A method for navigation control of a tracked vehicle and related apparatus

Abstract

The application discloses a navigation control method and related device of a tracked vehicle, and relates to the field of automatic driving control. A discretization error tracking model is used to build a linear relationship between a discretized form of a pose tracking error vector and a tracked speed error vector, so that the control variable and the state variable are in a linear relationship. Solving the linear problem can obtain the left tracked speed error and the right tracked speed error. The expected value of the left tracked speed is calculated based on the left tracked speed error and the reference value of the left tracked speed, and the expected value of the right tracked speed is calculated based on the right tracked speed error and the reference value of the right tracked speed. The reference value of the bilateral tracked speed is calculated according to the left tracked speed error, the right tracked speed error and the steering curvature of the target reference point on the preset reference path, so that the expected value of the bilateral tracked speed can make the actual driving path of the tracked vehicle approach the reference path. In summary, the scheme improves the adaptability and control accuracy of the navigation control method for the tracked vehicle.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic driving control, and particularly relates to a navigation control method of a tracked vehicle and a related device. BACKGROUND

[0002] A tracked vehicle (referred to as a tracked vehicle) refers to a vehicle that moves by using a track drive. The tracked vehicle has the advantages of large driving force, small ground pressure, good passability, and the like, and can well adapt to special terrains and has been widely applied in the field of agricultural machinery. With the development of sensor, navigation and control technologies, the automatic driving research of agricultural machinery has become a trend. However, the existing navigation system of agricultural machinery is mainly developed for front-wheel steering vehicles, and has poor adaptability to tracked vehicles. Therefore, there is an urgent need for a high-precision navigation control method applied to tracked vehicles. SUMMARY

[0003] In view of the above problems, the present application provides a navigation control method of a tracked vehicle and a related device to achieve the purpose of improving the navigation control precision of the tracked vehicle. The specific scheme is as follows:

[0004] The first aspect of the present application provides a navigation control method of a tracked vehicle, comprising:

[0005] Real-time acquisition of the driving state information of the tracked vehicle, wherein the driving state information comprises real-time pose information and real-time speed information, the real-time pose information comprises real-time values of an X-axis coordinate value and a Y-axis coordinate value and a real-time value of a heading angle in a global coordinate system, and the real-time speed information comprises a real-time value of a driving speed;

[0006] Based on the real-time value of the driving speed and a reference value of a steering curvature, a reference value of a left track speed and a reference value of a right track speed are calculated, wherein the reference value of the steering curvature is a steering curvature of a target reference point on a preset reference path;

[0007] Based on a discretization error tracking model and the driving state information, a left track speed error and a right track speed error are acquired;

[0008] The discretization error tracking model is used to describe the linear relationship between the discrete form of the pose tracking error vector and the track speed error vector, the pose tracking error vector is composed of an X-axis tracking error, a Y-axis tracking error, and a heading angle tracking error, the track speed error vector is composed of a left track speed error and a right track speed error, the X-axis tracking error is a difference between an X-axis coordinate value of the tracked vehicle and an X-axis coordinate value of a target reference point, the Y-axis tracking error is a difference between a Y-axis coordinate value of the tracked vehicle and a Y-axis coordinate value of the target reference point, and the heading angle tracking error is a difference between a heading angle of the tracked vehicle and a heading angle of the target reference point; the left track speed error is a difference between an expected left track speed of the tracked vehicle and a left track speed of the target reference point, and the right track speed error is a difference between an expected right track speed of the tracked vehicle and a right track speed of the target reference point.

[0009] The expected value of the left track speed is calculated based on the left track speed error and a reference value of the left track speed, and the expected value of the right track speed is calculated based on the right track speed error and a reference value of the right track speed.

[0010] The track driving instruction is generated, and the track driving instruction includes the expected value of the left track speed and the expected value of the right track speed.

[0011] In a possible implementation, the navigation control method of the tracked vehicle further includes:

[0012] The original kinematic model of the tracked vehicle is constructed, and the original kinematic model is used to describe the relationship between a pose vector and a track speed vector, wherein the pose vector is composed of an X-axis coordinate value, a Y-axis coordinate value, and a heading angle of the tracked vehicle in a global coordinate system, and the track speed vector is composed of a left track speed and a right track speed of the tracked vehicle.

[0013] The original kinematic model is linearized to construct an error tracking model of the tracked vehicle, and the error tracking model is used to describe the linear relationship between the continuous form of the pose tracking error vector and the track speed error vector.

[0014] The error tracking model is discretized based on a preset sampling time to obtain the discretization error tracking model.

[0015] In a possible implementation, the reference values of the left track speed and the right track speed are calculated based on a real-time value of the driving speed and a reference value of the steering curvature, and the calculation includes:

[0016] Based on the real-time pose information, a target reference point is determined from the reference path, and pose information of the target reference point is obtained.

[0017] calculating distances between the target reference point and reference points located behind the target reference point on the reference path in sequence from near to far until the distance is greater than a preset preview distance threshold, to obtain a preview reference point and a preview distance;

[0018] calculating a reference value of the steering curvature based on pose information of the preview reference point and the target reference point;

[0019] calculating reference values of the left track speed and the right track speed based on structural parameters of the tracked vehicle, a real-time value of the driving speed, and the reference value of the steering curvature.

[0020] In a possible implementation, the left track speed error and the right track speed error are obtained based on a discretized error tracking model and the driving state information, including:

[0021] constructing an LQR performance function based on the discretized error tracking model, and calculating a track speed error vector by using Riccati equation;

[0022] obtaining the left track speed error and the right track speed error based on the driving state information.

[0023] In a possible implementation, the expected value of the left track speed is calculated based on the left track speed error and the reference value of the left track speed, and the expected value of the right track speed is calculated based on the right track speed error and the reference value of the right track speed, including:

[0024] calculating a sum of the reference value of the left track speed and the left track speed error as the expected value of the left track speed;

[0025] calculating a sum of the reference value of the right track speed and the right track speed error as the expected value of the right track speed.

[0026] discretizing the error tracking model based on a preset sampling time to obtain the discretized error tracking model.

[0027] The second aspect of the present application provides a navigation control device of a tracked vehicle, including:

[0028] a driving state monitoring unit configured to obtain driving state information of the tracked vehicle in real time, the driving state information including real-time pose information and real-time speed information, the real-time pose information including a real-time value of an X-axis coordinate value, a real-time value of a Y-axis coordinate value, and a real-time value of a heading angle in a global coordinate system, and the real-time speed information including a real-time value of a driving speed;

[0029] The reference curvature calculation unit is configured to calculate reference values of the left track speed and the right track speed based on a real-time value of the driving speed and a reference value of a steering curvature, the reference value of the steering curvature being a steering curvature of a target reference point on a preset reference path;

[0030] The speed error monitoring unit is configured to obtain left track speed errors and right track speed errors based on a discretized error tracking model and the driving state information.

[0031] The discretized error tracking model is used to describe a linear relationship between a discretized form of a pose tracking error vector and a track speed error vector, the pose tracking error vector being composed of an X-axis tracking error, a Y-axis tracking error, and a heading angle tracking error, the track speed error vector being composed of a left track speed error and a right track speed error, the X-axis tracking error being a difference between an X-axis coordinate value of the track vehicle and an X-axis coordinate value of a target reference point, the Y-axis tracking error being a difference between a Y-axis coordinate value of the track vehicle and a Y-axis coordinate value of the target reference point, and the heading angle tracking error being a difference between a heading angle of the track vehicle and a heading angle of the target reference point; the left track speed error being a difference between a left track speed of the track vehicle and a left track speed of the target reference point, and the right track speed error being a difference between a right track speed of the track vehicle and a right track speed of the target reference point.

[0032] The desired speed prediction unit is configured to calculate a desired value of the left track speed based on the left track speed error and the reference value of the left track speed, and to calculate a desired value of the right track speed based on the right track speed error and the reference value of the right track speed.

[0033] The speed driving unit is configured to generate a track driving instruction, the track driving instruction including the desired value of the left track speed and the desired value of the right track speed.

[0034] In a possible implementation, the navigation control device of the track vehicle further includes a model construction unit configured to

[0035] construct an original kinematic model of the track vehicle, the original kinematic model being used to describe a relationship between a pose vector and a track speed vector, wherein the pose vector is composed of an X-axis coordinate value, a Y-axis coordinate value, and a heading angle of the track vehicle in a global coordinate system, and the track speed vector is composed of a left track speed and a right track speed of the track vehicle.

[0036] linearize the original kinematic model to construct an error tracking model of the track vehicle, the error tracking model being used to describe a linear relationship between a continuous form of the pose tracking error vector and the track speed error vector.

[0037] The third aspect of the present application provides a computer program product, comprising computer readable instructions, which, when executed on an electronic device, cause the electronic device to implement the track vehicle navigation control method of the first aspect or any implementation manner of the first aspect.

[0038] The fourth aspect of the present application provides an electronic device, comprising at least one processor and a memory connected with the processor, wherein:

[0039] The memory is configured to store a computer program;

[0040] The processor is configured to execute the computer program, so that the electronic device can implement the track vehicle navigation control method of the first aspect or any implementation manner of the first aspect.

[0041] The fifth aspect of the present application provides a computer storage medium, which carries one or more computer programs, when the one or more computer programs are executed by an electronic device, can make the electronic device implement the track vehicle navigation control method of the first aspect or any implementation manner of the first aspect.

[0042] By the technical scheme, the navigation control method and related device of the tracked vehicle are provided, the driving state information of the tracked vehicle is acquired in real time, the reference value of the left tracked vehicle speed and the reference value of the right tracked vehicle speed are calculated based on the real-time value of the driving speed and the reference value of the steering curvature, the reference value of the steering curvature is the steering curvature of the target reference point on the preset reference path, the left tracked vehicle speed error and the right tracked vehicle speed error are acquired based on the discretization error tracking model and the driving state information. Since the driving state information includes real-time pose information and real-time speed information, the real-time pose information includes the real-time value of the X-axis coordinate value, the real-time value of the Y-axis coordinate value and the real-time value of the heading angle in the global coordinate system, and the real-time speed information includes the real-time value of the driving speed. The discretization error tracking model is used to describe the linear relationship between the discrete form of the pose tracking error vector and the tracked vehicle speed error vector, the pose tracking error vector is composed of the X-axis tracking error, the Y-axis tracking error and the heading angle tracking error, the tracked vehicle speed error vector is composed of the left tracked vehicle speed error and the right tracked vehicle speed error, the X-axis tracking error is the difference between the X-axis coordinate value of the tracked vehicle and the X-axis coordinate value of the target reference point, the Y-axis tracking error is the difference between the Y-axis coordinate value of the tracked vehicle and the Y-axis coordinate value of the target reference point, and the heading angle tracking error is the difference between the heading angle of the tracked vehicle and the heading angle of the target reference point. The left tracked vehicle speed error is the difference between the left tracked vehicle speed of the tracked vehicle and the left tracked vehicle speed of the target reference point, and the right tracked vehicle speed error is the difference between the right tracked vehicle speed of the tracked vehicle and the right tracked vehicle speed of the target reference point. It can be seen that the discretization error tracking model establishes the linear relationship between the discrete form of the pose tracking error vector and the tracked vehicle speed error vector, so that the control variable and the state variable are in a linear relationship. Therefore, the real-time driving state information is substituted into the discretization error tracking model, and the real-time value of the control variable, i.e., the left tracked vehicle speed error and the right tracked vehicle speed error, can be obtained by solving the linear problem. Further, the expected value of the left tracked vehicle speed is calculated based on the left tracked vehicle speed error and the reference value of the left tracked vehicle speed, and the expected value of the right tracked vehicle speed is calculated based on the right tracked vehicle speed error and the reference value of the right tracked vehicle speed. The tracked vehicle driving instruction is generated, and the tracked vehicle driving instruction includes the expected value of the left tracked vehicle speed and the expected value of the right tracked vehicle speed. Since the reference values of the bilateral tracked vehicle speeds are calculated according to the real-time value of the driving speed and the steering curvature of the target reference point on the preset reference path, the expected values of the bilateral tracked vehicle speeds can make the actual driving path of the tracked vehicle approach the reference path. In summary, the scheme can be applied to all types of tracked vehicles, improve the adaptability of the navigation control method to the tracked vehicle, and improve the navigation control accuracy of the tracked vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0043] The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings. The same or similar components have the same or similar reference labels. It should be understood that the drawings are schematic and elements in the drawings are not necessarily to scale.

[0044] Figure 1 A navigation control method of a tracked vehicle provided for an embodiment of the present application is specifically implemented in a flowchart;

[0045] Figure 2 A turning schematic diagram of a tracked vehicle provided for an embodiment of the present application;

[0046] Figure 3 A left and right turning schematic diagram of a tracked vehicle provided for an embodiment of the present application;

[0047] Figure 4 A flow schematic diagram of a navigation control method of a tracked vehicle provided for an embodiment of the present application;

[0048] Figure 5 A structure schematic diagram of a navigation control device of a tracked vehicle provided for an embodiment of the present application;

[0049] Figure 6 A structure schematic diagram of an electronic device provided for an embodiment of the present application. DETAILED DESCRIPTION

[0050] The embodiments of the present application are described below in conjunction with the drawings of the embodiments of the present application. The terms used in the embodiment part of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.

[0051] The embodiments of the present application are described below in conjunction with the drawings. It is known to those of ordinary skill in the art that, as technology develops and new scenarios appear, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0052] The terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged under appropriate circumstances, and this is only a distinguishing way used in the description of the embodiments of the present application to describe the objects with the same attributes. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, so that the processes, methods, systems, products or devices containing a series of units do not have to be limited to those units, but can include other units that are not clearly listed or inherent to these processes, methods, products or devices.

[0053] A navigation control method applied to a tracked vehicle in the prior art realizes agricultural mechanical path tracking control through fuzzy-PID. Specifically, the method obtains the lateral deviation and the heading deviation of the real-time position and the running track of the target agricultural vehicle by using preview control. When the lateral deviation is in [-0.3m, 0.3m] and the heading deviation is in [-30 degrees, 30 degrees], the lateral deviation and the heading deviation are fitted into an error ERROR by using a linear formula. The error ERROR is input into a PID controller, and the output of the PID controller is used as the front wheel steering angle. However, since the control variable of the method is the front wheel steering angle, the method is only applicable to the navigation control of the tracked vehicle with decoupled lateral and longitudinal directions, and is not applicable to all types of tracked vehicles. In addition, the prior art has poor applicability to different speed conditions, and the straight track tracking effect is acceptable, but the curve tracking effect is poor. At present, the operation mainly targets the AB straight running, but in the use process, some irregular plots, obstacle avoidance, U-turn, and automatic driving along the curve path are required.

[0054] To solve the above problems, the present application proposes to control the speed of the left and right tracks of the tracked vehicle in real time when navigating the tracked vehicle, and to control the steering of the tracked vehicle by controlling the speed of the left and right tracks, thereby controlling the automatic driving of the tracked vehicle along the curve path. Since the navigation control parameters (the speed of the left and right tracks) of the tracked vehicle and the position of the tracked vehicle have a nonlinear relationship, the present application further proposes to introduce an intermediate quantity to linearize the original kinematic model of the tracked vehicle, thereby converting the nonlinear problem into a linear problem. Thus, the present application proposes a navigation control method suitable for all types of tracked vehicles, which improves the curve track tracking control accuracy of the tracked vehicle.

[0055] The navigation control method of the tracked vehicle provided in the embodiments of the present application can be applied in the field of automatic driving control, specifically applied in the tracked vehicle automatic driving scene, tracks the reference path of the tracked vehicle, and based on the current pose information of the tracked vehicle, navigates the tracked vehicle by controlling the track speed of the two tracks, so that the tracked vehicle can automatically drive along the reference path.

[0056] It should be noted that the present method can be applied to the navigation control system configured in the vehicle controller of the tracked vehicle, and the embodiments of the present application provide a specific implementation method of the navigation control method of the tracked vehicle, Figure 1 The navigation control method of the tracked vehicle provided in the embodiments of the present application provides a specific implementation flowchart as shown in Figure 1 The present method specifically includes:

[0057] S101, constructing an original kinematic model of the tracked vehicle.

[0058] In this embodiment, the original kinematic model of the tracked vehicle uses the pose vector as the state vector and the track velocity vector as the control variable. The pose vector is determined by the X-axis coordinate value of the tracked vehicle in the global coordinate system. Y-axis coordinate value and heading angle Composition, denoted as The track velocity vector is formed by the velocities of the left and right tracks of the tracked vehicle, denoted as . .

[0059] Figure 2 This is a schematic diagram of the steering of a tracked vehicle provided in an embodiment of this application. Figure 2 An example is shown: a top view of the track in a geodetic coordinate system (X-Y axis), such as... Figure 2 As shown, the running gear of a tracked vehicle consists of two tracks, referred to as the left track and the right track. The structural parameters of a tracked vehicle include the axle... Track width Track length wheelbase The motion parameters of a tracked vehicle include the speed of the left track. Speed ​​of the right track heading angle The vehicle is in the direction of travel speed on .

[0060] In this embodiment, the original kinematic model is used to describe the pose vector. and track velocity vector The relationship between them. Specifically, the state equation of the original kinematic model of the tracked vehicle is shown in equation (1):

[0061] (1).

[0062] in, This represents the linear velocity of the tracked vehicle along the X-axis in the global coordinate system. The linear velocity of the tracked vehicle in the Y-axis direction in the global coordinate system. This indicates the angular velocity of the tracked vehicle's heading. Indicates the speed of the left track. This indicates the speed of the right track. , , respectively driving speed The rate of change of the X-axis coordinate value, the rate of change of the Y-axis coordinate value, and the rate of change of the heading angle.

[0063] S102. Linearize the original kinematic model to construct an error tracking model for the tracked vehicle.

[0064] In this embodiment, the state equation of the original kinematic model is Taylor expanded at the reference point, and high-order terms are ignored to obtain an error tracking model of the tracked vehicle.

[0065] In this embodiment, in the trajectory tracking research, for a given reference path, each reference point on the reference path satisfies the state equation of the original kinematic model, and the reference point is denoted as The pose information of the reference point includes an X-axis coordinate value in the global coordinate system , a Y-axis coordinate value in the global coordinate system , and a heading angle on the reference path . The velocity information of the reference point includes a left track velocity and a right track velocity .

[0066] In this embodiment, the state vector in the error tracking model is a pose tracking error vector, and the control variable is a track velocity error vector. The pose tracking error vector is composed of an X-axis tracking error, a Y-axis tracking error, and a heading angle tracking error. The X-axis tracking error is the difference between the actual position of the tracked vehicle in the global coordinate system X-axis coordinate value and the X-axis coordinate value of the target reference point. The Y-axis tracking error is the difference between the Y-axis coordinate value of the tracked vehicle in the global coordinate system and the Y-axis coordinate value of the target reference point. The heading angle tracking error is the difference between the heading angle of the tracked vehicle in the global coordinate system and the heading angle of the target reference point. Specifically, the pose tracking error vector is denoted as

[0067] The track velocity error vector is composed of a left track velocity error and a right track velocity error. The left track velocity error is the difference between the left track velocity of the tracked vehicle and the left track velocity of the target reference point. The right track velocity error is the difference between the right track velocity of the tracked vehicle and the right track velocity of the target reference point. Specifically, the track velocity error vector is denoted as .

[0068] In this embodiment, the error tracking model is used to describe the mathematical relationship between the state vector and the control variable . The state equation of the error tracking model is shown in formula (2):

[0069] (2)

[0070] It should be noted that the step linearizes the original kinematics model by constructing an error tracking model, and constructs a new state transition equation about the tracking error, so that it is converted from a nonlinear problem to a linear problem.

[0071] S103, based on the preset sampling time, the error tracking model is discretized to obtain a discretized error tracking model.

[0072] In this embodiment, the error tracking model is discretized using formula (3), and the state equation expression of the discretized error tracking model is shown in formula (3):

[0073] (3)

[0074] Wherein: t represents the time of the discrete form, is the state vector at time t, that is, the pose tracking error vector at time t, is the state vector at time t, that is, the pose tracking error vector at time t, is the state vector at time t, that is, the pose tracking error vector at time t, is the state transition matrix of the error tracking model at time t, that is, the discrete form of the state transition matrix, is the control variable at time t, that is, the track speed error vector at time t, is the discrete form of the control matrix of the discretized error tracking model at time t, and T is the discrete time step, that is, the sampling time interval. Specifically, the discrete forms of the state transition matrix and the control matrix are shown in formulas (4) and (5):

[0075] (4) ;

[0076] (5).

[0077] It should be noted that the scheme constructs the original kinematics model of the tracked vehicle through S101-S103, and linearizes the original kinematics model to obtain the error tracking model. Further, the error tracking model is discretized to obtain a discretized error tracking model, and the discretized error tracking model is deployed in the vehicle controller.

[0078] S104, the running state information of the tracked vehicle is acquired in real time.

[0079] S104, the running state information of the tracked vehicle is acquired in real time.

[0080] ​​In this embodiment, the driving state information includes real-time pose information and real-time speed information, wherein the real-time pose information includes real-time values of X-axis coordinate value, Y-axis coordinate value and heading angle in a global coordinate system and the real-time speed information includes a real-time value of driving speed.

[0081] In this embodiment, the high-precision navigation positioning system installed on the tracked vehicle is built-in with a high-precision positioning orientation board card, which can quickly and accurately calculate the relative position information and azimuth angle of the two antennas. At the same time, through receiving the differential data of the reference station, real-time carrier phase differential positioning can be realized, so as to obtain centimeter-level driving state information.

[0082] S105, determining a target reference point on the reference path based on the real-time pose information of the tracked vehicle, and obtaining the pose information of the target reference point.

[0083] In this embodiment, the reference path is a curved path composed of a plurality of reference points, and the target reference point is the reference point closest to the current position of the tracked vehicle on the reference path.

[0084] In this embodiment, the target reference point is denoted as , wherein represents the X-axis coordinate value of the target reference point, represents the Y-axis coordinate value of the target reference point, represents the heading angle of the target reference point.

[0085] S106, sequentially calculating the distance between the reference points after the target reference point on the reference path and the target reference point until the distance is greater than the preset preview distance threshold, to obtain the preview reference point and the preview distance.

[0086] In this embodiment, the distance between the preview reference point and the target reference point is greater than the preset preview distance threshold, and the distance between the previous reference point of the preview reference point and the target reference point is less than the preview distance threshold , the distance between the preview reference point and the target reference point is taken as the preview distance.

[0087] In this embodiment, the distance between the i-th reference point after the target reference point and the target reference point is calculated using formula (6) :

[0088] (6) ​​​​​​​​

[0089] the (n-1)th reference point after the target reference point is the target reference point , that is, the preview distance .

[0090] S107, calculating the steering curvature of the target reference point on the reference path based on the pose information of the preview reference point and the target reference point as the reference value of the steering curvature.

[0091] In this embodiment, the steering curvature of the target reference point on the reference path, that is, the reference value of the steering curvature, is calculated using formula (7) .

[0092] (7).

[0093] S108, calculating the reference value of the left track speed and the reference value of the right track speed based on the structural parameters of the tracked vehicle, the real-time value of the driving speed and the reference value of the steering curvature.

[0094] In this embodiment, the reference value of the left track speed and the reference value of the right track speed are calculated according to the steering motion model of the tracked vehicle, which is used to describe the relationship between the structural parameters (including the wheelbase and the track width ) of the tracked vehicle, the speed of the two sides of the track, the driving speed and the curvature.

[0095] Figure 3 The left and right steering schematic diagram of the tracked vehicle is shown as follows Figure 3 , when the left track speed is greater than the right track speed, the tracked vehicle realizes right steering, and when the right track speed is greater than the left track speed, the tracked vehicle realizes left steering.

[0096] In this embodiment, the relationship between the structural parameters of the tracked vehicle, the left track speed, the driving speed and the steering curvature can be represented as formula (8):

[0097] (8).

[0098] In this embodiment, the relationship between the structural parameters of the tracked vehicle, the right track speed, the driving speed and the steering curvature can be represented as formula (9):

[0099] (9).

[0100] Specifically, the reference value of the steering curvature , the real-time value of the driving speed , and the structural parameters of the tracked vehicle are substituted into formula (8) and (9) respectively to calculate the reference value of the left track speed and the reference value of the right track speed ​As follows formula (10) and (11):

[0101] (10);

[0102] (11).

[0103] S109, based on the discretization error tracking model, constructing LQR performance function.

[0104] In this embodiment, the LQR (Linear Quadratic Regulator) performance function is as formula (12):

[0105] (12).

[0106] Wherein, is a semi-positive definite symmetric weighted matrix, is a semi-positive definite symmetric weighted matrix, and are the start and end time respectively. Formula (12) is a quadratic function, which represents a comprehensive performance index of control deviation vector (crawler speed error vector) and control smoothness. The performance is the best when the solution result is the smallest. The LQR control parameter is the crawler speed error vector .

[0107] S110, based on the running state information of the tracked vehicle, calculating the LQR control parameter through the Riccati equation to obtain the left crawler speed error and the right crawler speed error.

[0108] In this embodiment, the LQR control parameter is the crawler speed error vector, and the parameter value of the LQR control parameter calculated based on the running state information of the tracked vehicle includes the left crawler speed error and the right crawler speed error in the crawler speed error vector. The Riccati equation is as formula (13):

[0109] (13).

[0110] The LQR control parameter is calculated by formula (14): :

[0111] (14).

[0112] S111, calculating the expected value of the left crawler speed based on the left crawler speed error and the reference value of the left crawler speed.

[0113] In this embodiment, the expected value of the left crawler speed is equal to the reference value of the left crawler speed and the LQR control parameter the left track speed error and, as formula (15):

[0114] (15).

[0115] S112, calculating the expected value of the right track speed based on the right track speed error and the reference value of the right track speed.

[0116] In this embodiment, the expected value of the right track speed is equal to the reference value of the right track speed and the LQR control parameters the left track speed error and, as formula (16):

[0117] (16).

[0118] S113, generating a track driving instruction to control the left track speed to change to the expected value of the left track speed and the right track speed to change to the expected value of the right track speed.

[0119] In this embodiment, the PWM (Pulse Width Modulation) technology is used to control the electromagnetic valve or motor to drive the differential rotation of the left and right wheels of the tracked vehicle, so as to realize the automatic driving control of the tracked vehicle in the curve path tracking.

[0120] As can be seen from the above technical solution, the navigation control method of the tracked vehicle provided by the embodiment of the application can construct a discretization error tracking model, introduce a track speed error vector to construct a linear relationship between the discretized form of the pose tracking error vector and the track speed error vector, so that the control variable and the state variable of the discretized system represented by the model are in a linear relationship. The real-time driving state information is substituted into the discretization error tracking model, and the real-time value of the control variable, i.e. the left track speed error and the right track speed error, can be obtained by solving the linear problem. The scheme can simplify the automatic driving control method of the tracked vehicle in the curve path tracking, improve the navigation control of the tracked vehicle, reduce the calculation amount and hardware requirements, for example, the method is deployed on the NXPLPC4337 to execute, and the time consumption is only 6ms, which improves the navigation control efficiency of the tracked vehicle. The navigation control method of the tracked vehicle provided by the application is deployed on the agricultural navigation product to realize the automatic driving control of the tracked vehicle in the curve path tracking. In the operation below the speed of 10km / h, the root mean square error of the tracking error is calculated, the target tracking accuracy is ±5cm, and the error is small.

[0121] Further, the reference values of the bilateral track speeds are calculated according to the real-time value of the driving speed and the steering curvature of the target reference point on the preset reference path, so that the expected values of the bilateral track speeds can realize that the actual driving path of the tracked vehicle approaches the reference path.

[0122] Further, compared with the traditional three-point calculation curvature method, the calculated curvature fluctuates greatly due to the non-smooth planning path, which causes the unevenness of vehicle control. The present method provides a specific method for calculating the steering curvature of the target reference point based on the preview reference point and the preview distance, improves the smoothness of the steering curvature, and thus ensures the smoothness of vehicle control.

[0123] In summary, the present scheme linearizes the traditional tracked vehicle kinematics model to optimize the solution of the nonlinear model in response to the demand for curve path tracking of tracked vehicles in practical applications, and combines the LQR algorithm and the pure tracking algorithm to design an automatic control algorithm. The control method has a target tracking accuracy of cm, which is relatively small.

[0124] In summary, the present scheme can be applied to all types of tracked vehicles, improving the adaptability of the navigation control method to tracked vehicles and improving the navigation control accuracy of tracked vehicles.

[0125] It should be noted that the above embodiments only provide a specific implementation process of the navigation control method of the tracked vehicle, and the present application can also be implemented through other optional specific implementation processes.

[0126] For example, S101-S103 provide a specific method for constructing a discretized error tracking model according to the present application. In other optional embodiments, the original kinematics model of the tracked vehicle can also be linearized and discretized to construct a discretized error tracking model. And the specific linear relationship between the control variables and state variables represented by the discretized error tracking model can also have other forms based on different degrees of simplification, which is not limited by the present application.

[0127] For example, S105-S108 provide a specific method for calculating the reference value of the left track speed and the reference value of the right track speed based on the real-time value of the driving speed and the reference value of the steering curvature according to the present application. In other optional embodiments, the steering curvature at the target reference point can also be calculated by a piecewise calculation method, which is not limited by the present application.

[0128] For another example, S109-S112 provide a specific method for obtaining the left track speed error and the right track speed error based on the discretized error tracking model and the driving state information according to the present application. In optional embodiments, the left track speed error and the right track speed error can also be calculated by other algorithms instead of the LQR algorithm.

[0129] For another example, the real-time speed information further includes a real-time value of the left track speed and a real-time value of the right track speed, and after the expected value of the left track speed and the expected value of the right track speed are calculated, the expected value of the track speed can be adjusted by the real-time value of the track speed to improve the smoothness of the speed change.

[0130] In summary, the navigation control method of the tracked vehicle provided in the embodiments of the present application can be summarized as Figure 4 , Figure 4 The flowchart of the navigation control method of the tracked vehicle provided in the embodiments of the present application is shown in FIG. 4, which can include S401 to S405, and the steps will be described in detail as follows. Figure 4

[0131] S401, real-time driving state information of the tracked vehicle is acquired.

[0132] In the embodiment, the driving state information includes real-time pose information and real-time speed information, the real-time pose information includes a real-time value of an X-axis coordinate value, a real-time value of a Y-axis coordinate value and a real-time value of a heading angle in a global coordinate system, and the real-time speed information includes a real-time value of a driving speed.

[0133] In the embodiment, the high-precision navigation positioning system installed on the tracked vehicle is built-in with a high-precision positioning and orientation board card, which can quickly and accurately solve the relative position information and the azimuth angle of the two antennas. Meanwhile, through receiving the differential data of the reference station, real-time carrier phase differential positioning can be realized, so as to acquire the centimeter-level driving state information.

[0134] S402, the reference values of the left track speed and the right track speed are calculated based on the real-time value of the driving speed and the reference value of the steering curvature.

[0135] In the embodiment, the reference value of the steering curvature is the steering curvature of a target reference point on the preset reference path. The target reference point is a reference point on the reference path corresponding to the current position of the tracked vehicle, and optionally, the target reference point is the reference point on the reference path closest to the current position of the tracked vehicle. The calculation method of the steering curvature of the target reference point on the reference path includes multiple methods, and one optional method can refer to the above-mentioned embodiments S105 to S107.

[0136] S403, the left track speed error and the right track speed error are acquired based on the discretization error tracking model and the driving state information.

[0137] ​In this embodiment, the discretized error tracking model is used to describe the linear relationship between the discretized form of the pose tracking error vector and the track velocity error vector, the pose tracking error vector is composed of the X-axis tracking error, the Y-axis tracking error, and the heading angle tracking error, the track velocity error vector is composed of the left track velocity error and the right track velocity error, the X-axis tracking error is the difference between the X-axis coordinate value of the tracked vehicle and the X-axis coordinate value of the target reference point, the Y-axis tracking error is the difference between the Y-axis coordinate value of the tracked vehicle and the Y-axis coordinate value of the target reference point, and the heading angle tracking error is the difference between the heading angle of the tracked vehicle and the heading angle of the target reference point. The left track velocity error is the difference between the left track velocity of the tracked vehicle and the left track velocity of the target reference point, and the right track velocity error is the difference between the right track velocity of the tracked vehicle and the right track velocity of the target reference point.

[0138] In an optional embodiment, the discretized error tracking model is obtained by linearizing and discretizing the original kinematic model of the tracked vehicle by introducing the steering curvature. It can be understood that the state variables in the discretized error tracking model are in a linear relationship with the control variables. The driving state information of the tracked vehicle is substituted into the discretized error tracking model to calculate the control variables under the driving state information, i.e., the left track velocity error and the right track velocity error.

[0139] S404, calculating the expected value of the left track velocity based on the left track velocity error and the reference value of the left track velocity, and calculating the expected value of the right track velocity based on the right track velocity error and the reference value of the right track velocity.

[0140] In this embodiment, the sum of the reference value of the left track velocity and the left track velocity error is calculated as the expected value of the left track velocity, and the sum of the reference value of the right track velocity and the right track velocity error is calculated as the expected value of the right track velocity.

[0141] S405, generating a track driving instruction, the track driving instruction including the expected value of the left track velocity and the expected value of the right track velocity.

[0142] In this embodiment, the track driving instruction is used to instruct to control the left track velocity to be updated to the expected value of the left track velocity, and to control the right track velocity to be updated to the expected value of the right track velocity, so as to control the tracked vehicle to automatically drive along the reference path through controlling the bilateral track velocities.

[0143] As can be seen from the above technical solution, the navigation control method for a tracked vehicle provided in this application includes real-time pose information and real-time speed information in its driving state information. The real-time pose information includes the real-time values ​​of the X-axis coordinate, Y-axis coordinate, and heading angle in the global coordinate system. The real-time speed information includes the real-time value of the driving speed. Furthermore, the discretized error tracking model is used to describe the linear relationship between the discrete pose tracking error vector and the track speed error vector. The pose tracking error vector consists of the X-axis tracking error, Y-axis tracking error, and heading angle tracking error. The track speed error vector consists of the left track speed error and the right track speed error. The X-axis tracking error is the difference between the X-axis coordinate of the tracked vehicle and the X-axis coordinate of the target reference point. The Y-axis tracking error is the difference between the Y-axis coordinate of the tracked vehicle and the Y-axis coordinate of the target reference point. The heading angle tracking error is the difference between the heading angle of the tracked vehicle and the heading angle of the target reference point. The left track speed error is the difference between the left track speed of the tracked vehicle and the left track speed of the target reference point, and the right track speed error is the difference between the right track speed of the tracked vehicle and the right track speed of the target reference point. It can be seen that the discretized error tracking model introduces the track speed error vector by constructing a linear relationship between the discrete pose tracking error vector and the track speed error vector, thus making the control variables and state variables of the discrete system represented by the model linearized. Therefore, by substituting the real-time acquired driving state information into the discretized error tracking model and solving the linear problem, the real-time values ​​of the control variables, i.e., the left track speed error and the right track speed error, can be obtained. Furthermore, the reference values ​​of the bilateral track speeds are calculated based on the real-time driving speed and the steering curvature of the target reference point on the preset reference path. Therefore, the expected values ​​of the bilateral track speeds can make the actual driving path of the tracked vehicle approach the reference path.

[0144] In summary, this solution can be applied to all types of tracked vehicles, improving the adaptability of navigation control methods to tracked vehicles and enhancing the navigation control accuracy of tracked vehicles.

[0145] The above describes a navigation control method for a tracked vehicle provided by an embodiment of this application. The following will describe the apparatus for performing the above-described navigation control method for a tracked vehicle.

[0146] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a navigation control device for a tracked vehicle provided in an embodiment of this application. Figure 5 As shown, the navigation control device 500 of the tracked vehicle includes:

[0147] The driving state monitoring unit 501 is configured to acquire real-time driving state information of the tracked vehicle, wherein the driving state information comprises real-time pose information and real-time speed information, the real-time pose information comprises real-time values of an X-axis coordinate value and a Y-axis coordinate value and a real-time value of a heading angle in a global coordinate system, and the real-time speed information comprises a real-time value of a driving speed;

[0148] The reference curvature calculation unit 502 is configured to calculate reference values of left track speed and right track speed based on the real-time value of the driving speed and a reference value of a steering curvature of a target reference point on a preset reference path;

[0149] The speed error monitoring unit 503 is configured to acquire left track speed error and right track speed error based on a discretized error tracking model and the driving state information;

[0150] The discretized error tracking model is configured to describe a linear relationship between a discretized pose tracking error vector and a track speed error vector, the pose tracking error vector is composed of an X-axis tracking error, a Y-axis tracking error and a heading angle tracking error, the track speed error vector is composed of the left track speed error and the right track speed error, the X-axis tracking error is a difference between the X-axis coordinate value of the tracked vehicle and the X-axis coordinate value of the target reference point, the Y-axis tracking error is a difference between the Y-axis coordinate value of the tracked vehicle and the Y-axis coordinate value of the target reference point, and the heading angle tracking error is a difference between the heading angle of the tracked vehicle and the heading angle of the target reference point; the left track speed error is a difference between the left track speed of the tracked vehicle and the left track speed of the target reference point, and the right track speed error is a difference between the right track speed of the tracked vehicle and the right track speed of the target reference point;

[0151] The desired speed prediction unit 504 is configured to calculate a desired value of the left track speed based on the left track speed error and the reference value of the left track speed, and calculate a desired value of the right track speed based on the right track speed error and the reference value of the right track speed;

[0152] The speed driving unit 505 is configured to generate a track driving instruction, wherein the track driving instruction comprises the desired value of the left track speed and the desired value of the right track speed.

[0153] In a possible implementation, the navigation control device of the tracked vehicle further comprises a model construction unit configured to

[0154] constructing an original kinematic model of the tracked vehicle, the original kinematic model being used to describe a relationship between a pose vector and a tracked velocity vector, wherein the pose vector is composed of an X-axis coordinate value, a Y-axis coordinate value and a heading angle of the tracked vehicle in a global coordinate system, and the tracked velocity vector is composed of a left tracked velocity and a right tracked velocity of the tracked vehicle;

[0155] linearizing the original kinematic model to construct an error tracking model of the tracked vehicle, the error tracking model being used to describe a linear relationship between the pose tracking error vector and the tracked velocity error vector in a continuous form.

[0156] In a possible implementation, the reference curvature calculation unit is configured to calculate the reference values of the left tracked velocity and the right tracked velocity based on a real-time value of the driving speed and a reference value of a steering curvature, and specifically configured to:

[0157] determining a target reference point on the reference path based on the real-time pose information, and obtaining pose information of the target reference point;

[0158] calculating distances between the target reference point and reference points located behind the target reference point on the reference path in sequence from near to far until the distance is greater than a preset preview distance threshold, to obtain a preview reference point and a preview distance;

[0159] calculating the reference value of the steering curvature based on the pose information of the preview reference point and the target reference point;

[0160] calculating the reference values of the left tracked velocity and the right tracked velocity based on a structural parameter of the tracked vehicle, the real-time value of the driving speed and the reference value of the steering curvature.

[0161] In a possible implementation, the speed error monitoring unit is configured to obtain the left tracked velocity error and the right tracked velocity error based on the discretized error tracking model and the driving state information, and specifically configured to:

[0162] constructing an LQR performance function based on the discretized error tracking model, and calculating a tracked velocity error vector through Riccati equation;

[0163] obtaining the left tracked velocity error and the right tracked velocity error based on the driving state information.

[0164] In a possible implementation, the expected speed prediction unit is configured to calculate an expected value of the left tracked velocity based on the left tracked velocity error and the reference value of the left tracked velocity, and calculate an expected value of the right tracked velocity based on the right tracked velocity error and the reference value of the right tracked velocity, and specifically configured to:

[0165] The sum of the reference value of the left track speed and the error of the left track speed is calculated as the expected value of the left track speed;

[0166] The sum of the reference value of the right track speed and the error of the right track speed is calculated as the expected value of the right track speed.

[0167] This application also provides an electronic device in its embodiments. (See reference...) Figure 6 The diagram illustrates a structural schematic suitable for implementing the electronic device in the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 6 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0168] like Figure 6 As shown, the electronic device may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 into a random access memory (RAM) 603. When the electronic device is powered on, the RAM 603 also stores various programs and data required for the operation of the electronic device. The processing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0169] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 608 including, for example, memory cards, hard drives, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have alternatively.

[0170] This application also provides a computer program product including computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement any of the navigation control methods for tracked vehicles provided in this application.

[0171] The embodiment of the present application further provides a computer readable storage medium, the storage medium carries one or more computer programs, when the one or more computer programs are executed by an electronic device, the electronic device can realize any navigation control method of the tracked vehicle provided by the embodiment of the present application.

[0172] In addition, it should be noted that the above-described device embodiments are merely illustrative, wherein the units described as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., can be located in one place or distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment. In addition, the device embodiments provided in the present application, the connection relationship between the modules indicates that there is a communication connection between them, which can be implemented as one or more communication buses or signal lines.

[0173] Through the description of the above embodiments, those skilled in the art can clearly understand that the present application can be realized by software and necessary general hardware, and of course, it can also be realized by special hardware including special integrated circuits, special CPUs, special memories, special components, etc. Generally, functions completed by computer programs can be easily realized by corresponding hardware, and the specific hardware structure for realizing the same function can also be various, such as analog circuits, digital circuits or special circuits. However, for the present application, software program implementation is a better embodiment. Based on this understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer floppy disk, U disk, mobile hard disk, ROM, RAM, magnetic disk or optical disk, etc., including a plurality of instructions to make a computer device (which can be a personal computer, training device, or network device, etc.) execute the method described in each embodiment of the present application.

[0174] In the above embodiments, all or part can be realized by software, hardware, firmware or any combination thereof. When realized by software, it can be realized in the form of a computer program product in whole or in part.

[0175] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from one website, computer, training device or data center to another website, computer, training device or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be stored by the computer or a data storage device such as a training device, a data center, etc. integrated with one or more available media sets. The available media can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)), etc.

Claims

1. A method of navigating a tracked vehicle, characterized by, The method comprises the following steps: obtaining real-time driving state information of the tracked vehicle, the real-time driving state information comprising real-time pose information and real-time speed information, the real-time pose information comprising real-time values of an X-axis coordinate value and a Y-axis coordinate value and a real-time value of a heading angle in a global coordinate system, and the real-time speed information comprising a real-time value of a driving speed; calculating reference values of a left tracked vehicle speed and a right tracked vehicle speed based on the real-time value of the driving speed and a reference value of a steering curvature, the reference value of the steering curvature being a steering curvature of a target reference point on a preset reference path; obtaining left tracked vehicle speed errors and right tracked vehicle speed errors based on a discretized error tracking model and the real-time driving state information, wherein the discretized error tracking model is used to describe a linear relationship between a discretized form of a pose tracking error vector and a tracked vehicle speed error vector, the pose tracking error vector being composed of an X-axis tracking error, a Y-axis tracking error and a heading angle tracking error, the tracked vehicle speed error vector being composed of the left tracked vehicle speed errors and the right tracked vehicle speed errors, the X-axis tracking error being a difference between the X-axis coordinate value of the tracked vehicle and an X-axis coordinate value of the target reference point, the Y-axis tracking error being a difference between the Y-axis coordinate value of the tracked vehicle and a Y-axis coordinate value of the target reference point, and the heading angle tracking error being a difference between the heading angle of the tracked vehicle and a heading angle of the target reference point, the left tracked vehicle speed error being a difference between an expected left tracked vehicle speed of the tracked vehicle and a left tracked vehicle speed of the target reference point, and the right tracked vehicle speed error being a difference between an expected right tracked vehicle speed of the tracked vehicle and a right tracked vehicle speed of the target reference point; calculating expected values of the left tracked vehicle speed based on the left tracked vehicle speed errors and the reference value of the left tracked vehicle speed, and calculating expected values of the right tracked vehicle speed based on the right tracked vehicle speed errors and the reference value of the right tracked vehicle speed; generating tracked vehicle driving instructions, the tracked vehicle driving instructions comprising the expected values of the left tracked vehicle speed and the expected values of the right tracked vehicle speed. The navigation control method of the tracked vehicle further comprises the following steps:

2. The method of claim 1, wherein, constructing an original kinematic model of the tracked vehicle, the original kinematic model being used to describe a relationship between a pose vector and a tracked vehicle speed vector, wherein the pose vector is composed of an X-axis coordinate value, a Y-axis coordinate value and a heading angle of the tracked vehicle in a global coordinate system, and the tracked vehicle speed vector is composed of a left tracked vehicle speed and a right tracked vehicle speed of the tracked vehicle; linearizing the original kinematic model to construct an error tracking model of the tracked vehicle, the error tracking model being used to describe a linear relationship between a continuous form of the pose tracking error vector and the tracked vehicle speed error vector; discretizing the error tracking model based on a preset sampling time to obtain the discretized error tracking model. The calculation of the reference values of the left tracked vehicle speed and the right tracked vehicle speed based on the real-time value of the driving speed and the reference value of the steering curvature comprises the following steps:

3. The method of claim 1, wherein, determining a target reference point from the reference path based on the real-time pose information, and obtaining pose information of the target reference point; ​ calculating distances between the target reference point and reference points located behind the target reference point on the reference path in sequence from near to far until the distance is greater than a preset preview distance threshold, to obtain a preview reference point and a preview distance; calculating a reference value of the steering curvature based on pose information of the preview reference point and the target reference point; calculating reference values of the left track speed and the right track speed based on structure parameters of the tracked vehicle, a real-time value of the driving speed, and the reference value of the steering curvature.

4. The method of claim 1, wherein, The left track speed error and the right track speed error are obtained based on the discretized error tracking model and the driving state information, including: constructing an LQR performance function based on the discretized error tracking model, and calculating a track speed error vector through Riccati equation; obtaining the left track speed error and the right track speed error based on the driving state information.

5. The method of claim 1, wherein, The expected value of the left track speed is calculated based on the left track speed error and the reference value of the left track speed, and the expected value of the right track speed is calculated based on the right track speed error and the reference value of the right track speed, including: calculating a sum of the reference value of the left track speed and the left track speed error as the expected value of the left track speed; calculating a sum of the reference value of the right track speed and the right track speed error as the expected value of the right track speed.

6. A navigation control device for a tracked vehicle, characterised in that, including: a driving state monitoring unit for obtaining driving state information of the tracked vehicle in real time, the driving state information including real-time pose information and real-time speed information, the real-time pose information including real-time values of an X-axis coordinate value and a Y-axis coordinate value and a real-time value of a heading angle in a global coordinate system, and the real-time speed information including a real-time value of a driving speed; a reference curvature calculation unit for calculating reference values of the left track speed and the right track speed based on the real-time value of the driving speed and a reference value of a steering curvature, the reference value of the steering curvature being a steering curvature of a target reference point on a preset reference path; a speed error operation unit for obtaining left track speed errors and right track speed errors based on a discretized error tracking model and the driving state information; wherein the discretized error tracking model is used to describe a linear relationship between a discretized pose tracking error vector and a track speed error vector, the pose tracking error vector being composed of an X-axis tracking error, a Y-axis tracking error, and a heading angle tracking error, the track speed error vector being composed of a left track speed error and a right track speed error, the X-axis tracking error being a difference between an X-axis coordinate value of the tracked vehicle and an X-axis coordinate value of a target reference point, the Y-axis tracking error being a difference between a Y-axis coordinate value of the tracked vehicle and a Y-axis coordinate value of the target reference point, and the heading angle tracking error being a difference between a heading angle of the tracked vehicle and a heading angle of the target reference point; the left track speed error being a difference between a left track speed of the tracked vehicle and a left track speed of the target reference point, and the right track speed error being a difference between a right track speed of the tracked vehicle and a right track speed of the target reference point; An expected speed prediction unit is configured to calculate an expected value of the left track speed based on the left track speed error and a reference value of the left track speed, and calculate an expected value of the right track speed based on the right track speed error and a reference value of the right track speed; A speed driving unit is configured to generate a track driving instruction, the track driving instruction including the expected value of the left track speed and the expected value of the right track speed.

7. The track vehicle navigation control device of claim 6, wherein, The navigation control device of the tracked vehicle further includes a model construction unit configured to construct an original kinematic model of the tracked vehicle, the original kinematic model being configured to describe a relationship between a pose vector and a track speed vector, wherein the pose vector is composed of an X-axis coordinate value, a Y-axis coordinate value and a heading angle of the tracked vehicle in a global coordinate system, and the track speed vector is composed of a left track speed and a right track speed of the tracked vehicle; linearize the original kinematic model to construct an error tracking model of the tracked vehicle, the error tracking model being configured to describe a linear relationship between a continuous form of the pose tracking error vector and the track speed error vector; discretize the error tracking model based on a preset sampling time to obtain the discretized error tracking model.

8. A computer program product, characterised in that, An electronic device including computer readable instructions that, when executed on the electronic device, cause the electronic device to implement the navigation control method of the tracked vehicle according to any one of claims 1 to 5.

9. An electronic device, comprising: An electronic device including at least one processor and a memory connected to the processor, wherein: the memory is configured to store a computer program; the processor is configured to execute the computer program to enable the electronic device to implement the navigation control method of the tracked vehicle according to any one of claims 1 to 5.

10. A computer storage medium, characterized in that, The storage medium carries one or more computer programs, which, when executed by an electronic device, enable the electronic device to implement the navigation control method of the tracked vehicle according to any one of claims 1 to 5.

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