Row control method, device and equipment of corn harvester and storage medium

Abstract

The invention provides a row control method, device and equipment of a corn harvester and a storage medium. The method comprises the following steps: acquiring image information of corn plants in front of the corn harvester; acquiring latitude and longitude data of the current position of the corn harvester; according to the corn crop image information, determining a corn plant boundary point mean value coordinate; determining a median point coordinate of the corn harvester according to the latitude and longitude data of the current position; according to the mean value coordinate and the median value point coordinate of the boundary point of the corn plant, determining an automatic row alignment line; and controlling the corn harvester to execute row control operation according to the automatic row control line. The robustness and the harvesting efficiency of the corn harvester are improved.

Description

Technical Field

[0001] The present application relates to the technical field of agricultural machinery, and in particular to a row control method, device, equipment and storage medium for a corn harvester. Background Art

[0002] A corn harvester is an agricultural machine used to harvest corn. The row-control capability of the corn harvester is directly related to the accuracy and efficiency of the operation.

[0003] Currently, automatic row alignment technologies for corn harvesters fall into two main categories. One is a sensor-based guidance system, which uses sensors like lasers and infrared to detect lateral distance and angle sensors to adjust the orientation for automatic row alignment. The other is based on image processing technology, which uses deep learning and other methods to identify corn plant boundaries and apply the least squares method to fit the initial row alignment of the corn crop. However, sensor-based guidance systems suffer from large errors in sensor-received parameter errors when plants deviate significantly, resulting in inaccurate row alignment results. Furthermore, image processing-based row alignment technologies are significantly affected by complex environments, leading to image distortion and, in turn, row line distortion, compromising the accuracy of row alignment results.

[0004] Based on this, in the prior art, there is a problem of low row alignment accuracy of corn harvesters. Summary of the Invention

[0005] The embodiments of the present application provide a row alignment control method, device, equipment and storage medium for a corn harvester, so as to improve the row alignment accuracy of the corn harvester.

[0006] In a first aspect, an embodiment of the present application provides a row control method for a corn harvester, which is applied to the corn harvester, and the method includes:

[0007] Obtain image information of corn plants in front of the corn harvester;

[0008] Get the current latitude and longitude data of the corn harvester;

[0009] Determine the mean coordinates of the boundary points of the corn plants based on the corn crop image information;

[0010] Determine the median coordinates of the corn harvester based on the current location latitude and longitude data;

[0011] Determine the automatic row alignment line based on the mean coordinates and median coordinates of the corn plant boundary points;

[0012] According to the automatic row alignment line, the corn harvester is controlled to perform row alignment operations.

[0013] In one possible implementation, controlling a corn harvester to perform row alignment according to the automatic row alignment line includes:

[0014] Obtain the preview distance and wheelbase of the corn harvester;

[0015] Determine the angle between the preview point and the vehicle body based on the automatic flight path and the current position longitude and latitude data;

[0016] Determine the target front wheel turning angle based on the preview distance, vehicle wheelbase, and the angle between the preview point and the vehicle body;

[0017] According to the target front wheel angle, the corn harvester is controlled to perform row operations.

[0018] In a possible implementation, determining the mean coordinates of the boundary points of corn plants based on corn crop image information includes:

[0019] Preprocessing the corn crop image information to obtain preprocessed image information;

[0020] Perform image segmentation on the pre-processed image information to obtain the pixel coordinates of the corn crop boundary points;

[0021] Perform coordinate system conversion on the pixel coordinates of the corn crop boundary points to obtain the world coordinates of the corn plant boundary points;

[0022] The world coordinates of the corn plant boundary points are averaged to obtain the mean coordinates of the corn plant boundary points.

[0023] In one possible implementation, determining the median point coordinates of the corn harvester based on the current position latitude and longitude data includes:

[0024] Performing regional segmentation processing on the current location longitude and latitude data to obtain multiple segmented regional longitude and latitude data;

[0025] Median filtering and mean calculation are performed on the segmented area longitude and latitude data to obtain the segmented area longitude and latitude data.

[0026] In one possible implementation, determining the automatic row alignment line based on the mean coordinates and the median coordinates of the corn plant boundary points includes:

[0027] The slope of the line was calculated using the least squares method and the straight line equation according to the mean coordinates of the boundary points and the median coordinates of the corn plants.

[0028] According to the slope of the line, fitting processing is performed to obtain the automatic alignment line.

[0029] In one possible embodiment, a corn harvester is equipped with a camera;

[0030] Accordingly, the image information of the corn plants in front of the corn harvester is obtained, including:

[0031] The camera collects image information of corn plants in front of the corn harvester.

[0032] In one possible implementation, the corn harvester is equipped with a real-time dynamic differential satellite positioning module;

[0033] Accordingly, the current latitude and longitude data of the corn harvester is obtained, including:

[0034] The current latitude and longitude data of the corn harvester are collected through the real-time dynamic differential satellite positioning module.

[0035] In a second aspect, an embodiment of the present application provides a row control device for a corn harvester, which is applied to a corn harvester and includes:

[0036] A first acquisition module is used to acquire image information of corn plants in front of the corn harvester;

[0037] The second acquisition module is used to obtain the current position latitude and longitude data of the corn harvester;

[0038] A first determination module is used to determine the mean coordinates of the boundary points of the corn plants based on the corn crop image information;

[0039] The second determining module is used to determine the median point coordinates of the corn harvester based on the current position longitude and latitude data;

[0040] The third determination module is used to determine the automatic row alignment line based on the mean coordinates and median coordinates of the corn plant boundary points;

[0041] The control module is used to control the corn harvester to perform row-aligning operations according to the automatic row-aligning line.

[0042] In a third aspect, an embodiment of the present application provides a row control device for a corn harvester, comprising: a memory, a processor;

[0043] Memory stores computer-executable instructions;

[0044] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0045] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementation methods of the first aspect.

[0046] The embodiments of the present application provide a method, device, equipment, and storage medium for controlling row alignment of a corn harvester. The method obtains the image information of the corn plant in front of the corn harvester and the longitude and latitude data of the current position; determines the mean coordinates of the boundary points of the corn plant according to the corn crop image information; determines the median coordinates of the corn harvester according to the longitude and latitude data of the current position; determines the automatic row alignment line according to the mean coordinates of the boundary points of the corn plant and the median coordinates; and controls the corn harvester to perform row alignment operations according to the automatic row alignment line. Compared with the prior art, the method of the present application accurately determines the mean coordinates of the boundary points of the corn plant and the median coordinates of the corn harvester by combining the image information of the corn plant and the longitude and latitude data of the current position, thereby calculating the precise row alignment line; reduces the influence of the external environment, improves the accuracy of row alignment, and thereby improves the harvesting efficiency of the corn harvester. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0048] Figure 1 This is a schematic diagram of the row control system architecture of a corn harvester provided in this application;

[0049] Figure 2 Schematic diagram of the process of the row control method of the corn harvester provided in this application Figure 1 ;

[0050] Figure 3 Schematic diagram of the process of the row control method of the corn harvester provided in this application Figure 2 ;

[0051] Figure 4 Schematic diagram of the process of the row control method of the corn harvester provided in this application Figure 3 ;

[0052] Figure 5 Schematic diagram of the process of the row control method of the corn harvester provided in this application Figure 4 ;

[0053] Figure 6 Schematic diagram of the process of the row control method of the corn harvester provided in this application Figure 5 ;

[0054] Figure 7 A schematic diagram of the steering structure of the corn harvester provided in this application;

[0055] Figure 8 A schematic diagram of the structure of the row control device of the corn harvester provided in this application;

[0056] Figure 9 This is a schematic diagram of the structure of the row control equipment of the corn harvester provided in this application.

[0057] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0058] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0059] It should be noted that the data involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0060] Optionally, Figure 1 This is a schematic diagram of the row control system architecture of a corn harvester provided in this application, such as Figure 1 As shown, the row control system architecture of the corn harvester includes at least one of a camera 101 , an RTK satellite positioning unit (Real-Time Kinematic, real-time dynamic differential positioning) 102 , an image processing unit 103 , a controller 104 and a steering mechanism 105 .

[0061] It is understood that the structure illustrated in the embodiments of this application does not constitute a specific limitation on the above architecture. In other feasible implementations of this application, the above architecture may include more or fewer components than shown, or combine or split certain components, or arrange the components differently. The specific configuration can be determined based on the actual application scenario and is not limited here. Figure 1 The components shown can be implemented in hardware, software, or a combination of software and hardware.

[0062] In a specific implementation process, the camera 101 is installed in the middle position above the cab of the corn harvester to collect images of the working area.

[0063] Two multi-frequency high-precision antennas of the RTK satellite positioning unit 102 are installed on the top of the cab of the corn harvester and are more than 1 meter apart. They are used to receive the latitude and longitude parameters of the current location of the corn harvester through the serial port line.

[0064] The image processing unit 103 is used to receive image samples collected from the working area and process the image samples using image processing technology.

[0065] The controller 104 is configured to receive and send command signals via a CAN (Controller Area Network) bus. In addition to the CAN bus, other communication protocols include RS232 (Recommended Standard 232), RS485 (Recommended Standard 485), or Ethernet Modbus-TCP (Ethernet Modbus Transmission Control Protocol), which are not specifically limited herein.

[0066] The steering mechanism 105 is used to receive a command signal from the controller 104 and control the corn harvester to perform a corresponding steering action according to the command signal.

[0067] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0068] Figure 2 Schematic diagram of the process of the row control method of the corn harvester provided in this application Figure 1 ,like Figure 2 As shown, the method includes:

[0069] S201: Acquire image information of corn plants in front of a corn harvester.

[0070] Furthermore, the corn harvester is equipped with a camera;

[0071] Accordingly, the image information of the corn plants in front of the corn harvester is obtained, including:

[0072] The camera collects image information of corn plants in front of the corn harvester.

[0073] In this embodiment, the corn plant image information includes clear corn plant boundaries.

[0074] In this embodiment, the actual installation position and installation angle of the camera can be slightly adjusted according to the specific situation. When installing the camera, it can be tilted downward at a preset angle to prevent direct sunlight or dust from affecting the quality of the collected image.

[0075] S202: Obtain the current latitude and longitude data of the corn harvester.

[0076] Furthermore, the corn harvester is equipped with a real-time dynamic differential satellite positioning module;

[0077] Accordingly, the current latitude and longitude data of the corn harvester is obtained, including:

[0078] The current latitude and longitude data of the corn harvester are collected through the real-time dynamic differential satellite positioning module.

[0079] In this embodiment, the real-time dynamic differential satellite positioning module is a high-precision satellite positioning technology that achieves centimeter-level positioning accuracy through differential correction; through the real-time dynamic differential satellite positioning module, the current position latitude and longitude data of the corn harvester can be accurately collected in real time.

[0080] S203: Determine the mean coordinates of the corn plant boundary points based on the corn crop image information.

[0081] In this embodiment, corn crop image information is preprocessed and segmented to obtain pixel coordinates of corn crop boundary points, and the pixel coordinates of corn crop boundary points are subjected to coordinate system conversion and mean calculation to determine the mean coordinates of corn plant boundary points; the number of image samples is reduced, hardware requirements are lowered, and the training process is simplified, thereby effectively improving the computational efficiency of the corn harvester.

[0082] S204: Determine the median point coordinates of the corn harvester based on the current position latitude and longitude data.

[0083] In this embodiment, by obtaining the real-time longitude and latitude data of the current position of the corn harvester, the longitude and latitude data of the current position are segmented in terms of region and time, and then median filtering and mean calculation are performed to smooth the data and reduce the probability of data errors, thereby improving the accuracy of the median point coordinates of the corn harvester.

[0084] S205: Determine the automatic row alignment line based on the mean coordinates and median coordinates of the corn plant boundary points.

[0085] In this embodiment, the automatic row alignment is obtained based on the mean coordinates and median coordinates of the corn plant boundary points, which reduces the dependence on sensors and mechanical structures, thereby reducing the harvesting cost. At the same time, the mean coordinates and median coordinates of the corn plant boundary points remove abnormal data and smooth the data, reducing data errors and improving the accuracy of the automatic row alignment.

[0086] S206: Control the corn harvester to perform row alignment according to the automatic row alignment line.

[0087] In this embodiment, the corn harvester uses the current position of the corn harvester as the starting point, navigates according to the automatic row alignment line, performs automatic row alignment, and uses path tracking technology to perform steering movements to complete the harvesting of corn plants in the operation area, thereby reducing manual work and improving work efficiency. The path tracking technology includes a PID algorithm (Proportional-Integral-Derivative Control Algorithm), a fuzzy control algorithm, and a deep learning algorithm.

[0088] The present invention provides a method for controlling row alignment of a corn harvester. This method obtains image information of corn plants in front of the harvester and the longitude and latitude data of the harvester's current location; determines the mean coordinates of the corn plant boundary points based on the corn crop image information; determines the median coordinates of the harvester based on the longitude and latitude data of the harvester's current location; determines an automatic row alignment line based on the mean coordinates of the corn plant boundary points and the median coordinates; and controls the harvester to perform row alignment based on the automatic row alignment line. Compared to existing technologies, this method reduces the impact of the external environment and harvesting costs, while improving the accuracy of the harvester's row alignment control.

[0089] Figure 3 Schematic diagram of the process of the row control method of the corn harvester provided in this application Figure 2 ,like Figure 3 As shown, this embodiment Figure 2 Based on the embodiment, the method of determining the mean coordinates of the corn plant boundary points according to the corn crop image information in step S203 is described in detail. The method includes:

[0090] S301 : Preprocess corn crop image information to obtain preprocessed image information.

[0091] In this embodiment, due to environmental interference such as dust, lighting conditions or mechanical vibration in the working area, the collected corn crop image information usually includes information noise. Therefore, Gaussian filtering, median filtering or bilateral filtering can be used to denoise the corn crop image information to improve the accuracy of the image information.

[0092] S302: Perform image segmentation processing on the pre-processed image information to obtain pixel coordinates of corn crop boundary points.

[0093] In this embodiment, the Canny edge detection algorithm is used to perform image segmentation processing on the preprocessed image information to obtain the pixel coordinates of the corn crop boundary points; wherein the image segmentation processing includes gradient amplitude and direction calculation, non-maximum suppression, dual threshold detection and edge connection.

[0094] S303: Perform coordinate system conversion processing on the pixel coordinates of the corn crop boundary points to obtain the world coordinates of the corn plant boundary points.

[0095] In this embodiment, a preset coordinate system conversion formula is used to perform coordinate system conversion processing on the pixel coordinates of the corn crop boundary points to obtain the world coordinates of the corn plant boundary points; wherein the coordinate system conversion formula is as follows:

[0096]

[0097] Where s is the scale factor; u and v are the pixel coordinates of the corn crop boundary point; A is the camera intrinsic parameter matrix; R is the rotation matrix; t is the translation matrix; X and Y are the world coordinates of the corn plant boundary point, Z is the pixel coordinates of the corn crop boundary point, and const The world coordinate height of the corn plant boundary point.

[0098] S304: Perform mean calculation processing on the world coordinates of the corn plant boundary points to obtain mean coordinates of the corn plant boundary points.

[0099] In this embodiment, after obtaining the world coordinates of the corn plant boundary points through the preset coordinate system conversion formula, the world coordinates (X, Y, Z) of the multiple corn plant boundary points are converted into the world coordinates (X, Y, Z) of the corn plant boundary points. const ), due to Z const For the same world coordinate height of the corn plant boundary point, the mean of X and Y is calculated respectively to obtain the stable mean coordinates of the corn plant boundary point, so as to smooth the data, reduce noise and improve data accuracy.

[0100] The row control method for a corn harvester provided in the present application improves the image quality by preprocessing, segmenting, converting coordinates, and calculating the mean of corn crop image information, and obtains spatial information from the image data to determine the growth status and spatial distribution characteristics of the corn plants, providing accurate data for subsequent row calculations.

[0101] Figure 4 Schematic diagram of the process of the row control method of the corn harvester provided in this application Figure 3 ,like Figure 4 As shown, this embodiment Figure 2 Based on the embodiment, the method of determining the median point coordinates of the corn harvester according to the current position longitude and latitude data in step S204 is described in detail. The method includes:

[0102] S401: Perform regional segmentation processing on the current position longitude and latitude data to obtain a plurality of segmented regional longitude and latitude data.

[0103] In this embodiment, for example, the real-time recording of the current position longitude and latitude data is (x ij ,y ij ), after segmenting the current location longitude and latitude data into different regions, N groups of longitude and latitude data are obtained, and each group of longitude and latitude data includes M longitude and latitude data; i is the longitude and latitude data group identifier, i is less than or equal to N, j is the longitude and latitude data identifier, j is less than or equal to M, N and M are both integers greater than 0; then x ij The longitude of the jth longitude and latitude data of the i-th group, y ij Represents the latitude of the j-th longitude and latitude data of the i-th group.

[0104] S402: Perform median filtering and mean calculation processing on the segmented area longitude and latitude data to obtain the median point coordinates of the corn harvester.

[0105] In this embodiment, the segmented area longitude and latitude data are subjected to median filtering to remove outliers in the segmented area longitude and latitude data; the segmented area longitude and latitude data after removing outliers are cached according to a preset time interval, and the longitude and latitude data of the preset time interval are then subjected to mean calculation processing to obtain the median point coordinates (x m ,y m ).

[0106] The row control method for a corn harvester provided in the present application reduces data noise while retaining the edge features of the data by segmenting the longitude and latitude data in terms of region and time, thereby reducing data errors and reducing the impact of deviating plants on the fitting of automatic row lines, thereby improving the accuracy of longitude and latitude data.

[0107] Figure 5 Schematic diagram of the process of the row control method of the corn harvester provided in this application Figure 4 ,like Figure 5 As shown, this embodiment Figure 2 Based on the embodiment, the method of automatically specifying the row lines according to the mean coordinates and median coordinates of the corn plant boundary points in step S205 includes:

[0108] S501. Using the least square method and the straight line equation, the slope of the line is calculated based on the mean coordinates of the boundary points and the median coordinates of the corn plants.

[0109] In this embodiment, the calculation formula of the row line slope is as follows:

[0110]

[0111] Where k is the slope of the line; n is the number of mean coordinates of the boundary points of the corn plant; i is the mean coordinate identifier of the boundary points of the corn plant; x i ,y i are the mean coordinates of the boundary points of the corn plant; x m ,y m are the coordinates of the median point respectively.

[0112] S502: Perform fitting processing according to the slope of the line to obtain the automatically aligned line.

[0113] In this embodiment, a fitting process is performed based on the slope of the row line and the coordinates of the boundary points of the corn plants to obtain an automatic row line for use in navigating the corn harvester to facilitate accurate harvesting of the corn harvester.

[0114] The row control method for a corn harvester provided in this application calculates the slope of the row line and performs fitting processing to obtain an automatic row line for guiding the navigation of the corn harvester, helping the corn harvester to move accurately along the automatic row line, thereby improving the efficiency and accuracy of harvesting.

[0115] Figure 6 Schematic diagram of the process of the row control method of the corn harvester provided in this application Figure 5 ,like Figure 6 As shown, this embodiment Figure 2 Based on the embodiment, the above step S206 of controlling the corn harvester to perform row alignment according to the automatic row alignment line is described in detail. The method includes:

[0116] S601: Obtain the preview distance and wheelbase of the corn harvester.

[0117] In this embodiment, the preview distance refers to the distance between the corn harvester and the preview point; the vehicle wheelbase refers to the distance between the front and rear axles of the corn harvester.

[0118] S602: Determine the angle between the preview point and the vehicle body based on the automatic navigation route and the current position longitude and latitude data.

[0119] In this embodiment, the preview point refers to a preset steering position; and the angle between the preview point and the vehicle body refers to the angular difference between the direction of the preview point and the current direction of the corn harvester.

[0120] S603: Determine the target front wheel turning angle based on the preview distance, the vehicle body wheelbase, and the angle between the preview point and the vehicle body.

[0121] In this embodiment, the preview distance, the vehicle wheelbase and the angle between the preview point and the vehicle body are similar to the target front wheel turning angle. Figure 7 shown; in Figure 7 In the figure, C is the preview point, (x r ,y r ) is the longitude and latitude coordinates of the preview point; A is the current position of the corn harvester, (x h ,y h ) are the longitude and latitude coordinates of the current position of the corn harvester; O is the center of the turning circle; R is the turning radius.

[0122] The target front wheel angle is calculated based on the preview distance, the vehicle wheelbase, and the angle between the preview point and the vehicle body:

[0123]

[0124] By simplifying formula 3, we can get:

[0125]

[0126]

[0127] From formula 4 and formula 5, we can get:

[0128]

[0129] Where, is the target front wheel angle; is the preview distance; is the angle between the preview point and the vehicle body; L is the wheelbase of the vehicle body.

[0130] S604: Control the corn harvester to perform row-aligning operations according to the target front wheel turning angle.

[0131] In this embodiment, the target front wheel angle is calculated through path tracking technology to control the steering of the corn harvester, thereby achieving row-by-row operation of corn plants in the entire operation area, reducing human errors and improving operation efficiency.

[0132] The row control method for a corn harvester provided in the present application determines the target front wheel angle by obtaining the preview distance of the corn harvester, the wheelbase of the vehicle body, and the angle between the determined preview point and the vehicle body, so as to control the automatic steering of the corn harvester, perform row operations, realize automatic harvesting of corn plants, and improve the harvesting efficiency and accuracy of the corn harvester.

[0133] Figure 8This is a schematic diagram of the structure of the row control device of the corn harvester provided in this application, as shown in FIG. Figure 8 As shown, the row control device of the corn harvester provided in this embodiment includes:

[0134] The first acquisition module 801 is used to acquire image information of corn plants in front of the corn harvester;

[0135] The second acquisition module 802 is used to obtain the longitude and latitude data of the current position of the corn harvester;

[0136] A first determining module 803 is configured to determine the mean coordinates of the boundary points of the corn plants based on the corn crop image information;

[0137] The second determining module 804 is configured to determine the median coordinates of the corn harvester based on the current location latitude and longitude data;

[0138] The third determining module 805 is used to determine the automatic row alignment line based on the mean coordinates and median coordinates of the corn plant boundary points;

[0139] The control module 806 is used to control the corn harvester to perform row alignment operations according to the automatic row alignment line.

[0140] In a possible implementation, the corn harvester is equipped with a camera; the first acquisition module 801 may further be used to:

[0141] The camera collects image information of corn plants in front of the corn harvester.

[0142] In a possible implementation, the corn harvester is equipped with a real-time dynamic differential satellite positioning module; the second acquisition module 802 may further be used to:

[0143] The current latitude and longitude data of the corn harvester are collected through the real-time dynamic differential satellite positioning module.

[0144] In a possible implementation, the first determining module 803 may further be configured to:

[0145] Preprocessing the corn crop image information to obtain preprocessed image information;

[0146] Perform image segmentation on the pre-processed image information to obtain the pixel coordinates of the corn crop boundary points;

[0147] Perform coordinate system conversion on the pixel coordinates of the corn crop boundary points to obtain the world coordinates of the corn plant boundary points;

[0148] The world coordinates of the corn plant boundary points are averaged to obtain the mean coordinates of the corn plant boundary points.

[0149] In a possible implementation, the second determining module 804 may further be configured to:

[0150] Performing regional segmentation processing on the current location longitude and latitude data to obtain multiple segmented regional longitude and latitude data;

[0151] Median filtering and mean calculation are performed on the segmented area longitude and latitude data to obtain the median point coordinates of the corn harvester.

[0152] In a possible implementation, the third determining module 805 may further be configured to:

[0153] The slope of the line was calculated using the least squares method and the straight line equation according to the mean coordinates of the boundary points and the median coordinates of the corn plants.

[0154] According to the slope of the line, fitting processing is performed to obtain the automatic alignment line.

[0155] In a possible implementation, the control module 806 may further be configured to:

[0156] Obtain the preview distance and wheelbase of the corn harvester;

[0157] Determine the angle between the preview point and the vehicle body based on the automatic flight path and the current position longitude and latitude data;

[0158] Determine the target front wheel turning angle based on the preview distance, vehicle wheelbase, and the angle between the preview point and the vehicle body;

[0159] According to the target front wheel angle, the corn harvester is controlled to perform row operations.

[0160] The row control device for a corn harvester provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effects are similar, and are not described in detail in this embodiment.

[0161] Figure 9 This is a schematic diagram of the structure of the row control device of the corn harvester provided in this application. Figure 9 As shown, the row control device for a corn harvester provided in this embodiment includes: at least one processor 901 and a memory 902. Optionally, the row control device for a corn harvester further includes a communication component 903. The processor 901, the memory 902, and the communication component 903 are connected via a bus 904.

[0162] During the specific implementation process, at least one processor 901 executes the computer-executable instructions stored in the memory 902, so that the at least one processor 901 performs the above method.

[0163] The specific implementation process of the processor 901 can be found in the above method embodiment. Its implementation principle and technical effects are similar and will not be repeated here in this embodiment.

[0164] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASICs), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules within the processor.

[0165] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage.

[0166] A bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be categorized as address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0167] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0168] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0169] The readable storage medium may be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0170] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0171] The division of units is merely a logical functional division; actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, any direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units, either through an interface, electrical, mechanical, or other means.

[0172] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0173] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0174] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0175] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0176] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. A method for controlling rows of a corn harvester, characterized in that: Applied to a corn harvester, the method comprises: Acquiring image information of corn plants in front of the corn harvester; Obtaining the current latitude and longitude data of the corn harvester; determining mean coordinates of corn plant boundary points based on the corn crop image information; Determining the median point coordinates of the corn harvester based on the current position latitude and longitude data; determining an automatic row alignment line according to the mean coordinates of the corn plant boundary points and the median coordinates; According to the automatic row alignment line, the corn harvester is controlled to perform row alignment operations.

2. The method according to claim 1, characterized in that The step of controlling the corn harvester to perform row alignment according to the automatic row alignment line includes: Obtaining the preview distance and wheelbase of the corn harvester; Determining the angle between the preview point and the vehicle body according to the automatic alignment route and the current position latitude and longitude data; Determining a target front wheel turning angle according to the preview distance, the vehicle body wheelbase, and the angle between the preview point and the vehicle body; According to the target front wheel turning angle, the corn harvester is controlled to perform row operation.

3. The method according to claim 1, characterized in that Determining the mean coordinates of the corn plant boundary points based on the corn crop image information includes: Preprocessing the corn crop image information to obtain preprocessed image information; Performing image segmentation processing on the pre-processed image information to obtain pixel coordinates of corn crop boundary points; Performing coordinate system conversion processing on the pixel coordinates of the corn crop boundary points to obtain world coordinates of the corn plant boundary points; The world coordinates of the corn plant boundary points are averaged to obtain the average coordinates of the corn plant boundary points.

4. The method according to claim 1, wherein Determining the median point coordinates of the corn harvester based on the current position latitude and longitude data includes: Performing regional segmentation processing on the current position longitude and latitude data to obtain a plurality of segmented regional longitude and latitude data; Median filtering and mean calculation are performed on the segmented area longitude and latitude data to obtain the median point coordinates of the corn harvester.

5. The method according to any one of claims 1 to 4, characterized in that The step of determining the automatic row alignment line according to the mean coordinates of the corn plant boundary points and the median coordinates includes: The slope of the line is calculated using the least squares method and the straight line equation according to the mean coordinates of the boundary points of the corn plants and the coordinates of the median point; According to the line slope, fitting processing is performed to obtain the automatic alignment line.

6. The method according to any one of claims 1 to 4, characterized in that The corn harvester is equipped with a camera; Accordingly, the obtaining of image information of corn plants in front of the corn harvester includes: The camera collects image information of corn plants in front of the corn harvester.

7. The method according to any one of claims 1 to 4, characterized in that The corn harvester is equipped with a real-time dynamic differential satellite positioning module; Accordingly, the obtaining of the current position latitude and longitude data of the corn harvester includes: The real-time dynamic differential satellite positioning module is used to collect the longitude and latitude data of the current position of the corn harvester.

8. A row control device for a corn harvester, characterized in that: Applied to a corn harvester, the device comprises: a first acquisition module, configured to acquire image information of corn plants in front of the corn harvester; A second acquisition module is used to obtain the current position longitude and latitude data of the corn harvester; a first determining module, configured to determine mean coordinates of corn plant boundary points based on the corn crop image information; A second determining module is used to determine the median point coordinates of the corn harvester according to the current position longitude and latitude data; a third determining module, configured to determine an automatic row alignment line based on the mean coordinates of the corn plant boundary points and the median coordinates; A control module is used to control the corn harvester to perform row-aligning operations according to the automatic row-aligning line.

9. A row control device for a corn harvester, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the row control method of the corn harvester according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the row control method for a corn harvester according to any one of claims 1 to 7.

Images