AGV operation control method, electronic device and medium

Abstract

The present invention relates to the technical field of AGVs, and in particular to an operation control method, electronic device and medium of an AGV. The method comprises: obtaining a starting point and an end point of an item transported by the AGV and a maximum speed threshold of the AGV, thereby determining a planned path of the AGV and the curvature of each discrete point in the planned path; then determining the maximum acceleration of the AGV based on the weight of the item carried by the AGV; obtaining the transport path of the AGV based on the maximum acceleration of the AGV, the curvature of each discrete point and the maximum speed threshold of the AGV; when controlling the AGV to travel along the transport path, determining in real time an optimal PID parameter value corresponding to a posture error, and controlling the AGV to adjust to the transport path according to the optimal PID parameter value and continue to travel until reaching the end point of the transported item; the present invention can take into account both the efficiency and safety of AGV transportation.

Description

Technical Field

[0001] The present invention relates to the field of robotics technology, and in particular to an AGV operation control method, electronic equipment and medium. Background Art

[0002] When AGV (Automated Guided Vehicle) is transporting items, it is necessary to ensure the smooth operation of the AGV to prevent the items from falling due to the AGV tilting, excessive acceleration or deceleration, etc.

[0003] Under different load inertia conditions, AGV has different motion parameters. How to combine these motion parameters with the actual situation of the transportation path to derive a control scheme suitable for AGV operation while taking into account the efficiency and safety of AGV transportation has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The purpose of the present invention is to provide an AGV operation control method, electronic device and medium to solve one or more technical problems existing in the prior art and at least provide a beneficial choice or create conditions.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] In a first aspect, an embodiment of the present invention provides an AGV operation control method, the method comprising the following steps:

[0007] Obtain the starting point and end point of the AGV transporting items, and the maximum speed threshold of the AGV;

[0008] Determine a planned path of the AGV based on a starting point and an end point of the AGV transporting items, and determine the curvature of each discrete point in the planned path;

[0009] When the AGV transports an object from the starting point of the planned path, determining the weight of the object carried by the AGV, and determining the maximum acceleration of the AGV based on the weight of the object carried by the AGV;

[0010] Based on the maximum acceleration of the AGV, the curvature of each discrete point in the planned path, and the maximum speed threshold of the AGV, the planned path is adjusted using a fitting function to obtain a transportation path for the AGV;

[0011] Controlling the AGV to travel along the transport path, and obtaining the current posture of the AGV and the theoretical posture in the transport path;

[0012] Determine the difference between the current posture and the theoretical posture as the posture error of the AGV, determine the optimal PID parameter value corresponding to the posture error in real time, and control the AGV to adjust to the transportation path according to the optimal PID parameter value and continue driving until it reaches the destination of the transported items.

[0013] Further, determining the planned path of the AGV based on the starting point and the end point of the AGV transporting the item, and determining the curvature of each discrete point in the planned path, includes:

[0014] Get the starting point and end point of the AGV transport items;

[0015] A global path planning algorithm is used to determine a global path with the shortest distance from the starting point and the end point, wherein the global path is composed of a number of discrete points;

[0016] Determine the initial curvature of each discrete point in the global path, and take the discrete points corresponding to the initial curvature greater than the curvature threshold as invalid points; wherein the curvature threshold is the maximum curvature allowed for the AGV to travel;

[0017] Determine the discrete points at both ends of the invalid point, use a local search algorithm to redetermine the discrete points between the discrete points at both ends of the invalid point, replace the invalid points with the discrete points in the redetermined global path, thereby updating the invalid points in the global path, and obtain the planned path for the AGV to transport items; wherein the curvature of the discrete points in the planned path are all less than the curvature threshold.

[0018] Further, determining the maximum acceleration of the AGV based on the weight of the items carried by the AGV includes:

[0019] Obtaining item parameters of the item carried by the AGV and the AGV's own parameters; wherein the own parameters include the mass of the AGV, the stiffness and maximum stroke of the AGV's suspension, the chassis width of the AGV, and the height of the center of gravity of the AGV; the item parameters include the weight and height of the item carried by the AGV;

[0020] Under the premise of preventing the AGV from tipping over when carrying items, the maximum acceleration of the AGV is determined based on the item parameters and the AGV's own parameters.

[0021] Further, the real-time determination of the optimal PID parameter value corresponding to the posture error, and the control of the AGV to adjust to the transport path according to the optimal PID parameter value to continue driving until reaching the destination of the transported items, include:

[0022] Step S610, establishing a PID control model for the AGV to perform posture compensation; wherein the input of the PID control model is the posture error, and the output is the speed and angular velocity of the AGV;

[0023] Step S620, determining each PID parameter value in the PID control model, and obtaining a data point set corresponding to the posture error and the PID parameter value as a PID parameter table;

[0024] Step S630, searching for the optimal PID parameter value corresponding to the posture error by using the Grey Wolf Algorithm;

[0025] Step S640, after controlling the AGV to run for a set time or a set distance according to the optimal PID parameter value, determining whether the posture error is less than a set posture error threshold, if so, determining that the AGV is adjusted to the transportation path; if not, executing step S620;

[0026] Step S650, determining that the AGV is adjusted to the transport path, and controlling the AGV to continue traveling until it reaches the destination of the transported items.

[0027] In a second aspect, an embodiment of the present invention further provides an AGV operation control device, the device comprising:

[0028] at least one processor;

[0029] at least one memory for storing at least one program;

[0030] When the at least one program is executed by the at least one processor, the at least one processor implements the AGV operation control method as described in the first aspect.

[0031] In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which an AGV operation control program is stored. When the AGV operation control program is executed by a processor, the steps of the AGV operation control method described in the first aspect are implemented.

[0032] The beneficial effects of the present invention are as follows: the present invention discloses an AGV operation control method, electronic device and medium, first starting from the efficiency of AGV transportation, preliminarily determining the planned path of the AGV, then determining the maximum acceleration of the AGV based on the weight of the items carried by the AGV, combining the curvature of each discrete point in the planned path and the maximum speed threshold of the AGV, using a fitting function to adjust the planned path to obtain the transportation path of the AGV, thereby taking into account the safety of AGV transportation; then according to the posture error of the AGV, determining the corresponding optimal PID parameter value in real time, controlling the AGV to adjust to the transportation path and continue to travel until reaching the destination of the transported items. The embodiments provided by the present invention can take into account the efficiency and safety of AGV transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0034] Figure 1 is a flow chart of an AGV operation control method in an embodiment of the present invention;

[0035] Figure 2 Schematic diagram of the structure of the AGV operation control device in the embodiment of the present invention. DETAILED DESCRIPTION

[0036] The following will be combined with the embodiments and drawings to clearly and completely describe the concept, specific structure and technical effects of this application, so as to fully understand the purpose, scheme and effect of this application. It should be noted that the embodiments and features in the embodiments of this application can be combined with each other without conflict.

[0037] See also Figure 1 , Figure 1 This is a flow chart of an AGV operation control method provided by the present application, and the method comprises the following steps:

[0038] Step S100, obtaining the starting point and the end point of the AGV transporting the item, and the maximum speed threshold of the AGV;

[0039] Step S200, determining a planned path of the AGV based on a starting point and an end point of the AGV transporting items, and determining a curvature of each discrete point in the planned path;

[0040] Step S300, when the AGV transports an item from the starting point of the planned path, determining the weight of the item carried by the AGV, and determining the maximum acceleration of the AGV based on the weight of the item carried by the AGV;

[0041] Step S400, adjusting the planned path using a fitting function based on the maximum acceleration of the AGV, the curvature of each discrete point in the planned path, and the maximum speed threshold of the AGV to obtain a transportation path of the AGV;

[0042] It should be noted that the fitting function may be a quintic curve function, and three equations are established based on the maximum acceleration of the AGV, the curvature of each discrete point in the planned path, and the maximum speed threshold of the AGV, so as to solve the position, speed, and acceleration of each point between adjacent discrete points, with the purpose of fitting a transportation path suitable for the AGV to travel under the satisfied restriction conditions;

[0043] Step S500, controlling the AGV to travel along the transport path, and obtaining the current posture of the AGV and the theoretical posture in the transport path;

[0044] Step S600, determine the difference between the current posture and the theoretical posture as the posture error of the AGV, determine the optimal PID parameter value corresponding to the posture error in real time, and control the AGV to adjust to the transport path according to the optimal PID parameter value and continue to travel until it reaches the destination of the transported items.

[0045] It should be noted that the absolute value of the optimal PID parameter value does not exceed the maximum speed threshold and the maximum curvature threshold of the AGV.

[0046] In the embodiment provided by the present invention, first starting from the efficiency of AGV transportation, the planned path of the AGV is preliminarily determined, and then the maximum acceleration of the AGV is determined based on the weight of the items carried by the AGV, and the curvature of each discrete point in the planned path and the maximum speed threshold of the AGV are combined to adjust the planned path using a fitting function to obtain the transportation path of the AGV, thereby taking into account the safety of AGV transportation; then, according to the posture error of the AGV, the corresponding optimal PID parameter value is determined in real time, and the AGV is controlled to continue driving after adjusting to the transportation path until it reaches the destination of the transported items, thereby ensuring that the AGV always takes into account efficiency and safety during transportation.

[0047] As a further improvement of the above embodiment, in step S200, determining the planned path of the AGV based on the starting point and the end point of the AGV transporting the item, and determining the curvature of each discrete point in the planned path include:

[0048] Step S210, obtaining the starting point and end point of the AGV transporting the item;

[0049] Step S220, using a global path planning algorithm to determine a global path with the shortest distance from the starting point and the end point, wherein the global path is composed of a number of discrete points;

[0050] Step S230, determining the initial curvature of each discrete point in the global path, and taking the discrete points corresponding to the initial curvature greater than the curvature threshold as invalid points; wherein the curvature threshold is the maximum curvature allowed for the AGV to travel;

[0051] It should be noted that when AGV transports items, in order to ensure the safe transportation of goods and prevent the goods from falling due to excessive turning angles, it is necessary to set a maximum curvature for the AGV as the curvature threshold. The initial curvature of each discrete point in the global path is adjusted through the curvature threshold, so that the global path is smoothed to obtain a path suitable for AGV to transport items.

[0052] Step S240, determine the discrete points at both ends of the invalid point, use a local search algorithm to redetermine the discrete points between the discrete points at both ends of the invalid point, replace the invalid points with the discrete points in the redetermined global path, thereby updating the invalid points in the global path, and obtaining the planned path for the AGV to transport items; wherein the curvature of the discrete points in the planned path are all less than the curvature threshold.

[0053] It should be noted that the invalid point can be a single discrete point or multiple continuous discrete points; if it is multiple continuous discrete points, the multiple continuous discrete points will be regarded as invalid points, and the discrete points at both ends of the continuous invalid points will be re-determined by a local search algorithm, and the original invalid points will be replaced to obtain the planned path for the AGV to transport items and the curvature of each discrete point in the planned path.

[0054] As a further improvement of the above embodiment, in step S300, determining the maximum acceleration of the AGV based on the weight of the items carried by the AGV includes:

[0055] Step S310, obtaining the item parameters of the item carried by the AGV and the AGV's own parameters; wherein the own parameters include the mass of the AGV, the stiffness and maximum stroke of the AGV's suspension, the chassis width of the AGV, and the height of the center of gravity of the AGV; the item parameters include the weight and height of the item carried by the AGV;

[0056] Step S320, determining the maximum acceleration of the AGV based on the object parameters and the AGV's own parameters, while preventing the AGV from tipping over when carrying the object.

[0057] In some embodiments, the maximum acceleration calculation formula of the AGV is:

[0058] a=min{p*(mg-Kx)L / (mH), q*Vt 2 / (2*d)};

[0059] Wherein, m is the sum of the mass of the AGV and the weight of the items carried by the AGV, g is the acceleration of gravity, K is the stiffness of the suspension, x is the maximum stroke of the suspension, L is the chassis width of the AGV, H is the height of the center of gravity of the AGV after carrying the items, Vt is the maximum speed threshold of the AGV, d is the distance between two adjacent discrete points, p and q are proportional factors, 0<p<1, 0<q<1.

[0060] It should be noted that the suspension of the AGV is regarded as a linear spring. The larger Kx is, that is, the greater the suspension preload is, the smaller the acceleration the AGV withstands, and the AGV is more likely to sway; the wider the chassis of the AGV is, the greater the acceleration the AGV can withstand; when the height of the object increases, that is, when the center of gravity of the AGV rises, the acceleration that the AGV can withstand decreases, and it is more likely to tip over.

[0061] As a further improvement of the above embodiment, in step S600, the optimal PID parameter value corresponding to the posture error is determined in real time, and the AGV is controlled according to the optimal PID parameter value to adjust to the transportation path and continue to travel until the destination of the transported items is reached, including:

[0062] Step S610, establishing a PID control model for the AGV to perform posture compensation; wherein the input of the PID control model is the posture error, and the output is the speed and angular velocity of the AGV;

[0063] It should be noted that the PID control model is a mathematical model designed to control the error between the AGV at each posture and the theoretical posture in proportion, integration and differentiation. By adjusting the speed and angular velocity of the AGV, the AGV can be adjusted to the theoretical posture at each posture.

[0064] Step S620, determining each PID parameter value in the PID control model, and obtaining a data point set corresponding to the posture error and the PID parameter value as a PID parameter table;

[0065] Step S630, searching for the optimal PID parameter value corresponding to the posture error by using the Grey Wolf Algorithm;

[0066] Step S640, after controlling the AGV to run for a set time or a set distance according to the optimal PID parameter value, determining whether the posture error is less than a set posture error threshold, if so, determining that the AGV is adjusted to the transportation path; if not, executing step S620;

[0067] Step S650, determining that the AGV is adjusted to the transport path, and controlling the AGV to continue traveling until it reaches the destination of the transported items.

[0068] It should be noted that the set duration or the set distance is set according to the actual situation. If the duration or distance is too short, the computing resources will be increased, but the set duration or the set distance should not be too long. It is necessary to ensure that the posture error of the AGV is within a reasonable range. After the set duration or distance, the AGV operation posture error feedback is used to regularly update the PID parameter table until the posture error is less than the set posture error threshold, and then it is determined that the AGV is adjusted to the transportation path.

[0069] In some embodiments, the AGV includes a frame and two drive units arranged at the bottom of the frame. The drive unit includes a main frame, two driving wheels and two motors. The motor is driven by a driver. Each driving wheel is driven to rotate by a motor. When driving, the turning and straight driving of the AGV are achieved by controlling the speed difference between the two driving wheels. The two drive units are respectively connected to the host computer for communication. The host computer uses the method provided in the above embodiment to control the two drive units to drive the AGV to drive.

[0070] and Figure 1 Corresponding to the method, refer to Figure 2 An embodiment of the present application further provides an electronic device 10, wherein the electronic device 10 includes a memory 11, a processor 12, and a computer program stored in the memory 11 and executable on the processor 12.

[0071] The processor 12 and the memory 11 may be connected via a bus or other means.

[0072] The non-transitory software program and instructions required to implement the operation control method of the AGV in the above embodiment are stored in the memory 11 , and when executed by the processor 12 , the operation control method of the AGV in the above embodiment is executed.

[0073] and Figure 1 Corresponding to the method, an embodiment of the present application further provides a computer-readable storage medium, on which an AGV operation control program is stored. When the AGV operation control program is executed by a processor, the steps of the AGV operation control method described in any of the above embodiments are implemented.

[0074] The contents of the above method embodiments are all applicable to the present device embodiments. The functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0075] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the operation control device of the AGV, and various interfaces and lines are used to connect the various parts of the operation control device of the entire AGV.

[0076] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the operation control device of the AGV by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart-Media-Card, SMC), a secure digital (Secure-Digital, SD) card, a flash card (Flash-Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0077] Although the description of the present application has been quite detailed and specifically describes several described embodiments, it is not intended to be limited to any of these details or embodiments or any particular embodiment, but should be regarded as providing a broad possible interpretation of these claims by reference to the attached claims, taking into account the prior art, so as to effectively cover the intended scope of the present application. In addition, the above description of the present application is based on the embodiments foreseeable by the inventor, and its purpose is to provide a useful description, and those non-substantial changes to the present application that have not yet been foreseen may still represent equivalent changes to the present application.

Claims

1. An AGV operation control method, characterized in that: The method comprises the following steps: Obtain the starting point and end point of the AGV transporting items, and the maximum speed threshold of the AGV; Determine a planned path of the AGV based on a starting point and an end point of the AGV transporting items, and determine the curvature of each discrete point in the planned path; When the AGV transports items from the starting point of the planned path, the weight of the items carried by the AGV is determined, and the maximum acceleration of the AGV is determined based on the weight of the items carried by the AGV; wherein the maximum acceleration calculation formula of the AGV is: a=min{p*(mg-Kx)L / (mH), q*Vt2 / (2*d)}; wherein m is the sum of the mass of the AGV and the weight of the items carried by the AGV, g is the acceleration of gravity, K is the stiffness of the suspension, x is the maximum stroke of the suspension, L is the chassis width of the AGV, H is the height of the center of gravity of the AGV after carrying the items, Vt is the maximum speed threshold of the AGV, d is the distance between two adjacent discrete points, p and q are proportional factors, 0<p<1, 0<q<1; Based on the maximum acceleration of the AGV, the curvature of each discrete point in the planned path, and the maximum speed threshold of the AGV, the planned path is adjusted using a fitting function to obtain a transportation path for the AGV; Controlling the AGV to travel along the transport path, and obtaining the current posture of the AGV and the theoretical posture in the transport path; Determine the difference between the current posture and the theoretical posture as the posture error of the AGV, determine the optimal PID parameter value corresponding to the posture error in real time, and control the AGV to adjust to the transportation path according to the optimal PID parameter value and continue to travel until reaching the destination of the transported items; The step of determining the planned path of the AGV based on the starting point and the end point of the AGV transporting the item, and determining the curvature of each discrete point in the planned path includes: Get the starting point and end point of the AGV transport items; A global path planning algorithm is used to determine a global path with the shortest distance from the starting point and the end point, wherein the global path is composed of a number of discrete points; Determine the initial curvature of each discrete point in the global path, and take the discrete points corresponding to the initial curvature greater than the curvature threshold as invalid points; wherein the curvature threshold is the maximum curvature allowed for the AGV to travel; Determine the discrete points at both ends of the invalid point, use a local search algorithm to redetermine the discrete points between the discrete points at both ends of the invalid point, replace the invalid points with the re-determined discrete points in the global path, thereby updating the invalid points in the global path, and obtaining the planned path for the AGV to transport the items; wherein the curvature of the discrete points in the planned path is less than the curvature threshold; The determining the maximum acceleration of the AGV based on the weight of the item carried by the AGV comprises: Obtaining item parameters of the item carried by the AGV and the AGV's own parameters; wherein the own parameters include the mass of the AGV, the stiffness and maximum stroke of the AGV's suspension, the chassis width of the AGV, and the height of the center of gravity of the AGV; the item parameters include the weight and height of the item carried by the AGV; Under the premise of preventing the AGV from tipping over when carrying items, determining the maximum acceleration of the AGV based on the item parameters and the AGV's own parameters; The method of determining the optimal PID parameter value corresponding to the posture error in real time, and controlling the AGV to adjust to the transportation path according to the optimal PID parameter value and continue to travel until reaching the destination of the transported items, includes: Step S610, establishing a PID control model for the AGV to perform posture compensation; wherein the input of the PID control model is the posture error, and the output is the speed and angular velocity of the AGV; Step S620, determining each PID parameter value in the PID control model, and obtaining a data point set corresponding to the posture error and the PID parameter value as a PID parameter table; Step S630, searching for the optimal PID parameter value corresponding to the posture error by using the Grey Wolf Algorithm; Step S640, after controlling the AGV to run for a set time or a set distance according to the optimal PID parameter value, determining whether the posture error is less than a set posture error threshold, if so, determining that the AGV is adjusted to the transportation path; if not, executing step S620; Step S650, determining that the AGV is adjusted to the transport path, and controlling the AGV to continue traveling until it reaches the destination of the transported items.

2. An AGV operation control device, characterized in that: The device comprises: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the AGV operation control method as claimed in claim 1.

3. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores an AGV operation control program, and when the AGV operation control program is executed by the processor, the steps of the AGV operation control method according to claim 1 are implemented.

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