Dual magnetic guide control method and system of AGV, AGV, device, medium

Abstract

The application discloses a double-magnetic-guide control method and system of an AGV, the AGV, equipment and a medium, which takes the center of two magnetic sensors as a control target point, constructs a positive kinematics equation of each wheel and the control target point, solves the current speed of the vehicle body and the current speed deviation angle of the two control target points through inverse kinematics, combines the trajectory deviation measurement result of the magnetic sensor to calculate the predicted correction angle of each control target point, and finally solves the target speed and the target speed deviation angle of each wheel through positive kinematics. The method takes the positions of the two magnetic sensors as control targets, adopts the double-control-target-point angle correction mode, can well consider the front and rear control points, can not only realize fast correction of the AGV, greatly improves the correction response speed, but also can be applied to complex and changeable paths, can well follow various changeable paths, improves the path following precision, and greatly reduces the control error.

Description

Technical Field

[0001] The present invention relates to the field of AGV navigation control technology, and in particular to a dual-magnetic guide control method and system for an AGV, an AGV, an electronic device, and a computer-readable storage medium. Background Art

[0002] AGVs, as automated mobile vehicles, are widely used in logistics, manufacturing, warehousing, healthcare, and other industries, and occupy a vital position in the industrial sector. Accurate motion navigation is a prerequisite for achieving movement in confined spaces and precise delivery. Therefore, the navigation control method of AGVs is particularly important. Currently, common navigation methods can be divided into laser navigation, vision navigation, IMU+GPS navigation, track navigation, and magnetic navigation, depending on the type of sensor. Among them, laser navigation or vision navigation relies on lidar or cameras to obtain information about the surrounding environment and match it with an existing map for absolute positioning, thereby performing posture control. This navigation method is technically complex and requires clear environmental characteristics. When the environment changes, the map needs to be updated, and navigation reliability is not high. IMU+GPS navigation is suitable for outdoor navigation. Track navigation requires pre-laid tracks and cannot change the path. Magnetic navigation corrects motion based on the deviation between the magnetic sensor and the magnetic stripe. It is simple and reliable to control, and the magnetic stripe laying and maintenance costs are low. It has strong scalability, which is why it is widely used.

[0003] Currently, most AGVs utilize a central arrangement for magnetic sensors, placing the sensor at the vehicle's geometric center to control and correct the center position. However, this central arrangement results in larger control errors for larger vehicles. Therefore, for long AGVs, a dual front and rear magnetic guide arrangement is often used to simultaneously control the vehicle's posture and position. However, the current dual magnetic guide control method still transfers the errors measured by the two magnetic sensors to a single control center, failing to account for both front and rear control points. This makes it difficult to adapt to complex and variable paths, resulting in slow response speeds and poor motion response accuracy. Summary of the Invention

[0004] The present invention provides a dual-magnetic guide control method and system for an AGV, an AGV, an electronic device, and a computer-readable storage medium. The method can realize rapid deviation correction of the AGV, greatly improve the deviation correction response speed, and is applicable to complex and changeable paths. It can well follow various changing paths, improve path following accuracy, and greatly reduce control errors.

[0005] According to one aspect of the present invention, a dual magnetic permeability control method for an AGV is provided, wherein two magnetic sensors are respectively arranged at the front and rear edges of the vehicle body and parallel to the forward direction of the vehicle body, including the following contents:

[0006] A rectangular coordinate system is established with the center of the magnetic sensor as the origin, the forward direction as the X direction, and the left direction as the Y direction. The centers of the two magnetic sensors are used as the two control target points, and the forward kinematic equations of each wheel and the two control target points are constructed.

[0007] The current speed and current speed angle of each wheel are collected, and the inverse kinematics solution is performed based on the forward kinematics equation to calculate the current speed of the vehicle and the current speed angles of the two control target points.

[0008] Based on the current speed of the vehicle, the current speed deviation angle of each control target point, and the trajectory deviation measurement results of the corresponding magnetic sensor, the predicted correction angle of each control target point is calculated respectively;

[0009] The target speed of the vehicle is input, and the forward kinematics equation is combined with the predicted correction angles of the two control target points to solve the forward kinematics equation to calculate the target speed and target speed deviation angle of each wheel.

[0010] Furthermore, the forward kinematics equation is:

[0011]

[0012] in, and Represents the current speed of the i-th wheel in the x direction and in the y direction, θ i represents the current speed deviation angle of the i-th wheel, v represents the current speed of the vehicle body, α1 and α2 represent the current speed deviation angles of the rear control target point and the front control target point respectively, and x i and y i represents the coordinate value of the center of the i-th wheel, and d represents the distance between the two control target points.

[0013] Furthermore, for motion trajectories with small curvature changes, the predicted correction angle of each control target point is calculated based on the following formula:

[0014]

[0015] Among them, v represents the current speed of the vehicle, S i+1 and S i They represent the error values ​​caused by path changes at time (i+1) and time i, respectively, e i represents the trajectory deviation measurement value of the magnetic sensor corresponding to the control target point at time i, L represents the system characteristic constant, Δt represents the time interval between two adjacent moments, ΔH i+1 and ΔH i They represent the longitudinal movement distance of the control target point at time (i+1) and time i, respectively. i Indicates the current velocity angle of the control target point at time i, α i+1Represents the predicted correction angle at time (i+1).

[0016] Furthermore, for motion trajectories with large curvature changes, the predicted correction angle of each control target point is calculated based on the following formula:

[0017] S i+1 =e -vΔt S i +e i

[0018] ΔH i+1 =e -vΔt ΔH i +vΔttanα i ;

[0019]

[0020] Among them, v represents the current speed of the vehicle, S i+1 and S i They represent the error values ​​caused by path changes at time (i+1) and time i, respectively, e i represents the trajectory deviation measurement value of the magnetic sensor corresponding to the control target point at time i, L represents the system characteristic constant, Δt represents the time interval between two adjacent moments, ΔH i+1 and ΔH i They represent the longitudinal movement distance of the control target point at time (i+1) and time i, respectively. i Indicates the current velocity angle of the control target point at time i, α i+1 Represents the predicted correction angle at time (i+1).

[0021] Furthermore, after calculating the predicted correction angle of each control target point, the following contents are also included:

[0022] Based on the current speed of the vehicle and the trajectory deviation measurement results of the magnetic sensor corresponding to each control target point, the compensation angle of each control target point is calculated, and the predicted correction angle of each control target point is compensated accordingly using the compensation angle.

[0023] Furthermore, the compensation angle of each control target point is calculated based on the following formula:

[0024] Δθ i+1 =k p (e i -e i-1 )+k i e i +k d (e i -2e i-1 +e i-2 )

[0025] Δα i+1 =Δα i +Δθ i+1 ;

[0026] k i =vΔt / l i

[0027] k d =l d / (vΔt);

[0028] Among them, Δα i+1 and Δα i They represent the compensation angles of the control target point at time (i+1) and time i, Δθ i+1 Indicates the incremental PID compensation angle of the control target point at time (i+1), e i 、e i-1 and e i-2 They represent the trajectory deviation measurement values ​​of the control target point at time i, (i-1) and (i-2), respectively, and k p Represents the proportional constant, taking a constant value, k i and k d They represent the integral constant and differential constant respectively, v represents the current speed of the vehicle, Δt represents the time interval between two adjacent moments, l i and l d represent the integral coefficient and the differential coefficient respectively.

[0029] In addition, the present invention also provides a dual magnetic permeability control system for an AGV, which adopts the dual magnetic permeability control method described above, including:

[0030] The forward kinematics equation construction module is used to establish a rectangular coordinate system with the center of the rear magnetic sensor as the origin, the forward direction as the X direction, and the left direction as the Y direction. The centers of the two magnetic sensors are used as the two control target points to construct the forward kinematics equations for each wheel and the two control target points.

[0031] The inverse kinematics solution module is used to collect the current speed and current speed deviation angle of each wheel, and perform inverse kinematics solution based on the forward kinematics equation to calculate the current speed of the vehicle body and the current speed deviation angles of the two control target points;

[0032] The correction angle prediction module is used to calculate the predicted correction angle of each control target point based on the current speed of the vehicle body, the current speed deviation angle of each control target point, and the trajectory deviation measurement results of the corresponding magnetic sensor;

[0033] The forward kinematics solution module is used to input the target speed of the vehicle body and perform forward kinematics solution based on the predicted correction angles of the two control target points and the forward kinematics equation to calculate the target speed and target speed deviation angle of each wheel.

[0034] In addition, the present invention also provides an AGV that adopts the dual magnetic guide control system described above.

[0035] In addition, the present invention also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor is configured to execute the steps of the above method by calling the computer program stored in the memory.

[0036] In addition, the present invention also provides a computer-readable storage medium for storing a computer program for performing dual magnetic permeability control on an AGV, wherein the computer program executes the steps of the above-described method when running on a computer.

[0037] The present invention has the following beneficial effects:

[0038] The dual magnetic permeability control method of the AGV of the present invention uses the centers of the front and rear magnetic sensors as the two control target points, and constructs the forward kinematics equations of each wheel and the two control target points, and then obtains the current speed of the vehicle body and the current speed deviation angle of the two control target points through inverse kinematics solution, and then calculates the predicted correction angle of each control target point based on the inverse kinematics solution result and the trajectory deviation measurement result of the magnetic sensor. Finally, the forward kinematics solution is performed in combination with the target vehicle speed of the vehicle body to calculate the target speed and target speed deviation angle of each wheel. This method uses the positions of both magnetic sensors as control targets, and the dual control target point angle correction method can well take into account the front and rear control points. It can not only realize rapid correction of the AGV and greatly improve the correction response speed, but also can be applied to complex and changeable paths, can well follow various changing paths, and also improve the path following accuracy, greatly reducing the control error.

[0039] In addition, the dual magnetic permeability control system and the AGV of the present invention also have the above advantages.

[0040] In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0042] Figure 11 is a flow chart of a dual magnetic permeability control method for an AGV according to a preferred embodiment of the present application;

[0043] Figure 2 This is a schematic diagram of the arrangement of magnetic sensors on the AGV in a preferred embodiment of the present application;

[0044] Figure 3 Schematic diagram of the principle of calculating the predicted correction angle in the preferred embodiment of the present application;

[0045] Figure 4 This is another flow chart of the dual magnetic permeability control method for AGV according to a preferred embodiment of the present application;

[0046] Figure 5 This is a schematic diagram of the overall control strategy of the dual magnetic permeability control method of the preferred embodiment of the present application;

[0047] Figure 6 1 is a schematic diagram of simulation results of control simulation using a dual magnetic permeability control method in a preferred embodiment of the present application;

[0048] Figure 7 It is a schematic diagram of the module structure of the dual magnetic control system of the AGV according to another embodiment of the present application.

[0049] Description of Reference Numerals

[0050] 1. Front magnetic sensor; 2. Rear magnetic sensor; 3. Motion path magnetic stripe. DETAILED DESCRIPTION

[0051] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0052] Reference Figure 1 The preferred embodiment of the present application provides a dual magnetic permeability control method for an AGV, wherein two magnetic sensors are respectively arranged at the front and rear edges of the vehicle body and parallel to the forward direction of the vehicle body, including the following contents:

[0053] Step S1: Establish a rectangular coordinate system with the center of the rear magnetic sensor as the origin, the forward direction as the X direction, and the left direction as the Y direction. Use the centers of the two magnetic sensors as the two control target points to construct the forward kinematic equations of each wheel and the two control target points.

[0054] Step S2: Collect the current speed and current speed deviation angle of each wheel, and perform inverse kinematics solution based on the forward kinematics equation to calculate the current speed of the vehicle body and the current speed deviation angles of the two control target points;

[0055] Step S3: Based on the current speed of the vehicle, the current speed deviation angle of each control target point, and the trajectory deviation measurement result of the corresponding magnetic sensor, the predicted correction angle of each control target point is calculated;

[0056] Step S4: Input the target speed of the vehicle body, and perform forward kinematics solution based on the predicted correction angles of the two control target points and the forward kinematics equation to calculate the target speed and target speed deviation angle of each wheel.

[0057] It can be understood that the dual magnetic permeability control method of the AGV of this embodiment uses the centers of the front and rear magnetic sensors as the two control target points, and constructs the forward kinematic equations of each wheel and the two control target points. The current speed of the vehicle body and the current speed deviation angle of the two control target points are then obtained by inverse kinematics solution. Based on the inverse kinematics solution results and the trajectory deviation measurement results of the magnetic sensor, the predicted correction angle of each control target point is calculated. Finally, the forward kinematic solution is performed in combination with the target vehicle speed of the vehicle body to calculate the target speed and target speed deviation angle of each wheel. This method uses the positions of both magnetic sensors as control targets, and the dual control target point angle correction method can well take into account the two control points in front and behind. It can not only realize rapid correction of the AGV and greatly improve the correction response speed, but also can be applied to complex and changeable paths, can well follow various changing paths, and also improve the path following accuracy, greatly reducing the control error.

[0058] It is understandable that Figure 2 As shown, the front magnetic sensor 1 is arranged at the front edge of the vehicle body, and the rear magnetic sensor 2 is arranged at the rear edge of the vehicle body. The AGV needs to be driven on the moving path magnetic strip 3. In step S1, the center of the rear magnetic sensor 2 is the origin, the forward direction is the X direction, and the left direction is the Y direction to establish a rectangular coordinate system 0XY. The coordinates of each wheel can be measured by the total station as (x i ,y i ), and the coordinates of the front magnetic sensor are (d, 0). Kinematic analysis of the AGV shows that the instantaneous motion of the AGV can be considered as all points rotating around the center of a circle. A perpendicular line perpendicular to the wheel speed is drawn through the centers of all wheels. The intersection of these perpendicular lines is the center of the circle O'. A perpendicular line O'H is drawn between the center of the circle and the line OF connecting the two magnetic sensors. Based on the geometric relationship, we can obtain: O'H tanα1+O'H tan(-α2)=d, where α1 and α2 represent the current velocity deviation angles of the rear control target point and the front control target point, respectively, and d represents the distance between the two magnetic sensors. Therefore, the y-coordinate value of the center of the circle O', O'H, can be obtained as: The x-coordinate value of the center O' is: Therefore, by solving the right triangle, we can get the coordinates of the center O': The turning radius r of each wheel center point can be obtained by the two-point distance formulai , taking point H as the reference object, the angular velocity of the vehicle is:

[0059] Since v = ωr, the forward kinematic equations of each wheel and the control target point can be constructed as follows:

[0060]

[0061] in, and Represents the current speed of the i-th wheel in the x direction and in the y direction, θ i represents the current speed deviation angle of the i-th wheel, v represents the current speed of the vehicle body, α1 and α2 represent the current speed deviation angles of the rear control target point and the front control target point respectively, and x i and y i represents the coordinate value of the center of the i-th wheel, and d represents the distance between the two control target points.

[0062] Transforming the angle formula in the forward kinematics equation yields:

[0063] tanθ i (dy i (tanα1-tanα2))=dtanα1-x(tanα1-tanα2);

[0064] Rewriting the above equation into matrix form can be expressed as:

[0065]

[0066] It can be understood that in step S2, the current speed v of each wheel can be obtained through each wheel controller. i =[v ix ,v iy ], the current speed deviation angle θ of each wheel can be obtained through the encoder of each wheel i , and the coordinates of the center points of each wheel (x i ,y i ) is known, so by combining the above angle equations for at least two wheels and solving them using the linear least squares method for inverse kinematics, we can obtain the current velocity deviation angles α1 and α2 of the two control target points. Then, by adding the kinematic constraints of all wheels, we can obtain the current velocity v of the vehicle body using the linear least squares method.

[0067] It can be understood that in step S3, Figure 3 As shown, assuming that the current velocity deviation angle of the target point at time i is α i , the corresponding track deviation measurement value of the magnetic sensor is e i, driving in the current direction of motion, after a time interval Δt, the trajectory deviation prediction value of the magnetic sensor at time i+1 is e i+1 The horizontal and vertical moving distances are Δd respectively. i+1 and ΔH i+1 , then the following relationship exists: e i+1 =s i+1 +ΔH i+1 =s i+1 +vΔttanα i , where s i+1 represents the error value caused by the path change at time (i+1), and v represents the current speed of the vehicle. The predicted correction angle can be calculated based on the following formula:

[0068]

[0069] Among them, α i+1 Represents the predicted correction angle at time (i+1).

[0070] It can be seen that the predicted correction angle is determined by two parts. The first part is S i+1 , which is the error caused by path change, and the second part is ΔH i+1 , that is, the error caused by the direction of motion. This invention takes into account that AGV usually adopts a speed following algorithm, and the system sampling time interval is stable, which is Δt, so the system characteristic speed is defined as v o , the time interval is Δt o , so the system characteristic constant L=v o Δt o .Depend on Figure 3 It can be seen that for the motion trajectory with small curvature change, S i+1 ≈e i , and the trajectory and speed change smoothly within the time interval, so the two parts of the error can be re-estimated based on the low-pass filtering algorithm to obtain: Therefore, for a motion trajectory with small curvature changes, the predicted correction angle of each control target point is calculated based on the following formula:

[0071]

[0072] Among them, v represents the current speed of the vehicle, S i+1 and S i They represent the error values ​​caused by path changes at time (i+1) and time i, respectively, e i represents the trajectory deviation measurement value of the magnetic sensor corresponding to the control target point at time i, L represents the system characteristic constant, Δt represents the time interval between two adjacent moments, ΔH i+1 and ΔH iThey represent the longitudinal movement distance of the control target point at time (i+1) and time i, respectively. i Indicates the current velocity angle of the control target point at time i, α i+1 Represents the predicted correction angle at time (i+1).

[0073] In addition, the inventors of this application found in actual applications that the linear function 1-vΔt / L is difficult to respond to motion trajectories with large curvature changes. Therefore, in order to improve the adaptability and accuracy of the algorithm, for motion trajectories with large curvature changes, an exponential function e with the same threshold and change trend is used. -vΔt Instead of performing a linear function calculation, the predicted correction angle of each control target point is calculated based on the following formula:

[0074] S i+1 =e -vΔt S i +e i

[0075] ΔH i+1 =e -vΔt ΔH i +vΔttanα i ;

[0076]

[0077] Among them, v represents the current speed of the vehicle, S i+1 and S i They represent the error values ​​caused by path changes at time (i+1) and time i, respectively, e i represents the trajectory deviation measurement value of the magnetic sensor corresponding to the control target point at time i, L represents the system characteristic constant, Δt represents the time interval between two adjacent moments, ΔH i+1 and ΔH i They represent the longitudinal movement distance of the control target point at time (i+1) and time i, respectively. i Indicates the current velocity angle of the control target point at time i, α i+1 Represents the predicted correction angle at time (i+1). It will be understood that in the present invention, when the curvature change of the motion trajectory is greater than a preset threshold, an exponential function is used to calculate the predicted correction angle. When the curvature change of the motion trajectory is not greater than the preset threshold, a linear function is used to calculate the predicted correction angle. The specific value of the preset threshold can be set manually based on experience and is not specifically limited here.

[0078] It can be understood that the present invention can adaptively select different algorithms to calculate the predicted correction angle according to the change in the curvature of the motion trajectory, thereby improving the adaptability of the algorithm and the calculation accuracy of the predicted correction angle.

[0079] It can be understood that in step S4, the target speed v of the vehicle body is input, and combined with the predicted correction angles of the two control target points, it is substituted into the forward kinematics equation for forward kinematic solution to obtain the target speed and target speed deviation angle of each wheel, thereby realizing rapid correction of the AGV, greatly improving the correction response speed, and being applicable to complex and changeable paths, and being able to follow various changing paths well, and also improving the path following accuracy, greatly reducing the control error.

[0080] In addition, if Figure 4 As shown, in another embodiment of the present invention, after calculating the predicted deviation correction angle of each control target point, the dual magnetic permeability control method of the AGV further includes the following:

[0081] Step S3a: Based on the current speed of the vehicle body and the trajectory deviation measurement results of the magnetic sensor corresponding to each control target point, the compensation angle of each control target point is calculated, and the predicted correction angle of each control target point is compensated accordingly using the compensation angle.

[0082] Specifically, in order to enhance the stability of system control, the present invention also adopts incremental PID compensation to predict the correction angle based on the current speed of the vehicle and the trajectory deviation measurement results of the magnetic sensor corresponding to each control target point, where the proportional constant k p Take the constant value. Since the system uses the movement distance as the characteristic parameter, the integral constant k i and the differential constant k d They are all related to the movement distance. The compensation angle of each control target point is calculated based on the following formula:

[0083] Δθ i+1 =k p (e i -e i-1 )+k i e i +k d (e i -2e i-1 +e i-2 )

[0084] Δα i+1 =Δα i +Δθ i+1 ;

[0085] k i =vΔt / l i

[0086] k d =l d / (vΔt);

[0087] Among them, Δα i+1 and Δαi They represent the compensation angles of the control target point at time (i+1) and time i, Δθ i+1 Indicates the incremental PID compensation angle of the control target point at time (i+1), e i 、e i-1 and e i-2 They represent the trajectory deviation measurement values ​​of the control target point at time i, (i-1) and (i-2), respectively, and k p Represents the proportional constant, taking a constant value, k i and k d They represent the integral constant and differential constant respectively, v represents the current speed of the vehicle, Δt represents the time interval between two adjacent moments, l i and l d Denote the integral coefficient and differential coefficient, respectively. After calculating the compensation angle for each control target point, the compensation angle is superimposed on the predicted correction angle to obtain the exact correction angle for each control target point, which is then substituted into step S4 for calculation. It can be understood that the compensation angle calculated using the above formula helps ensure accurate control of the system under path changes, further improving AGV control accuracy.

[0088] It can be understood that, as a preferred embodiment, the overall control strategy of the dual magnetic permeability control method of the AGV of the present invention is as follows: Figure 5 As shown in the figure, after the wheel moves, the front and rear trajectory deviation values ​​e1 and e2 are measured by two magnetic sensors, and the inverse kinematics estimation is performed based on the current speed and current speed deviation angle of each wheel to obtain the current speed deviation angles α1 and α2 of the two control target points at the current moment. Then, the predicted correction angle calculation formula is used to calculate the predicted correction angles β1 and β2 of the two control target points (that is, the α of the two control target points). i+1 ), and in order to enhance the stability of the system, e1 and e2 are input into the incremental PID to obtain the compensation angles Δα1 and Δα2 of the two control target points. The compensation angles are superimposed on the corresponding predicted correction angles to obtain the accurate correction angles at the next moment. Then, the target speed and target speed deviation angle of each wheel are obtained through forward kinematics calculation. Finally, the target speed and target speed deviation angle of each wheel are transmitted to the controller of each wheel to realize the AGV correction control. Among them, the results of the control simulation of the present invention are as follows: Figure 6 As shown in the figure, the red line segment represents the connection between the front and rear control target points. From the simulation results, it can be seen that even on the curved trajectory, the deviation distance between the front and rear control target points and the trajectory can still be kept very small, and the navigation control accuracy of the AGV is very high.

[0089] In addition, if Figure 7 As shown, another embodiment of the present invention further provides a dual magnetic permeability control system for an AGV, preferably using the dual magnetic permeability control method as described above, including:

[0090] The forward kinematics equation construction module is used to establish a rectangular coordinate system with the center of the rear magnetic sensor as the origin, the forward direction as the X direction, and the left direction as the Y direction. The centers of the two magnetic sensors are used as the two control target points to construct the forward kinematics equations for each wheel and the two control target points.

[0091] The inverse kinematics solution module is used to collect the current speed and current speed deviation angle of each wheel, and perform inverse kinematics solution based on the forward kinematics equation to calculate the current speed of the vehicle body and the current speed deviation angles of the two control target points;

[0092] The correction angle prediction module is used to calculate the predicted correction angle of each control target point based on the current speed of the vehicle body, the current speed deviation angle of each control target point, and the trajectory deviation measurement results of the corresponding magnetic sensor;

[0093] The forward kinematics solution module is used to input the target speed of the vehicle body and perform forward kinematics solution based on the predicted correction angles of the two control target points and the forward kinematics equation to calculate the target speed and target speed deviation angle of each wheel.

[0094] It can be understood that the dual magnetic control system of the AGV of this embodiment uses the centers of the front and rear magnetic sensors as the two control target points, and constructs the forward kinematic equations for each wheel and the two control target points. The current speed of the vehicle body and the current speed deviation angle of the two control target points are then obtained through inverse kinematics solution. Based on the inverse kinematics solution results and the trajectory deviation measurement results of the magnetic sensor, the predicted correction angle of each control target point is calculated. Finally, the forward kinematic solution is performed in combination with the target vehicle speed to calculate the target speed and target speed deviation angle of each wheel. The system uses the positions of both magnetic sensors as control targets and adopts a dual control target point angle correction method to well take into account the front and rear control points. It can not only realize rapid correction of the AGV and greatly improve the correction response speed, but also can be applied to complex and changeable paths, can well follow various changing paths, and also improve the path following accuracy, greatly reducing the control error.

[0095] In addition, the dual magnetic control system of the AGV also includes:

[0096] The correction angle compensation module is used to calculate the compensation angle of each control target point based on the current speed of the vehicle body and the trajectory deviation measurement results of the magnetic sensor corresponding to each control target point, and use the compensation angle to compensate the predicted correction angle of each control target point accordingly.

[0097] It can be understood that the various modules of the system embodiment correspond to the various steps of the above method embodiment, so the specific working principles of each module will not be repeated here, and the corresponding references can be made to the various steps of the above method embodiment.

[0098] In addition, another embodiment of the present invention further provides an AGV, which preferably adopts the dual magnetic guide control system as described above.

[0099] In addition, another embodiment of the present invention further provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor is configured to execute the steps of the above method by calling the computer program stored in the memory.

[0100] In addition, another embodiment of the present invention further provides a computer-readable storage medium for storing a computer program for performing dual magnetic guide control on an AGV, wherein the computer program executes the steps of the above-described method when running on a computer.

[0101] Common computer-readable storage media include: floppy disks, flexible disks, hard disks, magnetic tape, any other magnetic media, CD-ROMs, any other optical media, punch cards, paper tape, any other physical medium with a pattern of holes, random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), flash-erasable programmable read-only memory (FLASH-EPROM), any other memory chip or cartridge, or any other medium that can be read by a computer. Instructions can further be transmitted or received via a transmission medium. The term transmission medium may include any tangible or intangible medium that can be used to store, encode, or carry instructions for execution by a machine, and includes digital or analog communication signals or other intangible media that facilitate communication of such instructions. Transmission media include coaxial cables, copper wire, and fiber optics, including the wires of a bus used to transmit a computer data signal.

[0102] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiment of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal translation scripting language JavaScript, etc.

[0103] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0104] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0106] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0107] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

[0108] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A dual magnetic permeability control method for AGV, wherein two magnetic sensors are respectively arranged at the front and rear edges of the vehicle body and parallel to the forward direction of the vehicle body, characterized in that: Includes the following: A rectangular coordinate system is established with the center of the magnetic sensor as the origin, the forward direction as the X direction, and the left direction as the Y direction. The centers of the two magnetic sensors are used as the two control target points to construct the forward kinematic equations of each wheel and the two control target points. The forward kinematic equations are: in, and Represents the current speed of the i-th wheel in the x direction and in the y direction, θ i represents the current speed deviation angle of the i-th wheel, v represents the current speed of the vehicle body, α1 and α2 represent the current speed deviation angles of the rear control target point and the front control target point respectively, and x i and y i represents the coordinate value of the center of the i-th wheel, and d represents the distance between the two control target points; The current speed and current speed angle of each wheel are collected, and the inverse kinematics solution is performed based on the forward kinematics equation to calculate the current speed of the vehicle and the current speed angles of the two control target points. Based on the current speed of the vehicle, the current speed deviation angle of each control target point, and the trajectory deviation measurement results of the corresponding magnetic sensor, the predicted correction angle of each control target point is calculated respectively; The target speed of the vehicle is input, and the forward kinematics equation is combined with the predicted correction angles of the two control target points to solve the forward kinematics equation to calculate the target speed and target speed deviation angle of each wheel.

2. The dual magnetic permeability control method of AGV according to claim 1, characterized in that: For a motion trajectory with small curvature changes, the predicted correction angle of each control target point is calculated based on the following formula: Among them, v represents the current speed of the vehicle, S i+1 and S i They represent the error values ​​caused by path changes at time (i+1) and time i, respectively, e i represents the trajectory deviation measurement value of the magnetic sensor corresponding to the control target point at time i, L represents the system characteristic constant, Δt represents the time interval between two adjacent moments, ΔH i+1 and ΔH i They represent the longitudinal movement distance of the control target point at time (i+1) and time i, respectively. i Indicates the current velocity angle of the control target point at time i, α i+1 Represents the predicted correction angle at time (i+1).

3. The dual magnetic permeability control method of AGV according to claim 1, characterized in that: For motion trajectories with large curvature changes, the predicted correction angle of each control target point is calculated based on the following formula: S i+1 =e -vΔt S i +e i ΔH i+1 =e -vΔt ΔH i +vΔttanα i ; Among them, v represents the current speed of the vehicle, S i+1 and S i They represent the error values ​​caused by path changes at time (i+1) and time i, respectively, e i represents the trajectory deviation measurement value of the magnetic sensor corresponding to the control target point at time i, L represents the system characteristic constant, Δt represents the time interval between two adjacent moments, ΔH i+1 and ΔH i They represent the longitudinal movement distance of the control target point at time (i+1) and time i, respectively. i Indicates the current velocity angle of the control target point at time i, α i+1 Represents the predicted correction angle at time (i+1).

4. The dual magnetic permeability control method of AGV according to claim 1, characterized in that: After calculating the predicted correction angle of each control target point, the following contents are also included: Based on the current speed of the vehicle and the trajectory deviation measurement results of the magnetic sensor corresponding to each control target point, the compensation angle of each control target point is calculated, and the predicted correction angle of each control target point is compensated accordingly using the compensation angle.

5. The dual magnetic permeability control method of AGV according to claim 4, characterized in that: The compensation angle of each control target point is calculated based on the following formula: Δθ i+1 =k p (e i -e i-1 )+k i e i +k d (e i -2e i-1 +e i-2 ) Da i+1 =Da i +Δθ i+1 ; k i =vΔt / l i k d =l d / (vΔt); Among them, Δα i+1 and Δα i They represent the compensation angles of the control target point at time (i+1) and time i, Δθ i+1 Indicates the incremental PID compensation angle of the control target point at time (i+1), e i 、e i-1 and e i-2 They represent the trajectory deviation measurement values ​​of the control target point at time i, (i-1) and (i-2), respectively, and k p Represents the proportional constant, taking a constant value, k i and k d They represent the integral constant and differential constant respectively, v represents the current speed of the vehicle, Δt represents the time interval between two adjacent moments, l i and l d represent the integral coefficient and the differential coefficient respectively.

6. A dual magnetic permeability control system for an AGV, using the dual magnetic permeability control method according to any one of claims 1 to 5, characterized in that: include: The forward kinematics equation construction module is used to establish a rectangular coordinate system with the center of the rear magnetic sensor as the origin, the forward direction as the X direction, and the left direction as the Y direction. The centers of the two magnetic sensors are used as the two control target points to construct the forward kinematics equations for each wheel and the two control target points. The inverse kinematics solution module is used to collect the current speed and current speed deviation angle of each wheel, and perform inverse kinematics solution based on the forward kinematics equation to calculate the current speed of the vehicle body and the current speed deviation angles of the two control target points; The correction angle prediction module is used to calculate the predicted correction angle of each control target point based on the current speed of the vehicle body, the current speed deviation angle of each control target point, and the trajectory deviation measurement results of the corresponding magnetic sensor; The forward kinematics solution module is used to input the target speed of the vehicle body and perform forward kinematics solution based on the predicted correction angles of the two control target points and the forward kinematics equation to calculate the target speed and target speed deviation angle of each wheel.

7. An AGV, characterized in that: The dual magnetic permeability control system as claimed in claim 6 is adopted.

8. An electronic device, characterized in that: The method comprises a processor and a memory, wherein a computer program is stored in the memory, and the processor is configured to execute the steps of the method according to any one of claims 1 to 5 by calling the computer program stored in the memory.

9. A computer-readable storage medium for storing a computer program for dual-magnetic control of an AGV, characterized in that: When the computer program is run on a computer, the steps of the method according to any one of claims 1 to 5 are executed.

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