Agricultural machinery path tracking method and device based on LOS guidance, medium and program

Abstract

The invention provides an agricultural machinery path tracking method and device based on LOS guidance, a medium and a program, and the method comprises the steps: converting a path tracking problem into a tracking problem of an expected course angle through employing an LOS guidance method, and solving the expected course angle; and then based on a sliding mode control algorithm, solving a front wheel steering angle of the agricultural machine to control the agricultural machine. According to the agricultural machine path tracking method, the characteristics of high robustness and quick response of sliding mode control are utilized, under the condition that the control system has uncertainty and interference, it is guaranteed that the whole control system can operate stably, and the problem of system unknown interference caused by agricultural machine sideslip and the like is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of automatic driving of agricultural machinery, and specifically relates to a method, device, medium and program for path tracking of agricultural machinery based on LOS guidance. Background Art

[0002] With the continuous advancement of science and technology, the agricultural field is developing rapidly towards automation and intelligence. As a key component of this, agricultural machinery autonomous driving technology can significantly improve agricultural production efficiency, reduce labor intensity, and improve operation quality, which is of great significance for the realization of precision agriculture. Through precise path tracking, agricultural machinery can perform operations such as transplanting, sowing, fertilizing, and harvesting in the farmland to ensure consistency and accuracy of operations, thereby increasing crop yield and quality while reducing resource waste.

[0003] Current agricultural machinery path tracking technology still faces many challenges. Traditional path tracking algorithms show obvious shortcomings when facing the complex and changeable environment of farmland. On the one hand, the farmland terrain is complex and diverse, with irregular terrain such as slopes and potholes, which makes agricultural machinery susceptible to longitudinal and lateral forces during driving, resulting in path deviation. On the other hand, differences in soil conditions, such as unevenness in softness and humidity, can cause agricultural machinery to skid, thereby affecting its speed control and path tracking stability. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method, device, medium and program for path tracking of agricultural machinery based on LOS guidance, so as to solve the problem of unknown interference of the system caused by side slip of agricultural machinery.

[0005] The present invention achieves the above technical objectives through the following technical means.

[0006] A path tracking method for agricultural machinery based on LOS guidance:

[0007] Step 1: Use the LOS guidance method to solve the desired heading angle ψ d ;

[0008] Step 2: According to the desired heading angle ψ d , the adaptive fuzzy sliding mode control algorithm is used to solve the front wheel steering angle δ of the agricultural machinery f , used to control the steering of the front wheels of agricultural machinery.

[0009] Furthermore, in step 2, the adaptive fuzzy sliding mode control law of the front wheel steering angle is:

[0010]

[0011] The sliding surface s is defined as:

[0012]

[0013] In the formula, η1 and η2 are constants greater than zero, and are the estimated values of θ * and E respectively, and there is is the ideal value of the front wheel steering angle, θ * = [θ1, θ2, …, θ m T is the parameter vector, ζ(s) = [ζ1, ζ2, …, ζ m T is the fuzzy vector, ε is the fuzzy approximation error, |ε| < E, E represents the upper limit value of ε; k2 and k3 are constants greater than zero, ψ e = ψ d - ψ is the course angle deviation, ψ is the actual course angle of the agricultural machinery, τ is the time variable, ψ e (τ) is the function of ψ e with respect to the time τ, and t represents the current moment.

[0014] Furthermore, in the fuzzy vector ζ(s):

[0015]

[0016] In the formula, ω i is the weight of the fuzzy rule.

[0017] Furthermore, the membership function of the weight ω i with respect to s is:

[0018]

[0019] In the formula, c i is the center of the i-th rule, and σ i is the standard deviation of the i-th rule.

[0020] Furthermore, in the step 1, the functional formula of the desired course angle is:

[0021]

[0022] In the formula, χ p = arctan2(x ′ p (μ), y ′ p (μ)) is the path tangential angle of the desired path, and the ground coordinates of the actual position and the desired position of the agricultural machinery at the current moment are (x, y) and (x p (μ), y p ​​(μ)), μ is the path parameter, and the distance tracking error between the two positions along the two coordinate axes in the SF coordinate system is x e and e , Δ is the foresight distance.

[0023] Furthermore, the following two extended state observers are used to compensate for the sideslip angle in the process of solving the desired heading angle:

[0024]

[0025] In the formula, and They are the longitudinal speed of the agricultural machinery v x and the lateral velocity v y The estimated value of and are the auxiliary states of the above two state observers, k1 is the observer gain, is the speed of the agricultural machinery at the actual position;

[0026] The expected heading angle function after compensating the sideslip angle is:

[0027]

[0028] In the formula, is the estimated value of the sideslip angle of the agricultural machinery, k y To control the gain;

[0029] The adaptive update law of the path parameter μ is:

[0030]

[0031] k x is the control gain and is a positive value.

[0032] Furthermore, the foresight distance is adjusted as follows:

[0033]

[0034] In the formula, Δ max and Δ min are the upper and lower limits of the foresight distance Δ respectively.

[0035] A computer device comprising a memory and a processor;

[0036] The memory is used to store computer programs;

[0037] The processor is used to execute the computer program and implement the above-mentioned agricultural machinery path tracking method based on LOS guidance when executing the computer program.

[0038] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor executes the above-mentioned agricultural machinery path tracking method based on LOS guidance.

[0039] A computer program product includes a computer program, and when the computer program is executed by a processor, the above-mentioned agricultural machinery path tracking method based on LOS guidance is implemented.

[0040] The beneficial effects of the present invention are:

[0041] (1) The present invention provides a path tracking method for agricultural machinery based on LOS guidance. Through the LOS guidance method, the path tracking problem is converted into a tracking problem of a desired heading angle. Then, based on an adaptive fuzzy sliding mode control algorithm, the strong robustness and fast response characteristics of the sliding mode control are utilized to ensure that the entire control system can operate stably in the presence of uncertainty and interference in the control system, thereby solving the problem of unknown interference to the system caused by agricultural machinery side slipping.

[0042] (2) Aiming at the problem of tracking the desired heading angle, the present invention designs an adaptive fuzzy sliding mode control law for the corresponding front wheel steering angle based on the constructed two-degree-of-freedom dynamics model of agricultural machinery. On the one hand, it effectively improves the response speed of agricultural machinery path tracking; on the other hand, it reduces the oscillation and error caused by factors such as terrain undulations and changes in soil conditions during the driving process of agricultural machinery through the compensation effect of the switching characteristics of the sliding mode control, thereby greatly improving the robustness to interference and ensuring the continuity and accuracy of agricultural machinery operations.

[0043] (3) In order to solve the problem that the tracking effect of the traditional LOS guidance method deteriorates when the curvature of the target trajectory changes greatly, the present invention uses the SF coordinate system to describe the expected path, thereby designing a LOS guidance method suitable for curve tracking.

[0044] (4) In order to solve the problem of sideslip of agricultural machinery in slippery farmland, the present invention designs two extended state observers in the LOS guidance method to estimate the longitudinal speed and lateral speed of the agricultural machinery in real time, and then compensate for the sideslip angle that may be generated by the agricultural machinery.

[0045] (5) In view of the limitations of the fixed forward-looking distance in the traditional LOS guidance method, such as when the lateral deviation is large in the initial stage of path tracking, the convergence may be slow; and when approaching the reference path, the fixed forward-looking distance may cause tracking problems such as oscillation and jitter. In this regard, the present invention proposes a method for online adjusting the forward-looking distance based on the size of the lateral deviation, wherein when the agricultural machinery deviates greatly from the preset path, the convergence speed is accelerated by adjusting the forward-looking distance. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1This is a flowchart of the path tracking method according to an embodiment of the present application;

[0047] Figure 2 A geometric diagram of a reference path tracked by an extended LOS guidance method for an embodiment of the present application;

[0048] Figure 3 A schematic diagram of a two-degree-of-freedom dynamic model of an agricultural machine according to an embodiment of the present application;

[0049] Figure 4 The expected path tracking result of the simulation test of the embodiment of the present application;

[0050] Figure 5 This is the lateral deviation of the path tracking process simulated in the embodiment of the present application. DETAILED DESCRIPTION

[0051] Embodiments of the present invention are described in detail below, examples of the illustrated embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0052] 1. Technical solution

[0053] The LOS (Line-of-sight) guidance method has a simple principle and strong versatility. It can be applied to aerospace, missiles, vehicles, ships, drones and other fields, and can transform the path tracking problem into the tracking problem of the desired heading angle. Therefore, this embodiment adopts the following improved LOS guidance method to solve the heading angle of the agricultural machinery.

[0054] like Figure 1 As shown in FIG. 1 , firstly, the navigation unit and sensor installed on the agricultural machinery are used to obtain the position information and path information of the agricultural machinery, and used as the input of the entire control algorithm; then, the heading angle (desired heading angle) ψ required to track the desired path is calculated in real time based on the extended LOS guidance method. d , and then the desired heading angle ψ d Output to the adaptive fuzzy sliding mode controller; the adaptive fuzzy sliding mode controller is designed based on the agricultural machinery dynamics model to calculate the agricultural machinery front wheel steering angle δ f , to achieve tracking control of the agricultural machinery's driving path. The details are as follows:

[0055] 1. Position parameter definition

[0056] 1) If Figure 2 As shown, O g X g Y gis the ground coordinate system {G}, point M represents the actual center of mass position of the agricultural machinery at the current moment, and its position coordinates are (x, y); the curve marked by "path" in the figure is the expected path of the agricultural machinery, and point O p It represents the expected center of mass position of the agricultural machinery at the current moment, and its position coordinate is (x p (μ),y p (μ)), where μ is the path parameter, x p (μ) and y p (μ) is twice differentiable with respect to μ.

[0057] Therefore, the path tangent angle of the desired path is:

[0058] χ p =arctan2(x ′ p (μ),y ′ p (μ)) (1)

[0059] In the formula,

[0060] 2) Based on the LOS guidance method, the SF coordinate system (Serret-Frenet coordinate system) is established. p X p Y p}, the corresponding transformation matrix T between the ground coordinate system {G} and the SF coordinate system {P} pg for:

[0061]

[0062] 3) From the actual position of the agricultural machinery M to the expected position O p The tracking error between the distances is p Axis and Y p The components of the axes are x e and e ;Depend on Figure 2 The tracking error expression is:

[0063]

[0064] 4), taking the derivative of both ends of the equation (3) yields:

[0065]

[0066] In the formula, represents the speed of the agricultural machinery at the position point M, ψ is the actual heading angle of the agricultural machinery, and v x and v y Represent the longitudinal speed and lateral speed of the agricultural machinery respectively.

[0067] 5) To achieve the tracking of the desired path by the agricultural machinery, the actual heading angle ψ of the agricultural machinery must be equal to the desired heading angle ψ d ,according to Figure 2 You can get:

[0068]

[0069] In the formula, ψ d is the expected heading angle of the agricultural machinery, is the sideslip angle of the agricultural machinery, Δ is the forward distance, χ r It is the angle between the direction from the actual position of the center of mass point M to the foresight point and the tangent direction of the expected path.

[0070] 2. Extended LOS guidance method

[0071] 1), assuming that the agricultural machine can perfectly track the expected heading angle during the path tracking process, formula (4) can be expressed as:

[0072]

[0073] 2), the following two extended state observers are proposed to estimate the speed v x and v y :

[0074]

[0075] as well as

[0076]

[0077] In the formula, and They are v x and v y The estimated value of and are the auxiliary states of the above two state observers, and k1 is the observer gain.

[0078] 3), speed estimate and With the actual value v x and v y The error between them is:

[0079]

[0080] In the formula, represents the longitudinal velocity estimation error of the agricultural machinery, Represents the lateral velocity estimation error of the agricultural machinery.

[0081] 4), combined with formulas (6), (7), and (8), the derivative of formula (9) yields:

[0082]

[0083] 5) Substituting formula (9) into formula (6) yields:

[0084]

[0085] 6) In summary, the extended LOS guidance system consists of formulas (10) and (11). To make the system input stable, the update formula of the desired heading angle is:

[0086]

[0087] Among them, the adaptive update law of the path parameter μ is:

[0088]

[0089] In the formula, k x and k y is the adjustable control gain, where k x is a positive value, Δ max and Δ min are the upper and lower limits of the forward viewing distance Δ, respectively. In this embodiment, Δ max Take 8 times the wheelbase (the distance from the front axle to the rear axle of the agricultural machinery), Δ min Take 4 times the wheelbase.

[0090] 3. Adaptive fuzzy sliding mode control law

[0091] 1), considering that complex working environments will cause strong interference to the driving state of agricultural machinery, this embodiment establishes an agricultural machinery dynamics model suitable for complex working conditions. In order to improve the real-time performance of the control system and reduce the amount of calculation of the controller, this embodiment makes the following assumptions: ① only consider the yaw and lateral movements of the agricultural machinery, ② the steering angles of the left and right wheels are equal when the front wheels of the agricultural machinery are turned, ③ ignore the load transfer and aerodynamic effects; thus simplifying the obtained Figure 3 The two-degree-of-freedom agricultural machinery model shown.

[0092] According to Newton's second law, the dynamic analysis of the two-degree-of-freedom agricultural machinery model is carried out:

[0093]

[0094] Where r is the yaw rate of the agricultural machine, δ f is the front wheel steering angle of the agricultural machinery, F yf and F xf are the lateral force and longitudinal force on the front wheels of the agricultural machinery, respectively, and F yr is the lateral force on the rear wheel of the agricultural machinery, l fis the distance from the front wheel axle of the agricultural machinery to the center of mass, l r is the distance from the rear wheel axle of the agricultural machinery to the center of mass, I z is the moment of inertia of the Z axis (the axis perpendicular to the ground), and m is the mass of the agricultural machinery.

[0095] 2), considering that the agricultural machinery involved in this embodiment is in the process of path tracking, F yf and F yr Both act in the linear region, so the linear relationship between the lateral force and the sideslip angle can be obtained as follows:

[0096]

[0097] In the formula, α f and α r are the side slip angles of the front and rear wheels of the agricultural machinery, C f and C r are the cornering stiffness of the front and rear wheels of the agricultural machinery respectively.

[0098] 3), combined with the small angle approximation method, α f and α r The calculation formula is:

[0099]

[0100] 4), the state space equation of the agricultural machinery dynamics model is obtained from formulas (14) to (16):

[0101]

[0102] 5) Based on the purpose of path tracking, only the lateral and yaw movements of the agricultural machinery are considered. Based on the relationship between the heading angle and the heading angular rate, combined with the dynamic model of the agricultural machinery, the following state equation can be obtained:

[0103]

[0104] In the formula, Q = [v y ,r] T , t is the time variable, indicating the current moment, f(Q, t) is a function of Q and t, and the specific expression is obtained by formula (17).

[0105] 6), from formula (18):

[0106]

[0107] 7), based on the linear feedback control principle, the control law of the front wheel steering angle of the agricultural machinery is:

[0108]

[0109] In the formula, Denote the ideal value of the front wheel steering angle δ as ψ f , ψ e =ψ d -ψ is the heading angle deviation, and k2 and k3 are constants greater than zero.

[0110] 8), since the lateral velocity v of the agricultural machinery y is difficult to measure in practice, it is difficult to solve the front wheel steering angle control law shown in formula (20). To solve the above problems, according to the universal approximation property of the fuzzy system, there exists an optimal fuzzy control system θ *T ζ(s) such that the control law of the front wheel steering angle is:

[0111]

[0112] where ε is the fuzzy approximation error, and |ε| < E, E represents the upper limit value of ε; θ * =[θ1,θ2,…,θ m T is the parameter vector, ζ = ζ(s) = [ζ1,ζ2,…,ζ m T is the fuzzy vector, where:

[0113]

[0114] ω i is the weight of the fuzzy rule, which is a variable about s, used to represent the membership degree of the sliding mode surface s corresponding to the i-th fuzzy rule, and the corresponding membership function is denoted as ω i =ω i (s):

[0115]

[0116] where c i is the center of the i-th rule, and σ i is the standard deviation of the i-th rule. In addition to the membership functions of the above specific examples, other types of membership functions can also be used.

[0117] 9), define the sliding mode surface as:

[0118]

[0119] where τ is the time variable, and ψ e (τ) is the function of ψ e changing with time τ.

[0120] 10), based on the above sliding mode surface, the adaptive fuzzy sliding mode control law of the front wheel steering angle is designed as follows:

[0121] ​​

[0122] In the formula, and They are θ * and the estimated values ​​of E, η1 and η2 are constants greater than zero; for the current moment and Specifically, it can be obtained by iterating the initial value at each moment, that is, Δt is the time span between two moments.

[0123] In summary, refer to Figure 1 As shown, the path tracking method of the present invention is implemented in the following steps:

[0124] Step 0: Input the path and vehicle driving information, including the expected position coordinates of the agricultural machinery at the current moment (x p (μ),y p (μ)), the actual position coordinates of the agricultural machinery (x, y), the deviation between the actual position and the expected position in the SF coordinate system (x e ,y e ) and the actual heading angle ψ of the agricultural machinery.

[0125] Step 1: Based on the input information, the extended LOS guidance method proposed in the above embodiment is used to obtain the desired heading angle ψ d .

[0126] Step 1.1: Based on the two proposed extended state observers (corresponding to formulas (7) and (8)), the estimated longitudinal speed of the agricultural machinery is obtained: and lateral velocity estimates Used to solve the sideslip angle of agricultural machinery to compensate the heading angle;

[0127] Step 1.2: According to the extended LOS guidance method (Formula (12)), the desired heading angle ψ is solved: d .

[0128] Step 2: According to the desired heading angle ψ d Based on the adaptive fuzzy sliding mode control law proposed above (corresponding to formula (23)), the steering angle of the front wheel of the agricultural machinery δ is solved f .

[0129] Step 3: According to the front wheel steering angle δ f , to regulate the steering action of the front wheels of the agricultural machinery; then the vehicle driving information fed back by the agricultural machinery at the next moment and the path information planned by the navigation unit are used as input to carry out the next round of path tracking.

[0130] 2. Testing

[0131] In order to verify the effectiveness of the path tracking method designed in the above embodiment, a simulation test was built using the Euler discretization method in the Matlab 2021b environment. The simulation step size was set to 0.01s, the simulation time was 40s, the operating speed was 1m / s, and the initial lateral deviation was 4m. The test results were compared with the Stanley control algorithm. Figure 4 and Figure 5 shown.

[0132] Figure 4 The expected path tracking result is shown. Figure 5 The figure shows the lateral deviation of the path tracking process. Since the present invention introduces adaptive fuzzy theory and uses an extended state observer to compensate for the sideslip angle, it has a faster on-line speed under the same lateral deviation compared to the traditional Stanley control algorithm, and the on-line speed is specifically increased by 23.9%. When the vehicle is quickly on-line, the overshoot of the lateral deviation of the present invention is also significantly reduced, specifically by 38.3%; after entering the steady state, the steady-state tracking accuracy of the control method of this invention is improved by 15.5%.

[0133] III. Devices, Storage Media, and Program Products

[0134] 1. Based on the same inventive concept as the above-mentioned LOS-guided agricultural machinery path tracking method, the present application also provides an electronic device, which includes a processor and a memory, in which a computer-readable code is stored. When the computer-readable code is executed by the processor, the LOS-guided agricultural machinery path tracking method of the present invention is implemented.

[0135] The memory includes a non-volatile storage medium and an internal memory; the non-volatile storage medium can store an operating system and a computer-readable code. The computer-readable code includes program instructions, which, when executed, can enable the processor to execute a path tracking method for agricultural machinery based on LOS guidance. The processor is used to provide computing and control capabilities to support the operation of the entire electronic device. The memory provides an environment for the operation of the computer-readable code in the non-volatile storage medium, and when the computer-readable code is executed by the processor, the processor can execute a path tracking method for agricultural machinery based on LOS guidance.

[0136] It should be understood that the processor may be a central processing unit, other general-purpose processors, digital signal processors, application-specific integrated circuits, field programmable gate arrays or other programmable logic devices, transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or any conventional processor.

[0137] 2. The present application also provides a readable storage medium, which may be an internal storage unit of the electronic device described in the aforementioned embodiment, such as a hard disk or memory of the computer device. The readable storage medium may also be an external storage device of the electronic device, such as a plug-in hard disk, smart memory card, secure digital card, etc. equipped on the electronic device.

[0138] 3. The present application also provides a computer program product, including a computer program or instructions, which, when executed by a processor, implements the LOS-guided agricultural machinery path tracking method of the present invention.

[0139] In the description of the present invention, it should be understood that the terms "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside" and "outside" etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0140] The present invention is not limited to the above-mentioned embodiments. Any obvious improvement, substitution or deformation that can be made by those skilled in the art without departing from the essential content of the present invention belongs to the protection scope of the present invention.

Claims

1. A path tracking method for agricultural machinery based on LOS guidance, characterized in that: Step 1: Use the LOS guidance method to solve the desired heading angle ψ d ; Step 2: According to the desired heading angle ψ d , the adaptive fuzzy sliding mode control algorithm is used to solve the front wheel steering angle δ of the agricultural machinery f , used to control the steering of the front wheels of agricultural machinery.

2. The method for tracking agricultural machinery path based on LOS guidance according to claim 1, characterized in that: In step 2, the adaptive fuzzy sliding mode control law of the front wheel steering angle is: Among them, the sliding surface s is defined as: where η1 and η2 are constants greater than zero, and are the estimated values of θ * and E respectively, and there are is the ideal value of the front-wheel steering angle, θ * =[θ1,θ2,…,θ m T is the parameter vector, ζ(s)=[ζ1,ζ2,…,ζ m T is the fuzzy vector, ε is the fuzzy approximation error, |ε|<E, E represents the upper limit value of ε; k2 and k3 are constants greater than zero, ψ e =ψ d -ψ is the course angle deviation, ψ is the actual course angle of the agricultural machine, τ is the time variable, ψ e (τ) is the function of ψ e with respect to the time τ, and t represents the current moment.​​ 3. The method for tracking agricultural machinery path based on LOS guidance according to claim 2, characterized in that: In the fuzzy vector ζ(s): In the formula, ω i is the weight of the fuzzy rule.

4. The method for tracking agricultural machinery path based on LOS guidance according to claim 3, characterized in that: Weight ω i The membership function of s is: In the formula, c i is the center of the ith rule, σ i is the standard deviation of the ith rule.

5. The method for tracking agricultural machinery path based on LOS guidance according to claim 1, characterized in that: In step 1, the function of the expected heading angle is: In the formula, χ p =arctan2(x ′ p (μ),y ′ p (μ)) is the path tangent angle of the expected path. The ground coordinates of the actual position and the expected position of the agricultural machinery at the current moment are (x, y), (x p (μ),y p (μ)), μ is the path parameter, and the distance tracking error between the two positions along the two coordinate axes in the SF coordinate system is x e and e , Δ is the foresight distance.

6. The method for tracking the path of agricultural machinery based on LOS guidance according to claim 5, characterized in that: The following two extended state observers are used to compensate for the sideslip angle in the process of solving the desired heading angle: In the formula, and They are the longitudinal speed of the agricultural machinery v x and the lateral velocity v y The estimated value of and are the auxiliary states of the above two state observers, k1 is the observer gain, is the speed of the agricultural machinery at the actual position; The expected heading angle function after compensating the sideslip angle is: In the formula, is the estimated value of the sideslip angle of the agricultural machinery, k y To control the gain; The adaptive update law of the path parameter μ is: k x is the control gain and is a positive value.

7. The method for tracking agricultural machinery path based on LOS guidance according to claim 5, characterized in that: The foresight distance is adjusted as follows: In the formula, Δ max and Δ min are the upper and lower limits of the foresight distance Δ respectively.

8. A computer device, characterized in that: including memory and processor; The memory is used to store computer programs; The processor is used to execute the computer program and implement the LOS-guided agricultural machinery path tracking method as described in any one of claims 1 to 7 when executing the computer program.

9. A computer-readable storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a processor, the processor executes the agricultural machinery path tracking method based on LOS guidance as described in any one of claims 1 to 7.

10. A computer program product, characterized in that: It comprises a computer program, which, when executed by a processor, implements the path tracking method for agricultural machinery based on LOS guidance as described in any one of claims 1 to 7.

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