-established model. The agricultural information data includes the pest and disease distribution situation. Calculate the theoretical recommended grid size through the pest and disease distribution map according to the spatial statistics algorithm, obtain the ideal grid prescription map through the theoretical recommended grid size, and send the pest and disease distribution map and the ideal grid prescription map to the remote control module. The staff determines the variable grid prescription map on the remote control module by combining the pest and disease distribution map and the ideal grid prescription map, and sends the variable grid prescription map to the airborne processor of the airborne control module. When the airborne processor receives the variable grid prescription map, it generates a time signal, a displacement signal and a prescription value according to the variable grid prescription map and transmits them to the spraying actuator. The remote control module is used for the staff to determine the variable grid prescription map according to the pest and disease distribution map and the ideal grid prescription map, and send the variable grid prescription map back to the airborne processor of the airborne control module.

6. The drone variable spraying system according to claim 5, characterized in that, A memory is provided on the airborne control module or the remote control module. The memory is used to store the data acquired by the information collector, the ideal grid prescription map, the variable grid prescription map, the data of the flow sensor and the data of the displacement sensor.

7. The variable spraying system for unmanned aerial vehicle according to claim 5, characterized in that, The spraying assembly includes a spray pipe and a spray head. The spray head is fixedly connected to the spray pipe. The spray pipe is communicated with the medicine tank and is fixedly connected to the driving end of the transverse driving mechanism. The spraying assembly further includes an electromagnetic valve for controlling the spraying amount of the spray head and a flow sensor for monitoring the spraying amount of the spray head. The electromagnetic valve and the flow sensor are both arranged on the spray pipe. The electromagnetic valve and the flow sensor are both electrically connected to the airborne processor.

8. The variable spraying system for unmanned aerial vehicle according to claim 5, characterized in that, The transverse driving mechanism is arranged on the mounting frame. The transverse driving mechanism includes a transverse moving frame, a transverse driving motor and a transverse transmission assembly. The transverse transmission assembly includes a lead screw and a lead screw nut. The lead screw nut is fixedly connected to the transverse moving frame. The spraying assembly is arranged on the transverse moving frame. The transverse driving mechanism further includes a displacement sensor for detecting the moving distance of the spraying assembly. The displacement sensor is electrically connected to the airborne processor. There are two transverse moving frames. There are two sets of the transverse driving mechanism and the spraying assembly. The two sets of spraying assemblies are respectively arranged on the two transverse moving frames. Each set of spraying assemblies includes at least two spraying assemblies, and the spraying assemblies in the same set are arranged on the same transverse moving frame.

9. The drone variable spraying system according to claim 8, wherein, The transverse moving frame includes a fixed moving part and a moving swing part. The fixed moving part is connected to the driving end of the transverse driving mechanism. The moving swing part is rotatably connected to the lower end of the fixed moving part. The spraying actuator further includes a swing driving mechanism for driving the spray assembly to swing. The swing driving mechanism includes a swing driving motor. The housing of the swing driving motor is fixed on the fixed moving part, and the output shaft of the swing driving motor is fixedly connected to the moving swing part. The output shaft of the swing driving motor coincides with the rotation center of the moving swing part.

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