Agricultural machine attitude sensor measurement method, system, medium, product, and terminal

Abstract

This invention provides a method, system, medium, product, and terminal for measuring the attitude of agricultural machinery using an inertial measurement unit. The invention obtains raw attitude data measured by each inertial measurement unit, calibrates the raw attitude data to obtain calibrated attitude data, and selects an output mode based on measurement requirements. If the output mode is fused, the calibrated attitude data is fused and calculated to obtain fused attitude data, which is then output. If the output mode is normal, either the calibrated attitude data or the raw attitude data is directly output. This invention overcomes the high-precision requirements of slow tillage and the large-range requirements of rapid obstacle avoidance in agricultural machinery. It is adaptable to complex agricultural environments, features high-frequency output, intelligent switching, and multi-component redundant fusion capabilities, effectively addressing special working conditions such as complex vibrations and electromagnetic interference in farmland.

Description

Technical Field

[0001] This invention relates to the field of agricultural navigation technology, and in particular to a method, system, medium, product, and terminal for measuring the attitude of agricultural machinery. Background Technology

[0002] Attitude sensors are crucial components in smart agriculture scenarios such as positioning of agricultural unmanned vehicles, plant protection by agricultural drones, and farming by agricultural robots. Their measurement accuracy and reliability directly determine the efficiency of agricultural operations, the effectiveness of crop protection, and the safety of equipment operation. Although existing attitude sensors have been applied in many fields, they have significant limitations in adapting to complex agricultural scenarios.

[0003] Single inertial measurement units (IMUs) are low-cost and widely used in simple devices, but their data update frequency is only 50-100Hz. They are susceptible to gyroscope drift caused by farmland bumps, over-range interference when agricultural machinery climbs slopes, and obstacles. Distorted output data can cause unmanned vehicles to damage seedlings and drones to spray unevenly. Basic multi-sensor fusion types, such as IMU + magnetometer, improve accuracy through filtering algorithms but lack redundancy. Dust and damp environments in farmland can easily cause IMU malfunctions, and there is no backup switching solution. Switching delays exceed 10ms, which may lead to drones losing control in gusts of wind or robots deviating from their farming trajectories. Customized types for specific scenarios have strong anti-interference capabilities, but range and accuracy are tied together, making it difficult to meet the high-precision requirements of slow agricultural machinery cultivation and the large-range requirements of rapid obstacle avoidance. They also do not support flexible fusion of multiple components and cannot cope with complex vibrations and electromagnetic interference in farmland. Summary of the Invention

[0004] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide a method, system, medium, product and terminal for measuring the attitude of agricultural machinery, in order to solve the problems of insufficient high-frequency output, poor reliability under extreme working conditions and limited fusion accuracy in the prior art, which make it unable to adapt to the technical problems of precision operation and stable operation in intelligent agriculture.

[0005] To achieve the above and other related objectives, the present invention provides a method for measuring the attitude of an agricultural machinery using an attitude sensor. The method includes: obtaining raw attitude data measured by each inertial measurement unit; calibrating each raw attitude data to obtain corresponding calibrated attitude data; and outputting final attitude data based on each calibrated attitude data using a fusion output mode or a conventional output mode.

[0006] In one embodiment of the present invention, the fusion output mode includes: performing fusion calculation on each calibration attitude data to obtain fused attitude data and outputting it as the final attitude data.

[0007] In one embodiment of the present invention, the step of fusing and calculating the calibrated attitude data to obtain fused attitude data includes:

[0008] Based on the calibration parameters corresponding to each calibration attitude data, the calculation weights corresponding to each inertial measurement unit are determined; the calibration attitude data are then weighted and fused using each calculation weight to obtain fused attitude data.

[0009] In one embodiment of the present invention, the conventional output mode includes: outputting each original attitude data or each calibrated attitude data as the final attitude data.

[0010] In one embodiment of the present invention, the calibration of each original attitude data includes: inputting the original attitude data into a preset calibration platform, calculating calibration parameters based on a pre-constructed temperature error compensation data table and a fusion filtering algorithm, and inputting the calibration parameters and the original attitude data into a preset error model to obtain calibrated attitude data.

[0011] In one embodiment of the present invention, the method further includes: real-time monitoring of the calibration attitude data corresponding to each inertial measurement unit, wherein if the calibration attitude data is detected to be within a preset accuracy threshold range, a conventional output mode is adopted; if the calibration attitude data is detected to exceed the preset accuracy threshold range, a fusion output mode is adopted.

[0012] To achieve the above and other related objectives, the present invention provides an agricultural machinery attitude sensor measurement system, the system comprising: a data acquisition module for acquiring raw attitude data measured by each inertial measurement unit, calibrating each raw attitude data to obtain corresponding calibrated attitude data; and a data output module for outputting final attitude data based on each calibrated attitude data using a fusion output mode or a conventional output mode.

[0013] To achieve the above and other related objectives, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any of the preceding claims.

[0014] To achieve the above and other related objectives, the present invention provides a computer program product comprising computer program code, which, when executed on a computer, causes the computer to perform any of the methods described above.

[0015] To achieve the above and other related objectives, the present invention provides an electronic terminal, comprising: one or more memories and one or more processors; the one or more memories are used to store a computer program; the one or more processors are connected to the memories and are used to run the computer program to execute the agricultural machinery attitude sensor measurement method.

[0016] As described above, this invention relates to a method, system, medium, product, and terminal for measuring the attitude of agricultural machinery, and has the following beneficial effects: This invention obtains raw attitude data measured by each inertial measurement unit, calibrates the raw attitude data to obtain calibrated attitude data, selects an output mode based on measurement requirements, performs fusion calculations on the calibrated attitude data to obtain fused attitude data and outputs it if the fusion output mode is entered, or directly outputs either the calibrated attitude data or the raw attitude data if the conventional output mode is entered. This invention overcomes the high-precision requirements of slow tillage and the large-range requirements of rapid obstacle avoidance in agricultural machinery, adapts to complex agricultural environments, and features high-frequency output, intelligent switching, and multi-component redundant fusion functions, effectively coping with complex vibrations, electromagnetic interference, and other special working conditions in farmland. Attached Figure Description

[0017] Figure 1 The diagram shown is a flowchart illustrating the agricultural machinery attitude sensor measurement method according to an embodiment of the present invention.

[0018] Figure 2 The diagram shown is a flowchart illustrating another method for measuring the attitude of agricultural machinery using a sensor, according to an embodiment of the present invention.

[0019] Figure 3 The diagram shown is a structural schematic of an agricultural machinery attitude sensor measurement system according to an embodiment of the present invention.

[0020] Figure 4 The diagram shown is a structural schematic of an electronic terminal according to an embodiment of the present invention. Detailed Implementation

[0021] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0022] It should be noted that in the following description, reference is made to the accompanying drawings, which illustrate several embodiments of the invention. It should be understood that other embodiments may also be used, and changes in mechanical composition, structure, electrical system, and operation may be made without departing from the spirit and scope of the invention. The following detailed description should not be considered limiting, and the scope of the embodiments of the invention is defined only by the claims of the published patents. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. Spatially related terms, such as “upper,” “lower,” “left,” “right,” “below,” “below,” “lower part,” “above,” “upper part,” etc., may be used herein to illustrate the relationship between one element or feature shown in the figures and another element or feature.

[0023] Throughout this specification, when it is said that a part is "connected" to another part, this includes not only "direct connection" but also "indirect connection" by placing other elements in between. Furthermore, when it is said that a part "includes" a certain constituent element, unless otherwise stated otherwise, this does not exclude other constituent elements, but rather means that other constituent elements may also be included.

[0024] The terms "first," "second," and "third," etc., used herein are for the purpose of describing various parts, components, regions, layers, and / or segments, but are not limiting. These terms are used only to distinguish one part, component, region, layer, or segment from others. Therefore, the "first part," "component," "region," "layer," or "segment" described below may refer to a "second part," "component," "region," "layer," or "segment" without departing from the scope of this invention.

[0025] Furthermore, as used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context indicates otherwise. It should be further understood that the terms “comprising,” “including,” indicate the presence of the stated feature, operation, element, component, item, kind, and / or group, but do not preclude the presence, occurrence, or addition of one or more other features, operations, elements, components, items, kinds, and / or groups. The terms “or” and “and / or” as used herein are interpreted as inclusive, or mean any one or any combination thereof. Thus, “A, B, or C” or “A, B, and / or C” means “any one of: A; B; C; A and B; A and C; B and C; A, B, and C.” Exceptions to this definition arise only when combinations of elements, functions, or operations are inherently mutually exclusive in some manner.

[0026] Before providing a further detailed description of the present invention, the nouns and terms used in the embodiments of the present invention are explained, and the nouns and terms used in the embodiments of the present invention are subject to the following interpretations:

[0027] <1> IMU: Inertial Measurement Unit, a sensing device for measuring the acceleration and angular velocity of an object. In this invention, it is used to collect raw attitude data of triaxial acceleration and triaxial angular velocity, providing basic data input for subsequent calibration and fusion calculation.

[0028] <2> UTC: Coordinated Universal Time, a globally unified time standard. In this invention, it provides a unified time reference for data output, ensuring time synchronization between data acquisition and output of each inertial measurement unit, and guaranteeing the accuracy of high-frequency output.

[0029] <3> CAN: Controller Area Network, an industrial communication bus. As the communication bus of this invention, it supports online adjustment of parameters such as data update frequency, accuracy threshold, and output data source, while also achieving stable communication adaptation between this invention and the agricultural machinery navigation system.

[0030] This invention provides a method for measuring the attitude of agricultural machinery using an inertial measurement unit (IMU). The method obtains raw attitude data from each IMU measurement unit, calibrates this raw attitude data to obtain calibrated attitude data, and selects an output mode based on measurement requirements. If the method enters a fusion output mode, it performs fusion calculations on the calibrated attitude data to obtain and output fused attitude data. If the method enters a normal output mode, it directly outputs either the calibrated attitude data or the raw attitude data. This invention overcomes the high-precision requirements of slow tillage and the large-range requirements of rapid obstacle avoidance in agricultural machinery. It is adaptable to complex agricultural environments, features high-frequency output, intelligent switching, and multi-component redundant fusion capabilities, effectively addressing special working conditions such as complex vibrations and electromagnetic interference in farmland.

[0031] The present invention will now be described in detail with reference to the accompanying drawings, so that those skilled in the art can readily implement it. The present invention can be embodied in many different forms and is not limited to the embodiments described herein.

[0032] like Figure 1 This is a flowchart illustrating a method for measuring the attitude of agricultural machinery using a sensor, as shown in an embodiment of the present invention.

[0033] The method includes:

[0034] Step S1: Obtain the raw attitude data measured by each inertial measurement unit, calibrate each raw attitude data, and obtain the corresponding calibrated attitude data.

[0035] In one embodiment, upon power-on, an initialization process is initiated. First, the main control module is initialized and configured, and the relevant control registers of two small-range inertial measurement units and one large-range inertial measurement unit are configured simultaneously, including key parameters such as sampling frequency, measurement range, data output format, and communication protocol, to ensure that each inertial measurement unit is compatible with the main control module in terms of communication. Then, a chip self-test program is started to perform integrity and functional tests on the accelerometer, gyroscope core sensing components and internal circuits and communication links of each inertial measurement unit. After confirming that there are no faults, each inertial measurement unit begins to synchronously acquire and output raw triaxial acceleration and raw triaxial angular velocity measurements to obtain raw attitude data, providing basic data input for subsequent calibration processes.

[0036] In one embodiment, calibrating the original attitude data to obtain calibrated attitude data includes: inputting the original attitude data into a preset calibration environment; calculating the original attitude data based on a pre-built temperature error compensation data table and a fusion filtering algorithm to obtain calibration parameters; and substituting the calibration parameters into a preset error model in combination with the original attitude data to obtain calibrated attitude data.

[0037] Specifically, the operating temperature and raw attitude data output by each inertial measurement unit (IMU) are collected in real time. This raw attitude data includes raw measurements of triaxial acceleration and triaxial angular velocity. After inputting the raw attitude data into a preset calibration environment, a first calibration is performed based on a pre-constructed temperature error compensation data table. This table is obtained by fixing the IMU to a turntable and collecting multiple sets of acceleration measurement data at different preset temperatures through multi-temperature zero-bias tests and multi-temperature multi-axis rotational excitation tests. Then, the least squares method is used to calculate the acceleration and angular velocity calibration parameters at each temperature. During calibration, interpolation or table lookup is used. The calibration parameters corresponding to the current operating temperature of the inertial measurement unit (IMU) are obtained and substituted into the preset acceleration error model and angular velocity error model to calculate the initial calibration values ​​for acceleration and angular velocity. Subsequently, a second calibration is performed using a multi-sensor fusion filtering algorithm based on Kalman filtering optimization. This involves constructing the state equation of the IMU, inputting the initial calibration values ​​obtained from the first calibration to obtain the initial predicted values ​​for position and velocity, calculating the residuals by combining the collected actual position and velocity observations, iteratively updating the state equation based on the principle of minimizing the residuals, obtaining the optimal estimated calibration parameters, and then substituting them into the corresponding error models again to finally obtain the calibrated target calibration values ​​for acceleration and angular velocity, thus completing the calibration of the original attitude data.

[0038] Step S2: Output the final attitude data based on each calibration attitude data using either a fusion output mode or a regular output mode.

[0039] In one embodiment, the calibration attitude data corresponding to each inertial measurement unit is monitored in real time. The calibration attitude data is compared and analyzed with a preset accuracy threshold to determine the actual accuracy requirement. If the actual accuracy requirement is high accuracy, a fusion output mode is adopted to perform fusion calculation on each calibration attitude data and output the obtained fused attitude data as the final attitude data. If the actual accuracy requirement is normal accuracy, any calibration attitude data that meets the preset threshold is directly output.

[0040] Specifically, the calibration attitude data, such as the triaxial acceleration calibration value and triaxial angular velocity calibration value of each inertial measurement unit, are monitored in real time. Quantitative features of the calibration attitude data are extracted. These quantitative features specifically include the real-time fluctuation amplitude of the triaxial acceleration calibration value and the real-time rate of change of the triaxial angular velocity calibration value. These quantitative features are compared and analyzed with preset accuracy thresholds, including preset acceleration fluctuation thresholds and preset angular velocity change thresholds. The actual accuracy requirement is determined by combining the preset sampling period where the quantitative features meet the corresponding thresholds. If the actual accuracy requirement is determined to be high accuracy, i.e., the triaxial acceleration fluctuation amplitude is greater than the preset acceleration fluctuation threshold and the triaxial angular velocity change rate is greater than the preset angular velocity change threshold, and the data does not exceed the maximum allowable threshold, the accuracy requirement is determined to be high accuracy. If the range of the inertial measurement unit is preset to an upper limit, then based on the calibration attitude data of two small-range inertial measurement units and one large-range inertial measurement unit, and combined with the accuracy characteristics of each inertial measurement unit and the real-time operating status to assign dynamic weights, the fused attitude data is obtained by fusion calculation and is output as the final attitude data. If the actual accuracy requirement is determined to be conventional accuracy, that is, the three-axis acceleration fluctuation amplitude and the three-axis angular velocity change rate do not exceed the corresponding preset accuracy threshold, then any calibration attitude data or original attitude data that meets the preset threshold is directly output, and the output data source supports online modification via CAN bus. After the system completes UTC time synchronization, the six-axis attitude data of the selected inertial measurement unit is output at a frequency of 200Hz.

[0041] In one embodiment, in fusion output mode, the system continuously acquires and records inertial measurement unit data within 1 second. The data processing method can be Kalman filtering or direct integration, and the data sampling time interval is... The data is processed cyclically at these time intervals until 1 second of data acquisition and processing is completed, and the total amount of processed data is [amount missing]. .

[0042] The specific processing procedure requires first setting initial state parameters: Let the initial position be... The initial velocity is The initial attitude quaternion is Then, a loop process is started, with the loop variable k ranging from 0 to... :

[0043] Read the angular velocity and acceleration measurements output by the inertial measurement unit at the current moment;

[0044] Update attitude quaternions: First, calculate the true angular velocity by subtracting the angular velocity zero bias error from the angular velocity measurement value. Then, discretize the quaternion differential equation to obtain the attitude increment. After superimposing the attitude increment onto the current attitude quaternion, normalize the attitude quaternion to ensure calculation accuracy.

[0045] Coordinate transformation: Using the current attitude quaternion, the acceleration measurement value is transformed from the inertial measurement unit coordinate system to the world coordinate system to obtain the acceleration in the world coordinate system;

[0046] Acceleration correction: In the world coordinate system, the gravity vector is subtracted from the transformed acceleration to obtain the actual acceleration of the agricultural machinery.

[0047] Integral calculation: Update the real-time velocity using the actual acceleration, and then update the real-time position based on the real-time velocity;

[0048] After completing the above loop, the system will obtain the core state parameters of the agricultural machinery 1 second later, including position, speed and attitude quaternions.

[0049] The process then proceeds to the multi-sensor data fusion stage: The specific implementation of the fusion calculation involves first defining the calibration attitude data of two small-range inertial measurement units as follows: , The corresponding calibration parameters are , The calibration parameters include acceleration scaling factor, cross-axis non-orthogonality error parameter, zero bias error parameter, and angular velocity scaling factor, cross-axis non-orthogonality error parameter, zero bias error parameter, etc., with dynamic weights of... , The calibration attitude data of a large range sensing element is The corresponding calibration parameters are Similar to the aforementioned calibration parameter types, the dynamic weights are... Based on the error quantification evaluation results of the calibration parameters of each inertial measurement unit (IMU), the smaller the error, the higher the measurement accuracy. Combining the aforementioned estimated position, velocity, attitude quaternions, and other state parameters, the reliability and adaptability of the IMU data are judged in real time. The weights are dynamically adjusted according to the principle that the higher the accuracy, the greater the weight. , , At the same time, ensure that the weights meet the constraints. The aforementioned weights are then fused with the calibration attitude data of the corresponding sensing elements using a fusion formula. Weighted fusion calculations are performed to obtain fused attitude data that balances measurement accuracy and environmental adaptability. This data is the final attitude data of the output in the fusion output mode.

[0050] In one embodiment, the data update frequency can be flexibly set according to the accuracy requirements of agricultural machinery operation scenarios. The setting method can be adjusted online by configuring the control register of the inertial measurement unit or the CAN bus. Since multiple inertial measurement units distribute the acquisition pressure, no single device needs to bear the full data processing, which greatly reduces the end-to-end latency of data acquisition, processing and output. The data update frequency range is adapted from 1Hz to 200Hz, and a maximum high-frequency output of 200Hz is supported. Specifically, after the system is powered on and initialized, and before UTC time synchronization, the system defaults to outputting the original attitude data and calibration attitude data of all inertial measurement units at a frequency of 1Hz to meet the equipment self-test requirements. After UTC time synchronization is completed, the system can switch to a maximum high-frequency output of 200Hz, outputting 200 sets of calibration attitude data or original attitude data per second. This can accurately capture the instantaneous attitude changes of agricultural machinery under complex working conditions such as undulating and irregular hard ground, and fully meet the requirements of agricultural operations for data real-time performance and precision.

[0051] In one embodiment, the specific process of calibrating the original attitude data is as follows: First, the original attitude data, including the original triaxial acceleration and triaxial angular velocity measurements, collected by two small-range inertial measurement units and one large-range inertial measurement unit, is input into a preset calibration environment adapted to the characteristics of agricultural machinery operation. This environment has built-in temperature error compensation logic, a fusion filtering algorithm module, and a preset error model, and is compatible with data update frequencies from 1Hz to 200Hz. Then, the original attitude data is collaboratively calculated based on a pre-built temperature error compensation data table and a multi-sensor fusion filtering algorithm. The preferred multi-sensor fusion filtering algorithm is the Kalman filter algorithm. The temperature error compensation data table calculates the acceleration error parameters at different preset temperatures by performing multi-temperature zero-bias tests and multi-temperature multi-axis rotational excitation tests on each inertial measurement unit, using the least squares method. The calibration parameters are constructed by first obtaining the error parameters corresponding to the current operating temperature through interpolation or table lookup to complete the first correction. Then, combined with the actual observed values ​​of position and velocity collected by the GPS device, the second correction is completed by constructing state equations, calculating residuals, and iteratively updating the Kalman gain, ultimately obtaining the calibration parameters with optimized accuracy. Finally, the above calibration parameters and the corresponding original attitude data are substituted into the preset acceleration error model and angular velocity error model, respectively. The error correction of the original attitude data is completed through model calculation, and the final output is the calibrated attitude data containing the three-axis acceleration calibration values ​​and the three-axis angular velocity calibration values.

[0052] In one embodiment, the specific implementation of the accuracy threshold analysis based on each calibration attitude data is as follows: Real-time monitoring of calibration attitude data output by two small-range inertial measurement units and one large-range inertial measurement unit, respectively, including triaxial acceleration calibration values ​​and triaxial angular velocity calibration values, with a focus on tracking the real-time fluctuation status of each axis calibration data; wherein the preset accuracy threshold includes a fluctuation amplitude threshold for calibration acceleration values ​​and a rate of change threshold for calibration angular velocity values. These thresholds can be adjusted online via the CAN bus based on agricultural machinery operation scenarios such as flat ground and undulating hard ground, and have been pre-adapted to the range characteristics of each inertial measurement unit. For example, the threshold for the large-range unit is adapted to its ±10g acceleration and ±1000° / s angular velocity range, while the threshold for the small-range unit is adapted to its ±2g acceleration and ±250° / s angular velocity range; the system continuously compares the real-time monitored calibration attitude data with the preset accuracy threshold. When the calibration data of any inertial measurement unit exceeds the corresponding threshold, and this exceeding state lasts for no less than 3 sampling cycles (approximately 15ms) at the highest output frequency of 200Hz to avoid erroneous switching caused by transient interference, the system automatically initiates the mode switching process, seamlessly switching from the normal output mode to the fusion output mode. Immediately after the switch, the system starts the fusion calculation of the calibration attitude data of multiple inertial measurement units to ensure that the output data can adapt to the complex working conditions of irregular shaking and undulation of agricultural machinery, and to ensure the accuracy and stability of attitude measurement. It is worth noting that when agricultural machinery navigation is applied to grader operation scenarios, or when agricultural machinery is traveling on hard ground with undulating terrain and irregular topography, even if the agricultural machinery is traveling at a constant speed, the vehicle body may experience continuous irregular shaking and undulation due to the influence of the terrain. In this case, the system can automatically switch to the fusion output mode.

[0053] In one embodiment, after power-on initialization, two small-range inertial measurement units are enabled by default for attitude data acquisition and output, so as to give full play to their advantages of small range and higher measurement accuracy, and adapt to the needs of most conventional working conditions such as flat ground operation and conventional farming. During operation, the calibration attitude data output by the default small-range inertial measurement units is monitored in real time. When the acceleration measurement value or angular velocity measurement value of any small-range inertial measurement unit is detected to exceed the range, the range adaptation switching mechanism is immediately triggered. The data source is quickly switched within 2.5ms, and the processing and output of the raw attitude data and calibration attitude data of the large-range inertial measurement units are seamlessly enabled, avoiding measurement failure due to data overflow, and ensuring that the agricultural machinery can still obtain stable and effective attitude data support under extreme bumps, large fluctuations and other unconventional working conditions.

[0054] In one embodiment, the operating status of all inertial measurement units (IMUs) is monitored in real time. The monitoring dimensions cover key indicators such as the signal integrity of the core sensing components of the accelerometers and gyroscopes inside each IMU, the stability of the data transmission link, and whether the measured values ​​exceed the hardware limit range. When any one or more IMUs are diagnosed with faults such as signal interruption, data transmission error, or abnormally excessive measured values, a redundancy switching mechanism is activated. The data link of the faulty sensing element is quickly cut off within 2.5ms, and the system seamlessly switches to the data source of other normal IMUs. After the switch, the calibration attitude data of the normal IMUs is used to carry out subsequent threshold analysis, fusion calculation, or direct output processes, ensuring that the attitude data output is uninterrupted. This fully guarantees the continuity and reliability of data during agricultural machinery operations and avoids functional failure due to the failure of a single or multiple IMUs.

[0055] To better describe the agricultural machinery attitude sensor measurement method, the following specific embodiments are provided.

[0056] Example 1: Attitude sensor measurement method on agricultural unmanned vehicle.

[0057] like Figure 2 The following diagram further illustrates the implementation steps.

[0058] Step 1: Begin.

[0059] The initialization process is initiated, the control registers of two small-range inertial measurement units and one large-range inertial measurement unit are configured, and the chip self-test is completed.

[0060] Step 2: Collect raw attitude data.

[0061] Each inertial measurement unit synchronously acquires raw attitude data of triaxial acceleration and triaxial angular velocity. During the initialization phase of about 1 second, the raw attitude data of all sensing elements are output at a frequency of 1Hz. After completing UTC time synchronization, the output frequency is switched to the highest 200Hz.

[0062] Step 3: Calibrate the original attitude data.

[0063] The collected raw attitude data is input into the preset calibration environment. Based on the pre-built temperature error compensation data table, the error parameters corresponding to the current working temperature are obtained by interpolation or table lookup to complete the first correction. Then, Kalman filtering optimization is used, and the error parameters are iteratively optimized by combining GPS device observations to complete the second correction. Finally, the calibration parameters are substituted into the preset acceleration error model and angular velocity error model to calculate the calibration attitude data.

[0064] Step 4: Does it exceed the preset accuracy threshold?

[0065] The calibration attitude data output by each inertial measurement unit is monitored in real time. The calibration attitude data is compared with the preset accuracy threshold to determine whether the calibration data exceeds the threshold. If the data exceeds the threshold, it must continue for no less than the preset sampling period to filter out instantaneous interference.

[0066] Step 5: If not (accuracy threshold not exceeded), then enter normal output mode.

[0067] If the calibration attitude data does not exceed the preset accuracy threshold, it is determined to be a normal accuracy requirement and enters the normal output mode. In this mode, no fusion calculation is required, and any calibration attitude data or original attitude data that meets the preset threshold is directly output. The output data source can be modified online via CAN bus and keeps consistent with the current data update frequency to ensure the real-time performance and reliability of data in normal agricultural machinery operation scenarios.

[0068] Step 6: If it exceeds the accuracy threshold, then enter the fusion output mode.

[0069] If the calibrated attitude data continuously exceeds the preset accuracy threshold, it is determined to be a high-precision requirement, and the system automatically enters the fusion output mode. In this mode, the calibrated attitude data is continuously collected, and the attitude quaternion update, coordinate transformation, acceleration correction and integral calculation are completed in sequence to obtain the position, speed and attitude status parameters of the agricultural machinery. Then, based on the error evaluation results of the calibration parameters of each sensor element and the above status parameters, the weights are dynamically adjusted, and the weighted fusion is performed through the fusion formula to output fused attitude data that takes into account both accuracy and adaptability.

[0070] Based on the above steps, the present invention precisely achieves its goals of improving the measurement accuracy of agricultural machinery attitude data, adapting to complex operating conditions, and ensuring data real-time performance and reliability. Regarding accuracy improvement, a two-stage calibration process offsets zero-bias drift caused by temperature fluctuations and noise interference from agricultural machinery vibrations. Combined with integral processing and dynamic weighted fusion calculation in the fusion output mode, the attitude data measurement error is significantly reduced, fully meeting the high-precision operation requirements of complex conditions such as grader operation and undulating hard ground. Regarding mode adaptation, real-time accuracy threshold monitoring enables intelligent switching between conventional accuracy and fusion output modes. The conventional mode directly outputs calibration data to adapt to simple operating conditions such as flat ground, while the fusion output mode outputs fused data to adapt to complex operating conditions, balancing data processing efficiency and measurement accuracy. Regarding real-time performance, the system supports a flexibly adjustable update frequency from 1Hz to 200Hz, with a maximum of 200Hz. High-frequency output can accurately capture instantaneous attitude changes of agricultural machinery, and mode switching and fault sensor switching are completed within 2.5ms without data interruption. In terms of reliability, through chip self-testing, real-time monitoring of the operating status of all sensors, and redundancy switching mechanism, system failure caused by the failure of a single or multiple sensors is avoided, ensuring continuous data output throughout the entire agricultural machinery operation. At the same time, the data update frequency, accuracy threshold, and output data source all support online adjustment via CAN bus, adapting to different types of agricultural machinery and operating scenarios, and possessing practicality and compatibility.

[0071] The foregoing has provided a detailed explanation of the implementation process and principle of an agricultural machinery attitude sensor measurement method provided in the embodiments of this application. The following will further describe the agricultural machinery attitude sensor measurement method system, medium, product, and terminal of the present invention in conjunction with embodiments.

[0072] Similar in principle to the above embodiments, the present invention provides an agricultural machinery attitude sensor measurement system.

[0073] like Figure 3 A schematic diagram of the structure of an agricultural machinery attitude sensor measurement system according to an embodiment of the present invention is shown.

[0074] The system 300 includes:

[0075] The data acquisition module 301 is used to acquire the original attitude data measured by each inertial measurement unit, calibrate the original attitude data, and obtain calibrated attitude data.

[0076] The data output module 302 is used to generate the final attitude data based on each calibration attitude data using either a fusion output mode or a conventional output mode.

[0077] Since the implementation principle of the agricultural machinery attitude sensor measurement system has been described in the foregoing embodiments, it will not be repeated here. It should also be understood that the module division in the embodiments of this application is illustrative and only represents a logical functional division; other division methods may be used in actual implementation. Furthermore, the functional modules in the various embodiments of this application can be integrated into a single processor, exist as separate physical entities, or have two or more modules integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0078] This invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the methods described above.

[0079] This invention provides a computer program product, which includes computer program code. When the computer program code is run on a computer, the computer performs the method described in any of the preceding claims.

[0080] The agricultural machinery attitude sensor measurement method provided in this embodiment of the invention can be implemented on the terminal side or the server side. Regarding the hardware structure of the electronic terminal, please refer to... Figure 4 This is a schematic diagram of an optional hardware structure of an electronic terminal 4000 provided in an embodiment of the present invention. The terminal 4000 can be a mobile phone, computer device, tablet device, personal digital processing device, factory back-end processing device, etc. The terminal 4000 includes: at least one processor 4001, a memory 4002, at least one network interface 40010, and a user interface 4009. The various components in the device are coupled together through a bus system 4005. It is understood that the bus system 4005 is used to realize the connection and communication between these components. In addition to a data bus, the bus system 4005 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 4 The general will label all buses as bus systems.

[0081] The user interface 4009 may include a monitor, keyboard, mouse, trackball, clicker, button, touchpad, or touch screen.

[0082] It is understood that memory 4002 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM) or programmable read-only memory (PROM), which serves as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM) and synchronous static random access memory (SSRAM). The memories described in the embodiments of this invention are intended to include, but are not limited to, these and any other suitable categories of memory.

[0083] In this embodiment of the invention, the memory 4002 is used to store various types of data to support the operation of the terminal 4000. Examples of this data include: any executable program for operation on the terminal 4000, such as the operating system 40021 and application program 40022; the operating system 40021 contains various system programs, such as the framework layer, core library layer, driver layer, etc., for implementing various basic services and handling hardware-based tasks. The application program 40022 may contain various applications, such as media players, browsers, etc., for implementing various application services. The agricultural machinery attitude sensor measurement method provided in this embodiment of the invention can be included in the application program 40022.

[0084] The methods disclosed in the above embodiments of the present invention can be applied to, or implemented by, processor 4001. Processor 4001 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above methods can be completed by integrated logic circuits in the hardware of processor 4001 or by instructions in software form. Processor 4001 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 4001 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. General-purpose processor 4001 may be a microprocessor or any conventional processor, etc. The steps of the accessory optimization method provided in the embodiments of the present invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in a memory. The processor reads information from the memory and, in conjunction with its hardware, completes the steps of the aforementioned methods.

[0085] In an exemplary embodiment, the terminal 4000 may be used by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), or complex programmable logic devices (CPLDs) to execute the aforementioned method.

[0086] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented using computer program-related hardware. The aforementioned computer program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0087] In the embodiments provided in this application, the computer-readable and writable storage medium may include read-only memory, random access memory, EEPROM, CD-ROM or other optical disc storage devices, disk storage devices or other magnetic storage devices, flash memory, USB flash drive, portable hard drive, or any other medium capable of storing desired program code in the form of instructions or data structures and accessible by a computer. Additionally, any connection may be appropriately referred to as a computer-readable medium. For example, if instructions are transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. However, it should be understood that computer-readable and writable storage media and data storage media do not include connections, carrier waves, signals, or other transient media, but are intended for non-transient, tangible storage media. The disks and optical discs used in the application include compact optical discs (CDs), laser optical discs, optical discs, digital multifunction optical discs (DVDs), floppy disks, and Blu-ray discs, where disks typically copy data magnetically, while optical discs use lasers to copy data optically.

[0088] In summary, this invention provides a method, system, medium, product, and terminal for measuring the attitude of agricultural machinery using an attitude sensor. It offers the following advantages: The invention obtains raw attitude data measured by each inertial measurement unit (IMU), calibrates the raw attitude data to obtain calibrated attitude data, selects an output mode based on measurement requirements, performs fusion calculations on the calibrated attitude data to obtain and output fused attitude data if the fusion output mode is entered, and directly outputs either the calibrated attitude data or the raw attitude data if the conventional output mode is entered. This invention overcomes the high-precision requirements of slow tillage and the large-range requirements of rapid obstacle avoidance in agricultural machinery, adapts to complex agricultural environments, features high-frequency output, intelligent switching, and multi-component redundant fusion capabilities, and effectively addresses special working conditions such as complex vibrations and electromagnetic interference in farmland.

[0089] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for measuring the attitude of agricultural machinery using a posture sensor, characterized in that, The method includes: Obtain the raw attitude data measured by each inertial measurement unit, calibrate each raw attitude data, and obtain the corresponding calibrated attitude data; The final attitude data is output using either a fusion output mode or a regular output mode based on the various calibration attitude data.

2. The method for measuring the attitude of agricultural machinery using a sensor according to claim 1, characterized in that, The fusion output mode includes: performing fusion calculations on each calibration attitude data to obtain fused attitude data and outputting it as the final attitude data.

3. The method for measuring the attitude of agricultural machinery using a sensor according to claim 2, characterized in that, The process of fusing the calibration attitude data to obtain the fused attitude data includes: Based on the calibration parameters corresponding to each calibration attitude data, the calculation weights corresponding to each inertial measurement unit are determined. The calibrated attitude data are weighted and fused using the calculated weights to obtain the fused attitude data.

4. The method for measuring the attitude of agricultural machinery using a sensor according to claim 1, characterized in that, The standard output modes include: Each original attitude data or each calibrated attitude data is output as the final attitude data.

5. The method for measuring the attitude of agricultural machinery using a sensor according to claim 1, characterized in that, The calibration of each original attitude data includes: The original attitude data is input into the preset calibration platform. Based on the pre-built temperature error compensation data table and fusion filtering algorithm, the calibration parameters are calculated from the original attitude data. The calibration parameters and the original attitude data are then input into the preset error model to obtain the calibration attitude data.

6. The method for measuring the attitude of agricultural machinery using a sensor according to claim 1, characterized in that, The method further includes: The calibration attitude data corresponding to each inertial measurement unit is monitored in real time, among which, If the calibration attitude data is detected to be within the preset accuracy threshold range, then the normal output mode is adopted; If the calibration attitude data is detected to exceed the preset accuracy threshold range, the fusion output mode is adopted.

7. A measurement system for agricultural machinery attitude sensors, characterized in that, The system includes: The data acquisition module is used to obtain the raw attitude data measured by each inertial measurement unit, calibrate each raw attitude data, and obtain the corresponding calibrated attitude data. The data output module is used to output the final attitude data based on each calibration attitude data in either a fusion output mode or a regular output mode.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

9. A computer program product, characterized in that, The computer program product includes computer program code that, when run on a computer, causes the computer to implement the method as described in any one of claims 1 to 6.

10. An electronic terminal, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the method according to any one of claims 1 to 6.

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