Coordinate correction method, device, storage medium and electronic device for positioning markers

Abstract

An embodiment of the present invention provides a method, device, storage medium, and electronic device for correcting the coordinates of a positioning marker. The method includes: obtaining N sets of acquisition data, where the N sets of acquisition data include odometer information generated by a first automated guided vehicle moving from a first positioning marker to a second positioning marker N times and image information of the second positioning marker recognized; determining N position deviations between the first automated guided vehicle and the second positioning marker according to the image information in the N sets of acquisition data; determining N moving distances of the first automated guided vehicle according to the odometer information in the N sets of acquisition data; determining a first estimated coordinate of the second positioning marker and correcting its theoretical coordinate according to the theoretical coordinate of the first positioning marker, the N position deviations, the N moving distances, and the external parameter deviation of the odometer. Through the present invention, the problem of low accuracy of the coordinate information of the positioning marker in the related art is solved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of robotics technology, and more specifically, to a method, device, storage medium, and electronic device for correcting the coordinates of a positioning marker. Background Art

[0002] In the context of the widespread recognition of intelligent manufacturing and machine-replacing policies, automated guided vehicles (AGVs) have received widespread attention in industrial manufacturing. In applications such as smart warehousing, the use of QR code navigation and other methods to provide precise positioning for AGVs has been widely used. In actual use, the coordinate information of the QR code (or positioning marker) posted on the ground will be converted into a part of the environmental map information and stored in the AGV navigation and positioning system. However, considering that the construction link of the QR code will introduce more errors due to human factors, the actual coordinates of the QR code posted will deviate from the theoretical value; on the other hand, the QR code image will become difficult to recognize over time, and the AGV will gradually deteriorate in motion control accuracy as the mileage increases. Such situations will directly lead to abnormal node loss during the operation of the AGV, affecting the operating efficiency of the AGV. That is, there is a problem in the related technology that the positioning accuracy of the AGV is low due to inaccurate coordinate information of the positioning marker.

[0003] With regard to the problem of low accuracy of coordinate information of positioning markers existing in related technologies, no effective solution has been proposed so far. Summary of the invention

[0004] Embodiments of the present invention provide a method, device, storage medium and electronic device for correcting the coordinates of a positioning marker, so as to at least solve the problem of low accuracy of the coordinate information of the positioning marker existing in the related art.

[0005] According to an embodiment of the present invention, a method for correcting the coordinates of a positioning marker is provided, including: obtaining the acquisition data of a first automated guided vehicle, where the acquisition data of the first automated guided vehicle includes N sets of acquisition data, N is a positive integer greater than or equal to 1, and the N sets of acquisition data include the odometer information generated by the odometer on the first automated guided vehicle when the first automated guided vehicle moves from a first positioning marker to a second positioning marker N times, and the image information of the second positioning marker recognized by the first automated guided vehicle; determining the position deviation between the first automated guided vehicle and the second positioning marker when the first automated guided vehicle moves to the second positioning marker N times according to the image information of the second positioning marker in the N sets of acquisition data, and a total of N position deviations are obtained; determining the moving distances corresponding to the first automated guided vehicle moving from the first positioning marker to the second positioning marker N times according to the odometer information in the N sets of acquisition data, and a total of N moving distances are obtained; determining the first estimated coordinate of the second positioning marker according to the theoretical coordinate of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the externally calibrated deviation of the odometer obtained in advance; correcting the theoretical coordinate of the second positioning marker recorded in the target map according to the first estimated coordinate of the second positioning marker.

[0006] In an exemplary embodiment, the determining the first estimated coordinate of the second positioning marker according to the theoretical coordinate of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the externally calibrated deviation of the odometer obtained in advance includes: when N is equal to 1, the N position deviations are the current position deviation, and the N moving distances are the current moving distance, obtaining the product of the externally calibrated deviation and the current moving distance to obtain a corrected moving distance; determining the first estimated coordinate of the second positioning marker to be equal to the sum of the theoretical coordinate of the first positioning marker, the current position deviation, and the corrected moving distance.

[0007] In an exemplary embodiment, determining the first estimated coordinate of the second positioning marker according to the theoretical coordinate of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the externally calibrated deviation of the odometer obtained in advance includes: when N is greater than or equal to 2, for each set of corresponding position deviation and moving distance among the N position deviations and the N moving distances, perform the following steps to obtain N candidate coordinates of the second positioning marker. When performing the following steps, each set of corresponding position deviation and moving distance is the current position deviation and the current moving distance: Obtain the product of the externally calibrated deviation and the current moving distance to obtain a calibrated moving distance; Determine the candidate coordinate of the second positioning marker to be equal to the sum of the theoretical coordinate of the first positioning marker, the current position deviation, and the calibrated moving distance; Determine the first estimated coordinate of the second positioning marker to be equal to the average value of the N candidate coordinates.

[0008] In an exemplary embodiment, before determining the first estimated coordinate of the second positioning marker according to the theoretical coordinate of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the externally calibrated deviation of the odometer obtained in advance, the method further includes: Obtaining the sample collection data of the first automated guided vehicle, where the sample collection data includes M sets of collection data, M is a positive integer greater than or equal to 2, and the M sets of collection data include the odometer information generated by the odometer on the first automated guided vehicle when the first automated guided vehicle moves from the first reference positioning marker to the second reference positioning marker M times, and the image information of the second reference positioning marker recognized by the first automated guided vehicle; Determining the position deviation between the first automated guided vehicle and the second reference positioning marker when the first automated guided vehicle moves to the second reference positioning marker M times according to the image information of the second reference positioning marker in the M sets of collection data, and a total of M position deviations are obtained; Determining the moving distance corresponding to the first automated guided vehicle moving from the first reference positioning marker to the second reference positioning marker M times according to the odometer information in the M sets of collection data, and a total of M moving distances are obtained; Determining the estimated coordinate of the second reference positioning marker according to the theoretical coordinate of the first reference positioning marker obtained from the target map, the M position deviations, and the M moving distances; Determining the externally calibrated deviation of the odometer according to the theoretical coordinate of the first reference positioning marker, the estimated coordinate of the second reference positioning marker, and the actually measured distance between the first reference positioning marker and the second reference positioning marker measured in advance.

[0009] In an exemplary embodiment, determining the estimated coordinates of the second reference positioning marker according to the theoretical coordinates of the first reference positioning marker obtained from the target map, the M position deviations, and the M moving distances includes: for each pair of the M position deviations and the M moving distances that have a corresponding relationship, performing the following steps to obtain M candidate coordinates of the second reference positioning marker, where when performing the following steps, each pair of the position deviation and the moving distance that have a corresponding relationship is the current position deviation and the current moving distance: determining the candidate coordinates of the second reference positioning marker to be equal to the sum of the theoretical coordinates of the first reference positioning marker, the current position deviation, and the current moving distance; determining the estimated coordinates of the second reference positioning marker to be equal to the average value of the M candidate coordinates.

[0010] In an exemplary embodiment, determining the external parameter deviation of the odometer according to the theoretical coordinates of the first reference positioning marker, the estimated coordinates of the second reference positioning marker, and the actually measured distance between the first reference positioning marker and the second reference positioning marker that is pre-measured includes: determining the estimated distance between the first reference positioning marker and the second reference positioning marker according to the theoretical coordinates of the first reference positioning marker and the estimated coordinates of the second reference positioning marker; determining the external parameter deviation of the odometer to be equal to the ratio of the actually measured distance to the estimated distance.

[0011] In an exemplary embodiment, obtaining the target acquisition data of the first automated guided vehicle includes: obtaining the acquisition data of P automated guided vehicles, where the P automated guided vehicles include the first automated guided vehicle, P is a positive integer greater than or equal to 2, and the acquisition data of the i-th automated guided vehicle among the P automated guided vehicles includes Q i sets of acquisition data, 1 ≤ i ≤ P, Q i is a positive integer greater than or equal to 1, and the Q i sets of acquisition data include the Q iWhen moving from the first positioning marker to the second positioning marker for the second time, the odometer information generated by the odometer on the i-th automated guided vehicle, and the image information of the second positioning marker recognized by the i-th automated guided vehicle; the correcting the theoretical coordinates of the second positioning marker recorded in the target map according to the first estimated coordinate of the second positioning marker includes: determining the true coordinates of the second positioning marker according to P estimated coordinates of the second positioning marker, where the P estimated coordinates include the first estimated coordinate, and the P estimated coordinates are the estimated coordinates of the second positioning marker determined according to the acquisition data of the P automated guided vehicles and the external parameter deviation of the odometers on the P automated guided vehicles; correcting the theoretical coordinates of the second positioning marker recorded in the target map according to the true coordinates of the second positioning marker.

[0012] In an exemplary embodiment, the determining the true coordinates of the second positioning marker according to the P estimated coordinates of the second positioning marker includes: determining the true coordinates of the second positioning marker to be equal to the average value of the P estimated coordinates; or determining the true coordinates of the second positioning marker to be equal to the value obtained by the weighted summation of the P estimated coordinates and P weights, where the i-th weight among the P weights is positively correlated with Q i Is positively correlated.

[0013] In an exemplary embodiment, the correcting the theoretical coordinates of the second positioning marker recorded in the target map according to the true coordinates of the second positioning marker includes: correcting the theoretical coordinates of the second positioning marker recorded in the target map to be the true coordinates of the second positioning marker; or verifying the true coordinates of the second positioning marker, and correcting the theoretical coordinates of the second positioning marker recorded in the target map to be the true coordinates of the second positioning marker when the true coordinates of the second positioning marker pass the verification.

[0014] In an exemplary embodiment, the verifying the true coordinates of the second positioning marker includes: when the target map includes T positioning markers, determining whether the true coordinates of a group of positioning markers used to enclose a target shape among the T positioning markers satisfy a preset verification condition, where T is a positive integer greater than or equal to 2, the T positioning markers include the first positioning marker and the second positioning marker, and the group of positioning markers includes the second positioning marker; determining that the true coordinates of the group of positioning markers all pass the verification when the true coordinates of the group of positioning markers satisfy the preset verification condition.

[0015] In an exemplary embodiment, the correction of the theoretical coordinates of the second positioning marker recorded in the target map according to the first estimated coordinates of the second positioning marker includes: correcting the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker, where the true coordinates of the second positioning marker are the first estimated coordinates; or verifying the true coordinates of the second positioning marker, and when the true coordinates of the second positioning marker pass the verification, correcting the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker.

[0016] According to another embodiment of the present invention, there is also provided a coordinate correction device for a positioning marker, including: a first acquisition module, configured to acquire the acquisition data of a first automated guided vehicle, where the acquisition data of the first automated guided vehicle includes N sets of acquisition data, N is a positive integer greater than or equal to 1, and the N sets of acquisition data include the odometer information generated by the odometer on the first automated guided vehicle when the first automated guided vehicle moves from a first positioning marker to a second positioning marker N times, and the image information of the second positioning marker recognized by the first automated guided vehicle; a first determination module, configured to determine, according to the image information of the second positioning marker in the N sets of acquisition data, the position deviation between the first automated guided vehicle and the second positioning marker when the first automated guided vehicle moves to the second positioning marker N times, and a total of N position deviations are obtained; a second determination module, configured to determine, according to the odometer information in the N sets of acquisition data, the moving distances corresponding to the first automated guided vehicle moving from the first positioning marker to the second positioning marker N times, and a total of N moving distances are obtained; a third determination module, configured to determine the first estimated coordinates of the second positioning marker according to the theoretical coordinates of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the pre-acquired external parameter deviation of the odometer; and a correction module, configured to correct the theoretical coordinates of the second positioning marker recorded in the target map according to the first estimated coordinates of the second positioning marker.

[0017] According to still another embodiment of the present invention, there is also provided a computer-readable storage medium, in which a computer program is stored, where the computer program is configured to execute the steps in any one of the above method embodiments when running.

[0018] According to still another embodiment of the present invention, there is also provided an electronic device, including a memory and a processor, where a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0019] According to the present invention, N sets of acquisition data of the first automated guided vehicle are obtained, where the N sets of acquisition data of the first automated guided vehicle include the odometer information generated by the odometer of the first automated guided vehicle when it moves from the first positioning marker to the second positioning marker N times and the image information of the second positioning marker recognized by the first automated guided vehicle. N position deviations between the first automated guided vehicle and the second positioning marker are determined according to the image information of the second positioning marker included in the N sets of acquisition data, and N moving distances of the first automated guided vehicle moving from the first positioning marker to the second positioning marker are determined according to the odometer information included in the N sets of acquisition data. Then, according to the theoretical coordinates of the first positioning marker, the N position deviations, the N moving distances, and the external parameter deviation of the odometer of the first automated guided vehicle obtained in advance, the first estimated coordinates of the second positioning marker are determined, and then the theoretical coordinates of the second positioning marker recorded in the target map are corrected according to the first estimated coordinates. The purpose of correcting the theoretical coordinates of the second positioning marker based on the position deviations, moving distances, external parameter deviation of the first automated guided vehicle itself, and the theoretical coordinates of the first positioning marker included in the N sets of acquisition data is achieved, that is, the purpose of correcting the coordinate information of the positioning marker according to the actual data collected by the first automated guided vehicle during N runs is achieved, avoiding the problem in the related art that the positioning accuracy of the automated guided vehicle is low due to inaccurate coordinate information of the positioning marker. Therefore, the problem in the related art that the accuracy rate of the coordinate information of the positioning marker is low is solved, and the effect of improving the positioning accuracy of the automated guided vehicle is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 is the hardware structure block diagram of the mobile terminal of the coordinate correction method of the positioning marker in the embodiment of the present invention;

[0021] Figure 2 is the flowchart of the coordinate correction method of the positioning marker according to the embodiment of the present invention;

[0022] Figure 3 is the scenario example according to the embodiment of the present invention Figure 1 ;

[0023] Figure 4 is the scenario example according to the embodiment of the present invention Figure 2 ;

[0024] Figure 5 is the scenario example according to the embodiment of the present invention Figure 3 ;

[0025] Figure 6 is the overall flowchart of a coordinate correction method of a positioning marker according to the embodiment of the present invention;

[0026] Figure 7 is the data processing flowchart according to the specific embodiment of the present invention;

[0027] Figure 8 is the schematic diagram of QR code position estimation according to the specific embodiment of the present invention;

[0028] Figure 9 is the schematic diagram of cyclic redundancy check according to the specific embodiment of the present invention;

[0029] Figure 10 is the structural block diagram of the coordinate correction device for the positioning marker according to the embodiment of the present invention. Specific Embodiments

[0030] In the following, embodiments of the present invention will be described in detail with reference to the accompanying drawings and in conjunction with the embodiments.

[0031] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence.

[0032] The method embodiments provided in the embodiments of the present application can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 is the hardware structural block diagram of the mobile terminal for the coordinate correction method of the positioning marker according to the embodiment of the present invention. As Figure 1 shown, the mobile terminal may include one or more ( Figure 1 only one is shown in Figure 1 the processor 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Among them, the above-mentioned mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those of ordinary skill in the art can understand that Figure 1 the structure shown in Figure 1 is only schematic and does not limit the structure of the above-mentioned mobile terminal. For example, the mobile terminal may further include more or fewer components than

[0033] The memory 104 can be used to store computer programs, such as software programs and modules of application software, such as the computer program corresponding to the coordinate correction method of the positioning marker in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely disposed relative to the processor 102, and these remote memories may be connected to the mobile terminal through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0034] The transmission device 106 is used to receive or send data via a network. Specific examples of the above network may include a wireless network provided by a communication provider of the mobile terminal. In one instance, the transmission device 106 includes a network adapter (Network Interface Controller, abbreviated as NIC), which can be connected to other network devices through a base station and thus can communicate with the Internet. In one instance, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0035] In this embodiment, a coordinate correction method for a positioning marker is provided. Figure 2 It is a flowchart of the coordinate correction method for the positioning marker according to the embodiment of the present invention, as Figure 2 shown, and the process includes the following steps:

[0036] Step S202, obtaining the acquisition data of the first automated guided vehicle, where the acquisition data of the first automated guided vehicle includes N sets of acquisition data, N is a positive integer greater than or equal to 1, and the N sets of acquisition data include the odometer information generated by the odometer on the first automated guided vehicle when the first automated guided vehicle moves from the first positioning marker to the second positioning marker N times, and the image information of the second positioning marker recognized by the first automated guided vehicle;

[0037] Step S204, determining the position deviation between the first automated guided vehicle and the second positioning marker when the first automated guided vehicle moves to the second positioning marker N times according to the image information of the second positioning marker in the N sets of acquisition data, and a total of N position deviations are obtained;

[0038] Step S206: Determine the moving distances corresponding to the N times the first automated guided vehicle moves from the first positioning marker to the second positioning marker based on the odometer information in the N sets of collected data, obtaining N moving distances in total;

[0039] Step S208: Determine the first estimated coordinate of the second positioning marker based on the theoretical coordinates of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the externally calibrated deviation of the odometer obtained in advance;

[0040] Step S210: Correct the theoretical coordinates of the second positioning marker recorded in the target map based on the first estimated coordinate of the second positioning marker.

[0041] Through the above steps, by obtaining N sets of collected data of the first automated guided vehicle, where the N sets of collected data of the first automated guided vehicle include the odometer information generated by the odometer of the first automated guided vehicle when it moves from the first positioning marker to the second positioning marker N times and the image information of the second positioning marker recognized by the first automated guided vehicle, determining N position deviations between the first automated guided vehicle and the second positioning marker based on the image information of the second positioning marker included in the N sets of collected data, and determining N moving distances of the first automated guided vehicle from the first positioning marker to the second positioning marker based on the odometer information included in the N sets of collected data, then determining the first estimated coordinate of the second positioning marker based on the theoretical coordinates of the first positioning marker, the N position deviations, the N moving distances, and the externally calibrated deviation of the odometer of the first automated guided vehicle obtained in advance, and then correcting the theoretical coordinates of the second positioning marker recorded in the target map based on the first estimated coordinate. The purpose of correcting the theoretical coordinates of the second positioning marker based on the position deviations, moving distances, externally calibrated deviation of the first automated guided vehicle itself, and the theoretical coordinates of the first positioning marker included in the N times of collected data is achieved, that is, the purpose of calibrating the coordinate information of the positioning marker according to the actual data collected by the first automated guided vehicle during N operations, avoiding the problem of low positioning accuracy of the automated guided vehicle caused by inaccurate coordinate information of the positioning marker in the related art. Therefore, the problem of low accuracy rate of the coordinate information of the positioning marker in the related art is solved, and the effect of improving the positioning accuracy of the automated guided vehicle is achieved.

[0042] Among them, the execution subject of the above steps can be the server, or the device side, for example, an automatic guided vehicle (AGV) device, or a processor with human-computer interaction capabilities configured on a storage device, or a processing device or processing unit with similar processing capabilities, etc., but not limited to this. The following takes the server executing the above operations as an example (only an exemplary illustration, and in actual operations, other devices or modules can also execute the above operations) for description:

[0043] This embodiment will be described in conjunction with the accompanying drawings. Figure 3 is a scenario example according to an embodiment of the present invention Figure 1 , in the above embodiment, the server obtains the acquisition data of the first automatic guided vehicle (AGV). For example, after the first AGV acquires the data, it reports the data to the server side. Among them, the acquisition data of the first AGV includes N groups of acquisition data, where N is a positive integer greater than or equal to 1. For example, N is 5 (or 10 times, or other values). The N groups of acquisition data include the odometer information generated by the odometer on the first AGV when the first AGV moves from the first positioning marker to the second positioning marker N times, and the image information of the second positioning marker recognized by the first AGV. The first positioning marker is Figure 3 A1 in Figure 3 and the second positioning marker is Figure 3 A2 in Figure 4 is a scenario example according to an embodiment of the present invention Figure 2 , Figure 4 in Met1~Met N represents the odometer information generated each time the first positioning marker moves to the second positioning marker, with a total of N pieces of odometer information, and I1~I NIt represents the image information of the second positioning marker obtained each time the second positioning marker is recognized, with a total of N pieces of image information. For example, a shooting device is installed on the first automatic guided vehicle, and each time the second positioning marker is recognized, the image information of the second positioning marker is collected; according to the image information of the second positioning marker in the N groups of collected data, determine the position deviation between the first automatic guided vehicle and the second positioning marker when the first automatic guided vehicle moves to the second positioning marker N times. For example, by analyzing the image to obtain the position relationship between the center of the second positioning marker and the center of the first automatic guided vehicle, the position deviation between the first automatic guided vehicle and the second positioning marker can be obtained. In this way, through N times, a total of N position deviations can be obtained; and according to the odometer information in the N groups of collected data, determine the moving distances corresponding to the first automatic guided vehicle moving from the first positioning marker to the second positioning marker N times, and a total of N moving distances can be obtained. In practical applications, N moving distances in the X direction and N moving distances in the Y direction can also be obtained respectively from these N moving distances; then, according to the theoretical coordinates of the first positioning marker obtained from the target map, N position deviations, N moving distances, and the pre-obtained external parameter deviation of the odometer, determine the first estimated coordinates of the second positioning marker. In practical applications, the theoretical coordinates of each positioning marker (including the above-mentioned first positioning marker and second positioning marker) are recorded in the target map, that is, based on the position deviations and moving distances included in the N times of collected data, as well as the external parameter deviation of the first automatic guided vehicle itself and the theoretical coordinates of the first positioning marker, the coordinates of the second positioning marker are estimated to obtain the first estimated coordinates; then, according to the first estimated coordinates of the second positioning marker, correct the theoretical coordinates of the second positioning marker recorded in the target map. According to the above method, by analogy, the estimated coordinates of the third positioning marker and the Xth positioning marker can be obtained, and then the theoretical coordinates of each positioning marker are corrected. Through the above embodiments, the purpose of correcting the coordinate information of the positioning marker according to the actual data collected by the first automatic guided vehicle during N operations is achieved, avoiding the problem of low positioning accuracy of the automatic guided vehicle caused by inaccurate coordinate information of the positioning marker in the related technology. Therefore, the problem of low accuracy rate of the coordinate information of the positioning marker in the related technology is solved, and the effect of improving the positioning accuracy of the automatic guided vehicle is achieved.

[0044] Optionally, in practical applications, the acquisition data of multiple automatic guided vehicles can also be obtained, such as P (P≥2) automatic guided vehicles. Similarly, each automatic guided vehicle can obtain one or more sets of acquisition data. Then, according to the same method as described above, an estimated coordinate of a second positioning marker (corresponding to the above-mentioned first estimated coordinate) can be obtained for each automatic guided vehicle, so that P estimated coordinates can be obtained. Then, based on the P estimated coordinates, the actual coordinate of the second positioning marker is comprehensively determined, and then the theoretical coordinate of the second positioning marker is corrected. This can further improve the accuracy of determining the coordinate information of the positioning marker, thereby achieving the effect of improving the positioning accuracy of the automatic guided vehicle.

[0045] In an alternative embodiment, the determining the first estimated coordinate of the second positioning marker according to the theoretical coordinate of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the external parameter deviation of the odometer obtained in advance includes: when N is equal to 1, the N position deviations are the current position deviation, and the N moving distances are the current moving distances, obtaining the product of the external parameter deviation and the current moving distance to obtain a corrected moving distance; determining the first estimated coordinate of the second positioning marker to be equal to the sum of the theoretical coordinate of the first positioning marker, the current position deviation, and the corrected moving distance. In this embodiment, when N = 1, for example, only one set of acquisition data is included in the acquisition data of the first automatic guided vehicle above, that is, the first automatic guided vehicle only completes one movement operation from the first positioning marker to the second positioning marker. The first estimated coordinate of the second positioning marker can be determined according to the theoretical coordinate of the first positioning marker, the current position deviation, the current moving distance, and the external parameter deviation of the odometer. For example, P2 = P1 + S 1-2 *ɑ + Shift, where P2 is the first estimated coordinate of the second positioning marker, P1 is the theoretical coordinate of the first positioning marker, ɑ is the external parameter deviation of the odometer, S 1-2 represents the mileage information generated by the odometer when moving from the first positioning marker to the second positioning marker, and Shift is the position deviation between the first automatic guided vehicle and the second positioning marker determined according to the foregoing image information, which can be referred to Figure 8 as shown in. In practical applications, P1 and P2 can include coordinates in the X and Y directions. In this way, S 1-2 and Shift in the above formula can be calculated respectively according to the coordinate scores in the X and Y directions.

[0046] In an optional embodiment, determining the first estimated coordinate of the second positioning marker according to the theoretical coordinate of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the pre-acquired external parameter deviation of the odometer includes: when N is greater than or equal to 2, for each pair of the N position deviations and the N moving distances that have a corresponding relationship, perform the following steps to obtain N candidate coordinates of the second positioning marker. When performing the following steps, each pair of the position deviation and the moving distance that have a corresponding relationship is the current position deviation and the current moving distance: Obtain the product of the external parameter deviation and the current moving distance to obtain a corrected moving distance; Determine the candidate coordinate of the second positioning marker to be equal to the sum of the theoretical coordinate of the first positioning marker, the current position deviation, and the corrected moving distance; Determine the first estimated coordinate of the second positioning marker to be equal to the average value of the N candidate coordinates. In this embodiment, when N≥2, the first automated guided vehicle obtains N sets of acquisition data. Each set of acquisition data in the N sets of acquisition data includes 1 position deviation and 1 moving distance. For the 1 position deviation and 1 moving distance included in each set of acquisition data, performing the above steps can obtain 1 candidate coordinate of the second positioning marker. In this way, a total of N candidate coordinates can be obtained. Then, the average value of the N candidate coordinates is determined as the first estimated coordinate of the second positioning marker. Through this embodiment, the purpose of determining the first estimated coordinate of the second positioning marker through N sets of acquisition data is achieved.

[0047] In an optional embodiment, before determining the first estimated coordinate of the second positioning marker according to the theoretical coordinate of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the external parameter deviation of the odometer obtained in advance, the method further includes: obtaining sample acquisition data of the first automated guided vehicle, where the sample acquisition data includes M groups of acquisition data, M is a positive integer greater than or equal to 2, and the M groups of acquisition data include the odometer information generated by the odometer on the first automated guided vehicle when the first automated guided vehicle moves from the first reference positioning marker to the second reference positioning marker M times, and the image information of the second reference positioning marker recognized by the first automated guided vehicle; determining, according to the image information of the second reference positioning marker in the M groups of acquisition data, the position deviation between the first automated guided vehicle and the second reference positioning marker when the first automated guided vehicle moves to the second reference positioning marker M times, and a total of M position deviations are obtained; determining, according to the odometer information in the M groups of acquisition data, the moving distances corresponding to the first automated guided vehicle moving from the first reference positioning marker to the second reference positioning marker M times, and a total of M moving distances are obtained; determining the estimated coordinate of the second reference positioning marker according to the theoretical coordinate of the first reference positioning marker obtained from the target map, the M position deviations, and the M moving distances; determining the external parameter deviation of the odometer according to the theoretical coordinate of the first reference positioning marker, the estimated coordinate of the second reference positioning marker, and the actually measured distance between the first reference positioning marker and the second reference positioning marker measured in advance. In practical applications, before determining the first estimated coordinate of the second positioning marker through the acquisition data of the first automated guided vehicle, the external parameter deviation of the odometer can be determined by obtaining the sample acquisition data of the first automated guided vehicle, where the sample acquisition data can be the M groups of acquisition data obtained by the first automated guided vehicle when moving from the first reference positioning marker to the second reference positioning marker M times, such as Figure 3Re1 and Re2 are the first reference positioning marker and the second reference positioning marker respectively. Similarly, each set of collected data includes the odometer information of the first automatic guided vehicle and the image information of the second reference positioning marker recognized. Then, according to the same method as determining the first estimated coordinate of the second positioning marker in the foregoing embodiment, the estimated coordinate of the second reference positioning marker can be determined. The estimated coordinate of the second reference positioning marker here is similar to the first estimated coordinate of the second positioning marker in the foregoing embodiment. Then, based on the theoretical coordinate of the first reference positioning marker, the estimated coordinate of the second reference positioning marker, and the actual measured distance between the first and second reference positioning markers, the external parameter deviation of the odometer is determined. It should be noted that the above first reference positioning marker and the foregoing first positioning marker may be the same or different. Similarly, the above second reference positioning marker and the foregoing second positioning marker may be the same or different. Optionally, in practical applications, data collected by multiple (such as the foregoing P) automatic guided vehicles can also be obtained, the estimated coordinates of the second reference positioning marker are determined respectively, and then based on the P estimated coordinates, the final estimated coordinate of the second reference positioning marker is determined, and further the external parameter deviation of the odometer is determined. Through this embodiment, the purpose of determining the external parameter deviation of the odometer based on the sample collected data and the actual measured distance between the two reference positioning markers is achieved.

[0048] In an alternative embodiment, the determining the estimated coordinate of the second reference positioning marker according to the theoretical coordinate of the first reference positioning marker, the M position deviations, and the M moving distances obtained from the target map includes: for each set of the corresponding position deviation and the moving distance among the M position deviations and the M moving distances, perform the following steps to obtain M candidate coordinates of the second reference positioning marker. When performing the following steps, each set of the corresponding position deviation and the moving distance is the current position deviation and the current moving distance: determine the candidate coordinate of the second reference positioning marker to be equal to the sum of the theoretical coordinate of the first reference positioning marker, the current position deviation, and the current moving distance; determine the estimated coordinate of the second reference positioning marker to be equal to the average value of the M candidate coordinates. In this embodiment, the above sample collected data includes M sets of collected data, and each set of collected data in the M sets of collected data includes 1 position deviation and 1 moving distance, that is, there are M position deviations and M moving distances in total. For the 1 position deviation and 1 moving distance included in each set of collected data, performing the above steps can obtain 1 candidate coordinate of the second reference positioning marker, so a total of M candidate coordinates can be obtained. Then, the average value of the M candidate coordinates is determined as the above-mentioned estimated coordinate of the second reference positioning marker. Through this embodiment, the purpose of determining the estimated coordinate of the second reference positioning marker through M sets of collected data is achieved.

[0049] In an optional embodiment, determining the external parameter deviation of the odometer according to the theoretical coordinates of the first reference positioning marker, the estimated coordinates of the second reference positioning marker, and the actually measured distance between the first reference positioning marker and the second reference positioning marker measured in advance includes: determining the estimated distance between the first reference positioning marker and the second reference positioning marker according to the theoretical coordinates of the first reference positioning marker and the estimated coordinates of the second reference positioning marker; determining the external parameter deviation of the odometer to be equal to the ratio of the actually measured distance to the estimated distance. In this embodiment, the estimated distance between the two reference positioning markers can be determined according to the theoretical coordinates of the first reference positioning marker and the estimated coordinates of the second reference positioning marker above, and then, the ratio of the estimated distance to the actually measured distance above is determined as the external parameter deviation of the odometer. Through this embodiment, the purpose of evaluating the external parameter deviation of the odometer can be achieved.

[0050] In an optional embodiment, obtaining the target acquisition data of the first automated guided vehicle includes: obtaining the acquisition data of P automated guided vehicles, where the P automated guided vehicles include the first automated guided vehicle, P is a positive integer greater than or equal to 2, and the acquisition data of the i-th automated guided vehicle among the P automated guided vehicles includes Q i sets of acquisition data, 1 ≤ i ≤ P, Q i is a positive integer greater than or equal to 1, and the Q i sets of acquisition data include the Q iWhen moving from the first positioning marker to the second positioning marker for the second time, the odometer information generated by the odometer on the i-th automatic guided vehicle, and the image information of the second positioning marker recognized by the i-th automatic guided vehicle; the correcting the theoretical coordinates of the second positioning marker recorded in the target map according to the first estimated coordinate of the second positioning marker includes: determining the true coordinates of the second positioning marker according to the P estimated coordinates of the second positioning marker, where the P estimated coordinates include the first estimated coordinate, and the P estimated coordinates are the estimated coordinates of the second positioning marker determined according to the acquisition data of the P automatic guided vehicles and the external parameter deviation of the odometers on the P automatic guided vehicles; correcting the theoretical coordinates of the second positioning marker recorded in the target map according to the true coordinates of the second positioning marker. In this embodiment, the server can obtain the acquisition data of P automatic guided vehicles. For example, each automatic guided vehicle can report its own acquired acquisition data to the server at a predetermined period. Similarly, the data collected by each automatic guided vehicle can also be one group or multiple groups of data. For example, the acquisition data of the i-th automatic guided vehicle includes Q i groups of acquisition data, Figure 5 is a scenario example according to an embodiment of the present invention Figure 3 , Figure 5 which includes P automatic guided vehicles, such as Agv1, Agv i , Agv P , and each automatic guided vehicle has a corresponding external parameter deviation for its own odometer, such as Figure 5 is the same as the previous embodiment, and each group of acquisition data also includes the odometer information generated by the odometer when the automatic guided vehicle moves from the first positioning marker to the second positioning marker, such as Figure 5 in Met i,j , and the image information I i,j of the second positioning marker recognized by the automatic guided vehicle. Then, according to the same method as in the previous embodiment, P estimated coordinates (similar to the first estimated coordinate in the previous embodiment) can be obtained. Based on the P estimated coordinates, the true coordinates of the second positioning marker can be determined. Furthermore, according to the true coordinates of the second positioning marker, the theoretical coordinates of the second positioning marker recorded in the target map can be corrected. By analogy, the true coordinates of the third positioning marker and the X-th positioning marker can also be obtained, and then the theoretical coordinates of each positioning marker can be corrected. Through this embodiment, the purpose of further improving the accuracy of determining the coordinate information of the positioning marker can be achieved, thereby achieving the effect of improving the positioning accuracy of the automatic guided vehicle.

[0051] In an alternative embodiment, determining the true coordinates of the second positioning marker based on the P estimated coordinates of the second positioning marker includes: determining the true coordinates of the second positioning marker to be equal to the average of the P estimated coordinates; or determining the true coordinates of the second positioning marker to be equal to the value obtained by the weighted summation of the P estimated coordinates and P weights, where the i-th weight among the P weights is positively correlated with Q i In this embodiment, the true coordinates of the second positioning marker can be determined by taking the average of the P estimated coordinates. Optionally, the true coordinates of the second positioning marker can also be obtained by weighted summation of the P estimated coordinates. For example, the weight of each estimated coordinate among the P estimated coordinates can be determined according to the proportion of the number of times each vehicle passes by the second positioning marker in the total number of times. For example, there are 3 automated guided vehicles, such as Agv1, Agv2, and Agv3, and 3 estimated coordinates are obtained, namely Co1, Co2, and Co3. Then Co = ω1*Co1 + ω2*Co2 + ω3*Co3, where ω1, ω2, and ω3 correspond to their respective weight coefficients. Assuming that the number of times Agv1, Agv2, and Agv3 pass by the second positioning marker are 10 times, 6 times, and 4 times respectively, then ω1 = 10 / (10 + 6 + 4) = 0.5, ω2 = 6 / (10 + 6 + 4) = 0.3, ω1 = 4 / (10 + 6 + 4) = 0.2. In this way, the true coordinates of the second positioning marker can be obtained. Through this embodiment, the purpose of determining the true coordinates of the second positioning marker by different methods is achieved.

[0052] In an alternative embodiment, correcting the theoretical coordinates of the second positioning marker recorded in the target map based on the true coordinates of the second positioning marker includes: correcting the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker; or verifying the true coordinates of the second positioning marker, and when the true coordinates of the second positioning marker pass the verification, correcting the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker. In this embodiment, the theoretical coordinates of the second positioning marker recorded in the target map can be corrected to the true coordinates of the second positioning marker as described above. Optionally, the true coordinates of the second positioning marker can be verified first, and after passing the verification, the theoretical coordinates of the second positioning marker recorded in the target map can be corrected based on the true coordinates of the second positioning marker. Through this embodiment, the purpose of correcting the theoretical coordinates of the second positioning marker in the target map based on the true coordinates of the second positioning marker is achieved.

[0053] In an optional embodiment, the verification of the true coordinates of the second positioning marker includes: when the target map includes T positioning markers, determining whether the true coordinates of a set of positioning markers used to enclose the target shape among the T positioning markers meet a preset verification condition, where T is a positive integer greater than or equal to 2, the T positioning markers include the first positioning marker and the second positioning marker, and the set of positioning markers includes the second positioning marker; when the true coordinates of the set of positioning markers meet the preset verification condition, determining that the true coordinates of the set of positioning markers all pass the verification. In this embodiment, the acquisition method of the true coordinates of each positioning marker among the above T positioning markers is the same as the acquisition method of the true coordinates of the second positioning marker in the foregoing embodiment. The above target shape can be a closed shape or a non-closed shape. Among them, the closed shape can be a ring, a triangle, etc. For example, taking a ring as an example, if a ring includes 4 positioning markers, assuming the original coordinates of the i-th positioning marker are (CODEix, CODEiy), the coordinates of the second positioning marker are deduced from the coordinates of the first positioning marker as (code12x, code12y), the coordinates of the third positioning marker are deduced from the coordinates of the second positioning marker as (code23x, code23y), the coordinates of the fourth positioning marker are deduced from the coordinates of the third positioning marker as (code34x, code34y), and the coordinates of the first positioning marker are deduced from the coordinates of the fourth positioning marker as (code41x, code41y), then in the way of 1→2→3→4→1 ring verification, the verification is carried out according to the following formula: (code12 x -CODE1 x )+(code23 x -CODE2 x )+(code34 x -CODE3 x )+(code41 x -CODE4 x )≈0. If the above formula holds, it can be considered that the true coordinates of the above 4 positioning markers meet the preset verification condition. In an optional example, T is a positive integer greater than or equal to 3. Through this embodiment, the purpose of verifying the true coordinates of the positioning marker is achieved, thereby improving the accuracy of determining the true coordinates of the positioning marker.

[0054] In an optional embodiment, the correction of the theoretical coordinates of the second positioning marker recorded in the target map according to the first estimated coordinates of the second positioning marker includes: correcting the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker, where the true coordinates of the second positioning marker are the first estimated coordinates; or verifying the true coordinates of the second positioning marker, and when the true coordinates of the second positioning marker pass the verification, correcting the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker. In this embodiment, the theoretical coordinates of the second positioning marker recorded in the target map can be corrected to the above-mentioned first estimated coordinates; optionally, the true coordinates of the second positioning marker can be verified first, and after the verification passes, the theoretical coordinates of the second positioning marker recorded in the target map can be corrected based on the true coordinates of the second positioning marker. Through this embodiment, the purpose of correcting the theoretical coordinates of the second positioning marker in the target map is achieved.

[0055] Obviously, the above-described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Taking the error evaluation and correction of the two-dimensional code positioning marker as an example, the embodiments of the present invention will be specifically described below.

[0056] In this embodiment, it is proposed to evaluate the true coordinate information of the two-dimensional code by using the data information collected in the multi-vehicle working stage, and give the relative position relationship between the true position and the theoretical position for each two-dimensional code node (corresponding to the foregoing positioning marker, such as the first positioning marker), and at the same time give the individual wheel odometer error of each vehicle (corresponding to the foregoing automatic guided vehicle, such as the first automatic guided vehicle) to ensure the reliability of the wheel odometer during the long-term operation of the AGV.

[0057] In this embodiment, the parameters related to data collection are as follows: the AGV moves from the two-dimensional code node 1 (corresponding to the foregoing first positioning marker) to the two-dimensional code node 2 (corresponding to the foregoing second positioning marker), such as Figure 3 where the AGV moves from A1 to A2. Among them, the theoretical coordinates corresponding to node 1 are (Point1 x , Point1 y ); the theoretical coordinates corresponding to node 2 are (Point2 x , Point2 y ); the estimated (true) coordinates corresponding to node 2 are (point2 x , point2 y ); the position relationship between the center of the two-dimensional code and the center of the AGV obtained from the two-dimensional code image analysis is (shift x , shift y); When node two is recognized, the coordinates of the AGV's self-positioning are (pos x , pos y ); Generally, (point2 x , point2 y ) = (pos x + shift x , pos y + shift y ).

[0058] Figure 6 is the overall flowchart of a coordinate correction method for positioning markers according to an embodiment of the present invention. The process includes:

[0059] S602, single-vehicle data collection;

[0060] S604, multi-vehicle data collection;

[0061] S606, data analysis, which includes analyzing in combination with the pre-measured distance between benchmark QR code nodes and multi-vehicle data;

[0062] S608, output the real topo node information and issue the odometer parameters.

[0063] In the above process, the data collection stage is mainly divided into two steps, as follows:

[0064] (1) Single-vehicle data collection: During the working process, each AGV will separately record the QR code image information and the wheel odometer information. Among them, the odometer information will fuse the position information of the parsed QR code, so the odometer information should include the QR code node name of the fusion. Finally, single-vehicle data collection also needs to ensure according to a certain strategy that the size of the recorded data file will not affect the normal operation of the AGV.

[0065] (2) Multi-vehicle data collection: When the server issues a data collection request, it will upload the AGV data collection file according to the strategy, and the upload process should not interfere with normal network communication and affect the basic work tasks of the AGV. For example, it can be set to issue a data collection instruction according to a predetermined cycle, such as a certain idle period every day, or a certain fixed time every day, such as 22:00 at night, and each AGV will upload the data it has collected to the server.

[0066] Before data analysis, a certain number of reference QR code node pairs (corresponding to the aforementioned first reference positioning marker and second reference positioning marker) should be selected, and the true distance distance between the node pairs (corresponding to the aforementioned actual measurement distance) should be measured. Among them, the measurement accuracy should be significantly less than the point accuracy requirement for the AGV motion control under QR code navigation. For example, the measurement accuracy is 1 mm. There are no specific requirements for the selection of the reference QR code node pairs, but generally they are path segments that the AGV usually reaches. The more the number, the more reliable the result. For the purpose of reducing the workload, it is advisable to measure three to five pairs.

[0067] After completing data collection and the measurement of the spacing between the reference QR code nodes, data analysis can be carried out. Considering that the implementation of this stage requires a relatively complex amount of calculation, it is usually implemented on the server side. However, it does not rule out that with the improvement of the AGV performance, the AGV can be specified as a relay node, and the data collection and processing tasks can also be deployed on this AGV.

[0068] Data analysis is mainly divided into the following three stages: preparation stage, single vehicle data processing, and multi-vehicle joint data analysis. Figure 7 It is the data processing flow chart according to the specific embodiment of the present invention, and the specific steps are as follows:

[0069] (1) Preparation stage:

[0070] 1) Read the map file (corresponding to the aforementioned target map), and obtain the theoretical coordinates of the QR code nodes and the node connectivity information;

[0071] 2) Parse the data acquisition file, and obtain the vehicle IP and the odometer information and QR code image analysis results recorded during the operation;

[0072] 3) Problem node analysis and elimination: ① During the data acquisition process, it cannot be guaranteed that every QR code node passed by will be effectively recorded. Especially in the initial stage of the map activation, the coordinate deviation of the QR code nodes is relatively large, and it is easy to miss due to the failure to recognize the QR code nodes; record the code values and frequencies of the missing QR codes, and the relevant QR code image analysis results and odometer information will not be included in the subsequent calculations; ② According to the QR code image parsing score, analyze the recognizability of the QR codes, and give an alarm for the nodes with poor recognizability and high missing frequencies, and implement the replacement of the QR code node stickers; ③ Analyze the driving route between two nodes according to the odometer data; if the driving route is not a straight line, that is, the driving direction of the AGV deviates significantly during the driving process, then mark this group of data.

[0073] (2) Single vehicle data processing stage:

[0074] 1) Estimate the coordinate information of the reference QR code: Calculate the node coordinate information (point2 x , point2 y ) for each AGV every time it passes through the reference QR code node based on the odometer information and the QR code recognition information.

[0075] 2) Eliminate outliers: Since there are disturbances in the sensor data acquisition, this step eliminates the data with a large deviation from the data centroid according to the mathematical statistics method, including but not limited to eliminating outliers based on n times the standard deviation.

[0076] 3) Calculate the external deviation parameter of the odometer: Calculate the mean value based on the data after eliminating outliers, and calculate the external deviation parameter of the odometer on the basis of the obtained mean value where distance is the true measured distance between the reference QR code nodes.

[0077] 4) Based on the new external deviation parameter α of the odometer o Re-calculate the position of the QR code node. Because, in the previous calculation, it was defaulted that the measured value of the wheel odometer was the true value, but in fact, the actual error of the wheel odometer is about 1 cm per 1 m of travel or even larger, which seriously affects the calculation of the true coordinates of the QR code. As Figure 8 shown, Figure 8 is a schematic diagram of QR code position estimation according to a specific embodiment of the present invention. In the figure, the AGV moves from node 1 (corresponding to the aforementioned first positioning marker or the first reference positioning marker) to node 2 (corresponding to the aforementioned second positioning marker or the second reference positioning marker). Node 1 and node 2 respectively correspond to Figure 4 A1 and A2 in Figure 8 ; S in 1-2 represents the odometer information generated when the AGV moves from node 1 to node 2, and Shift represents the position deviation between the center point of the AGV and the center point of the second positioning marker; the actual point center coordinates of the AGV can be obtained by extrapolation interpolation in combination with the external deviation parameter α of the odometer o . It should be noted that when the motion control route between the QR code nodes is an arc, the center coordinates of the AGV are on the extension line of the connection between the head and the tail of the arc, and are extrapolated proportionally according to the line segment length between the two points at the head and the tail of the arc and α o .

[0078] 5) Compare the external deviation parameters α of the odometer obtained before and after o . When the change is large, jump to step 1 to recalculate; otherwise, exit the loop.

[0079] (3) Multi-vehicle joint data analysis stage:

[0080] 1) According to the data collected by multiple vehicles, combined with the calculated external deviation parameter of the odometer, calculate the true coordinate information (X of the QR codei , Y i ): For each AGV, a series of true coordinate information of the QR codes can be obtained. Since the frequencies of each vehicle passing through the specified path are different, the average value is taken according to the weights, and the obtained coordinate information is the estimated true coordinates of the QR codes (point2 x , point2 y ), and the standard deviation (sd x , sd y ).

[0081] 2) Node coordinate circular check: When estimating the true coordinates of the QR code nodes, the true coordinates of the second node are estimated based on the first QR code node that integrates the coordinate information. The circular check schematic diagram is as Figure 9 shown Figure 9 is the circular check schematic diagram according to the specific embodiment of the present invention. Taking the circular check composed of 4 nodes as an example Figure 9 includes 4 nodes (equivalent to the aforementioned first positioning marker or second positioning marker): Code1, Code2, Code3, and Code4. Denote the original coordinates of Codei as (CODEi x , CODEi y ), and the coordinates of Codej estimated from Codei are (codeij x , codeij y ), where Code1, Code2, Code3, and Code4 correspond to QR code 1, QR code 2, QR code 3, and QR code 4 respectively.

[0082] CODE1 x ≈ CODE1 x +(code12 x -CODE1 x )+(code21 x -CODE2 x )

[0083] =>0≈(code12 x -CODE1 x )+(code21 x -CODE2 x )

[0084] And 0≈(code12 y -CODE1 y )+(code21 y -CODE2 y );

[0085] Similarly, there are

[0086] 0≈(code12 x -CODE1 x )+(code23 x -CODE2 x )+(code34 x -CODE3 x )

[0087] +(code41 x -CODE4 x )

[0088] 0≈(code12 y -CODE1 y )+(code23 y -CODE2 y )+(code34 y -CODE3y + code41y - CODE4y;

[0089] When the formula is approximately 0, it is considered that the calculation result of the associated coordinates meets the requirements, where the approximation error should be less than the accuracy requirement for the AGV motion control to reach the point. For the nodes that fail to pass the verification, with the true calculated coordinates (point2 x , point2 y ) as the center, within the range of one standard deviation (sd x , sd y ), search for the optimal value and update it to the true calculated coordinates (point2′ x , point2′ y ) of this node.

[0090] 3) Update of the true coordinates of the Topo (topology) nodes: When the true coordinates of all nodes meet the circular check, select any QR code node as the center and update the coordinates of the QR code nodes of the entire map in a radiation manner. Taking the node relationship in Figure 9 as an example, if Code1 is selected as the center, then Code1 (CODE1 x , CODE1 y ), Code2 (code12 x , code12 y ), Code3 (code12 x + code23 x - CODE2 x , code12 y + code23 y - CODE2 y ), Code4 (code14 x , code14 y ).

[0091] After data analysis, update the corresponding information in the topo map (corresponding to the aforementioned target map) according to the analysis results, that is, the true coordinate information of the QR code nodes in the topo map, and update the external parameter α of the wheel odometer of each AGV. o 。

[0092] Finally, carry out a new round of data collection and carry out maintenance tasks regularly.

[0093] In the above embodiments, the deviation between the true coordinates and the theoretical coordinates of the positioning marker is solved in the way of positioning and deviation correction; based on the data processing problem, the true coordinates of the positioning marker are deduced by using multi-vehicle data; the QR code navigation maintenance is carried out in a periodic manner.

[0094] Through the above embodiments, based on multi-vehicle data analysis, it is possible to provide an evaluation and coordinate correction method for the true coordinates of markers in maps based on positioning auxiliary markers such as QR code navigation for AGVs. Compared with other solutions in the related art, the advantages are as follows:

[0095] (1) Consider the deviation between the theoretical coordinate information and the true coordinate information of the nodes of the QR code positioning marker, ensure the accuracy and stability of QR code logistics navigation and distribution, and reduce the probability of track deviation.

[0096] (2) Consider the clarity and damage of the QR code stickers, and carry out regular maintenance to ensure the stability of QR code navigation.

[0097] (3) No additional hardware facilities are required for assistance. The correction of the true coordinate deviation of the QR code can be achieved only with the cooperation of the AGV, and the influence of the environmental scene on the deviation correction is reduced.

[0098] (4) Finally, the circular check of the positioning coordinates further improves the reliability of the true coordinates of the marker.

[0099] (5) Periodic maintenance for continuous guarantee.

[0100] It should be noted that: (1) Any AGV can be used to give an alarm when the deviation between the theoretical value and the actual value of the QR code node is too large, but only a general deviation direction can be provided. If the wheel odometer of the AGV has just been calibrated and the odometer is very reliable, the node coordinate information calculated by the AGV will also be relatively reliable. However, considering the differences in consistency among different AGVs, for example, calibration vehicle A believes that the distance between node a and node b is 185 cm, but after vehicle B travels 185 cm from node a, it does not reach the center of node b and is still 2.3 cm away from b, that is, vehicle B believes that the distance from node a to node b is 187.5 cm. This error may also gradually change with the running mileage of the AGV, increasing the risk of node deviation; (2) The purpose of multiple single-vehicle runs and multi-vehicle data analysis is to calculate the most reliable node coordinates and avoid accidental errors to the greatest extent.

[0101] The core of the embodiment of the present invention is to achieve the periodic maintenance of the QR code navigation method. The core purpose of the first few times is to obtain the actual coordinate information of the QR code, and the core in the later stage is the analysis of the QR code recognizability and the loss error of the odometer. The solution of the embodiment of the present invention relies on a large amount of data information to obtain a more reliable analysis result. The application of the solution includes, but is not limited to, the scenario of QR code navigation, and can also be used for barcodes such as texture codes, one-dimensional codes, and any graphic positioning marker that can contain positioning information.

[0102] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases, the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0103] In this embodiment, a coordinate correction device for a positioning marker is also provided. Figure 10 It is a structural block diagram of the coordinate correction device for the positioning marker according to the embodiment of the present invention, as Figure 10 shown. The device includes:

[0104] The first acquisition module 1002 is configured to acquire the acquisition data of the first automated guided vehicle. The acquisition data of the first automated guided vehicle includes N sets of acquisition data, where N is a positive integer greater than or equal to 1. The N sets of acquisition data include the odometer information generated by the odometer on the first automated guided vehicle when the first automated guided vehicle moves from the first positioning marker to the second positioning marker N times, and the image information of the second positioning marker recognized by the first automated guided vehicle.

[0105] The first determination module 1004 is configured to determine the position deviation between the first automated guided vehicle and the second positioning marker when the first automated guided vehicle moves to the second positioning marker N times according to the image information of the second positioning marker in the N sets of acquisition data, and a total of N position deviations are obtained.

[0106] The second determination module 1006 is configured to determine the moving distances corresponding to the first automated guided vehicle moving from the first positioning marker to the second positioning marker N times according to the odometer information in the N sets of acquisition data, and a total of N moving distances are obtained.

[0107] The third determination module 1008 is configured to determine the first estimated coordinate of the second positioning marker according to the theoretical coordinate of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the external parameter deviation of the odometer obtained in advance.

[0108] The correction module 1010 is configured to correct the theoretical coordinate of the second positioning marker recorded in the target map according to the first estimated coordinate of the second positioning marker.

[0109] In an optional embodiment, the third determination module 1008 includes: a first obtaining unit, configured to obtain the product of the external parameter deviation and the current moving distance to obtain a corrected moving distance when N is equal to 1, the N position deviations are the current position deviation, and the N moving distances are the current moving distance; a first determination unit, configured to determine the first estimated coordinate of the second positioning marker to be equal to the sum of the theoretical coordinate of the first positioning marker, the current position deviation, and the corrected moving distance.

[0110] In an optional embodiment, the above-mentioned third determination module 1008 includes: a second acquisition unit, configured to, when N is greater than or equal to 2, for each pair of the N position deviations and the N movement distances that have a corresponding relationship, perform the following steps to obtain N candidate coordinates of the second positioning marker, where when performing the following steps, each pair of the position deviation and the movement distance that have a corresponding relationship are the current position deviation and the current movement distance: obtain the product of the external parameter deviation and the current movement distance to obtain a corrected movement distance; determine the candidate coordinate of the second positioning marker to be equal to the sum of the theoretical coordinate of the first positioning marker, the current position deviation, and the corrected movement distance; a second determination unit, configured to determine the first estimated coordinate of the second positioning marker to be equal to the average value of the N candidate coordinates.

[0111] In an optional embodiment, the above-mentioned device further includes: a second acquisition module, configured to acquire the sample acquisition data of the first automatic guided vehicle before determining the first estimated coordinate of the second positioning marker according to the theoretical coordinate of the first positioning marker, the N position deviations, the N movement distances, and the external parameter deviation of the odometer acquired in advance from the target map, where the sample acquisition data includes M sets of acquisition data, M is a positive integer greater than or equal to 2, and the M sets of acquisition data include the odometer information generated by the odometer on the first automatic guided vehicle when the first automatic guided vehicle moves from the first reference positioning marker to the second reference positioning marker M times, and the image information of the second reference positioning marker recognized by the first automatic guided vehicle; a first acquisition module, configured to determine the position deviation between the first automatic guided vehicle and the second reference positioning marker when the first automatic guided vehicle moves to the second reference positioning marker M times according to the image information of the second reference positioning marker in the M sets of acquisition data, and a total of M position deviations are obtained; a second acquisition module, configured to determine the movement distance corresponding to the first automatic guided vehicle moving from the first reference positioning marker to the second reference positioning marker M times according to the odometer information in the M sets of acquisition data, and a total of M movement distances are obtained; a fourth determination module, configured to determine the estimated coordinate of the second reference positioning marker according to the theoretical coordinate of the first reference positioning marker, the M position deviations, and the M movement distances acquired from the target map; a fifth determination module, configured to determine the external parameter deviation of the odometer according to the theoretical coordinate of the first reference positioning marker, the estimated coordinate of the second reference positioning marker, and the actually measured distance between the first reference positioning marker and the second reference positioning marker measured in advance.

[0112] In an optional embodiment, the above-mentioned fourth determination module includes: a third acquisition unit, configured to perform the following steps for each set of the position deviation and the moving distance among the M position deviations and the M moving distances that have a corresponding relationship, to obtain M candidate coordinates of the second reference positioning marker, where when performing the following steps, each set of the position deviation and the moving distance that have a corresponding relationship is the current position deviation and the current moving distance: determining the candidate coordinate of the second reference positioning marker to be equal to the sum of the theoretical coordinate of the first reference positioning marker, the current position deviation, and the current moving distance; a third determination unit, configured to determine the estimated coordinate of the second reference positioning marker to be equal to the average value of the M candidate coordinates.

[0113] In an optional embodiment, the above-mentioned fifth determination module includes: a fourth determination unit, configured to determine the estimated distance between the first reference positioning marker and the second reference positioning marker according to the theoretical coordinate of the first reference positioning marker and the estimated coordinate of the second reference positioning marker; a fifth determination unit, configured to determine the external parameter deviation of the odometer to be equal to the ratio of the actual measured distance to the estimated distance.

[0114] In an optional embodiment, the above-mentioned first acquisition module 1002 includes: a first acquisition unit, configured to acquire the acquisition data of P automatic guided vehicles, where the P automatic guided vehicles include the first automatic guided vehicle, P is a positive integer greater than or equal to 2, and the acquisition data of the i-th automatic guided vehicle among the P automatic guided vehicles includes Q i sets of acquisition data, 1 ≤ i ≤ P, and Q i is a positive integer greater than or equal to 1, and the Q i sets of acquisition data include the odometer information generated by the odometer on the i-th automatic guided vehicle when the i-th automatic guided vehicle moves from the first positioning marker to the second positioning marker Q i times, and the image information of the second positioning marker recognized by the i-th automatic guided vehicle; the above-mentioned correction module 1010 includes: a sixth determination unit, configured to determine the true coordinate of the second positioning marker according to the P estimated coordinates of the second positioning marker, where the P estimated coordinates include the first estimated coordinate, and the P estimated coordinates are the estimated coordinates of the second positioning marker determined according to the acquisition data of the P automatic guided vehicles and the external parameter deviation of the odometers on the P automatic guided vehicles; a first correction unit, configured to correct the theoretical coordinate of the second positioning marker recorded in the target map according to the true coordinate of the second positioning marker.

[0115] In an alternative embodiment, the above-mentioned sixth determination unit includes: a first determination subunit, configured to determine the true coordinates of the second positioning marker to be equal to the average value of the P estimated coordinates; or, a second determination subunit, configured to determine the true coordinates of the second positioning marker to be equal to the value obtained by performing a weighted sum of the P estimated coordinates and P weights, where the i-th weight among the P weights is positively correlated with Q i is positively correlated.

[0116] In an alternative embodiment, the above-mentioned first correction unit includes: a first correction subunit, configured to correct the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker; or, a first processing subunit, configured to verify the true coordinates of the second positioning marker, and in the case where the true coordinates of the second positioning marker pass the verification, correct the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker.

[0117] In an alternative embodiment, the above-mentioned first processing subunit can verify the true coordinates of the second positioning marker in the following manner: in the case where the target map includes T positioning markers, determine whether the true coordinates of a group of positioning markers used to enclose the target shape among the T positioning markers meet a preset verification condition, where T is a positive integer greater than or equal to 2, the T positioning markers include the first positioning marker and the second positioning marker, and the group of positioning markers includes the second positioning marker; in the case where the true coordinates of the group of positioning markers meet the preset verification condition, determine that the true coordinates of the group of positioning markers all pass the verification.

[0118] In an alternative embodiment, the above-mentioned correction module 1010 includes: a second correction unit, configured to correct the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker, where the true coordinates of the second positioning marker are the first estimated coordinates; or, a processing unit, configured to verify the true coordinates of the second positioning marker, and in the case where the true coordinates of the second positioning marker pass the verification, correct the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker.

[0119] It should be noted that the above-mentioned various modules can be implemented by software or hardware. For the latter, it can be implemented in the following manner, but not limited thereto: the above-mentioned modules are all located in the same processor; or, the above-mentioned various modules are respectively located in different processors in any combination form.

[0120] Embodiments of the present invention also provide a computer-readable storage medium storing a computer program, where the computer program is configured to execute the steps in any of the above method embodiments when running.

[0121] In an exemplary embodiment, the above computer-readable storage medium may include, but is not limited to: various media such as USB flash drives, read-only memories (ROM), random access memories (RAM), mobile hard disks, magnetic disks, or optical discs that can store computer programs.

[0122] Embodiments of the present invention also provide an electronic device including a memory and a processor, where the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any of the above method embodiments.

[0123] In an exemplary embodiment, the above electronic device may further include a transmission device and input / output devices, where the transmission device is connected to the above processor, and the input / output devices are connected to the above processor.

[0124] Specific examples in this embodiment may refer to the examples described in the above embodiments and exemplary embodiments, and will not be repeated here.

[0125] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed on a network composed of multiple computing devices. They can be implemented by program codes executable by the computing device, so that they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described can be executed in a different order from here, or they can be separately fabricated into individual integrated circuit modules, or multiple modules or steps among them can be fabricated into a single integrated circuit module to implement. Thus, the present invention is not limited to any specific combination of hardware and software.

[0126] The above are only preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for correcting the coordinates of a positioning marker, characterized in that, Including: Obtain the acquisition data of the first automated guided vehicle, where the acquisition data of the first automated guided vehicle includes N groups of acquisition data, N is a positive integer greater than or equal to 1, and the N groups of acquisition data include the odometer information generated by the odometer on the first automated guided vehicle when the first automated guided vehicle moves from the first positioning marker to the second positioning marker N times, and the image information of the second positioning marker recognized by the first automated guided vehicle; According to the image information of the second positioning marker in the N groups of acquisition data, determine the position deviation between the first automated guided vehicle and the second positioning marker when the first automated guided vehicle moves to the second positioning marker N times, and a total of N position deviations are obtained; According to the odometer information in the N groups of acquisition data, determine the moving distances corresponding to the first automated guided vehicle moving from the first positioning marker to the second positioning marker N times, and a total of N moving distances are obtained; According to the theoretical coordinates of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the externally calibrated deviation of the odometer obtained in advance, determine the first estimated coordinates of the second positioning marker; According to the first estimated coordinates of the second positioning marker, correct the theoretical coordinates of the second positioning marker recorded in the target map.

2. The method according to claim 1, wherein The determining the first estimated coordinates of the second positioning marker according to the theoretical coordinates of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the externally calibrated deviation of the odometer obtained in advance includes: When N is equal to 1, the N position deviations are the current position deviation, and the N moving distances are the current moving distance, obtain the product of the externally calibrated deviation and the current moving distance to obtain the calibrated moving distance; Determine the first estimated coordinates of the second positioning marker to be equal to the sum of the theoretical coordinates of the first positioning marker, the current position deviation, and the calibrated moving distance.

3. The method according to claim 1, characterized in that The determining the first estimated coordinates of the second positioning marker according to the theoretical coordinates of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the externally calibrated deviation of the odometer obtained in advance includes: When N is greater than or equal to 2, for each pair of the position deviation and the moving distance with a corresponding relationship among the N position deviations and the N moving distances, perform the following steps to obtain N candidate coordinates of the second positioning marker. When performing the following steps, each pair of the position deviation and the moving distance with a corresponding relationship is the current position deviation and the current moving distance: obtain the product of the externally calibrated deviation and the current moving distance to obtain the calibrated moving distance; determine the candidate coordinates of the second positioning marker to be equal to the sum of the theoretical coordinates of the first positioning marker, the current position deviation, and the calibrated moving distance; Determine the first estimated coordinate of the second positioning marker to be equal to the average of the N candidate coordinates.

4. The method according to claim 1, wherein Before determining the first estimated coordinate of the second positioning marker according to the theoretical coordinate of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the external parameter deviation of the odometer obtained in advance, the method further includes: Obtain the sample collection data of the first automated guided vehicle, where the sample collection data includes M sets of collection data, M is a positive integer greater than or equal to 2, and the M sets of collection data include the odometer information generated by the odometer on the first automated guided vehicle when the first automated guided vehicle moves from the first reference positioning marker to the second reference positioning marker M times, and the image information of the second reference positioning marker recognized by the first automated guided vehicle; According to the image information of the second reference positioning marker in the M sets of collection data, determine the position deviation between the first automated guided vehicle and the second reference positioning marker when the first automated guided vehicle moves to the second reference positioning marker M times, and a total of M position deviations are obtained; According to the odometer information in the M sets of collection data, determine the moving distances corresponding to the first automated guided vehicle moving from the first reference positioning marker to the second reference positioning marker M times, and a total of M moving distances are obtained; According to the theoretical coordinate of the first reference positioning marker obtained from the target map, the M position deviations, and the M moving distances, determine the estimated coordinate of the second reference positioning marker; According to the theoretical coordinate of the first reference positioning marker, the estimated coordinate of the second reference positioning marker, and the actually measured distance between the first reference positioning marker and the second reference positioning marker measured in advance, determine the external parameter deviation of the odometer.

5. The method according to claim 4, wherein The determining the estimated coordinate of the second reference positioning marker according to the theoretical coordinate of the first reference positioning marker obtained from the target map, the M position deviations, and the M moving distances includes: For each set of corresponding position deviation and moving distance among the M position deviations and the M moving distances, perform the following steps to obtain M candidate coordinates of the second reference positioning marker. When performing the following steps, each set of corresponding position deviation and moving distance is the current position deviation and the current moving distance: Determine the candidate coordinate of the second reference positioning marker to be equal to the sum of the theoretical coordinate of the first reference positioning marker, the current position deviation, and the current moving distance; Determine the estimated coordinate of the second reference positioning marker to be equal to the average of the M candidate coordinates.

6. The method according to claim 4, characterized in that The determining the external parameter deviation of the odometer according to the theoretical coordinate of the first reference positioning marker, the estimated coordinate of the second reference positioning marker, and the actually measured distance between the first reference positioning marker and the second reference positioning marker measured in advance includes: Determine the estimated distance between the first reference positioning marker and the second reference positioning marker according to the theoretical coordinates of the first reference positioning marker and the estimated coordinates of the second reference positioning marker; Determine the external parameter deviation of the odometer to be equal to the ratio of the actual measured distance to the estimated distance.

7. The method according to claim 1, wherein: Obtaining the acquisition data of the first automated guided vehicle includes: obtaining the acquisition data of P automated guided vehicles, where the P automated guided vehicles include the first automated guided vehicle, P is a positive integer greater than or equal to 2, and the acquisition data of the i-th automated guided vehicle among the P automated guided vehicles includes Q i sets of acquisition data, 1 ≤ i ≤ P, Q i is a positive integer greater than or equal to 1, and the Q i sets of acquisition data include the odometer information generated by the odometer on the i-th automated guided vehicle and the image information of the second positioning marker recognized by the i-th automated guided vehicle when the i-th automated guided vehicle moves from the first positioning marker to the second positioning marker Q i times; The correction of the theoretical coordinates of the second positioning marker recorded in the target map according to the first estimated coordinate of the second positioning marker includes: determining the true coordinates of the second positioning marker according to P estimated coordinates of the second positioning marker, where the P estimated coordinates include the first estimated coordinate, and the P estimated coordinates are the estimated coordinates of the second positioning marker determined according to the acquisition data of the P automated guided vehicles and the external parameter deviation of the odometers on the P automated guided vehicles; correcting the theoretical coordinates of the second positioning marker recorded in the target map according to the true coordinates of the second positioning marker.

8. The method according to claim 7, wherein The determination of the true coordinates of the second positioning marker according to the P estimated coordinates of the second positioning marker includes: Determine the true coordinates of the second positioning marker to be equal to the average value of the P estimated coordinates; or Determine the true coordinates of the second positioning marker to be equal to the value obtained by the weighted sum of the P estimated coordinates and P weights, where the i-th weight among the P weights is positively correlated with Q i Show a positive correlation.

9. The method according to claim 7, wherein The correction of the theoretical coordinates of the second positioning marker recorded in the target map according to the true coordinates of the second positioning marker includes: Correct the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker; or Verify the true coordinates of the second positioning marker, and when the true coordinates of the second positioning marker pass the verification, correct the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker.

10. The method according to claim 9, wherein The verification of the true coordinates of the second positioning marker includes: When the target map includes T positioning markers, determine whether the true coordinates of a group of positioning markers used to enclose the target shape among the T positioning markers meet the preset verification conditions, where T is a positive integer greater than or equal to 2, the T positioning markers include the first positioning marker and the second positioning marker, and the group of positioning markers includes the second positioning marker; When the true coordinates of the group of positioning markers meet the preset verification conditions, determine that the true coordinates of the group of positioning markers all pass the verification.

11. The method according to claim 1, wherein The correction of the theoretical coordinates of the second positioning marker recorded in the target map according to the first estimated coordinate of the second positioning marker includes: Correct the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker, where the true coordinates of the second positioning marker are the first estimated coordinate; or Verify the true coordinates of the second positioning marker, and when the true coordinates of the second positioning marker pass the verification, correct the theoretical coordinates of the second positioning marker recorded in the target map to the true coordinates of the second positioning marker.

12. A coordinate correction device for positioning markers, characterized in that, Including: A first acquisition module, configured to acquire the acquisition data of a first automated guided vehicle, where the acquisition data of the first automated guided vehicle includes N sets of acquisition data, N is a positive integer greater than or equal to 1, and the N sets of acquisition data include the odometer information generated by the odometer on the first automated guided vehicle when the first automated guided vehicle moves from a first positioning marker to a second positioning marker N times, and the image information of the second positioning marker recognized by the first automated guided vehicle; A first determination module, configured to determine the position deviation between the first automated guided vehicle and the second positioning marker when the first automated guided vehicle moves to the second positioning marker N times according to the image information of the second positioning marker in the N sets of acquisition data, and a total of N position deviations are obtained; A second determination module, configured to determine the moving distances corresponding to the first automated guided vehicle moving from the first positioning marker to the second positioning marker N times according to the odometer information in the N sets of acquisition data, and a total of N moving distances are obtained; A third determination module, configured to determine the first estimated coordinates of the second positioning marker according to the theoretical coordinates of the first positioning marker obtained from the target map, the N position deviations, the N moving distances, and the pre-acquired external parameter deviation of the odometer; A correction module, configured to correct the theoretical coordinates of the second positioning marker recorded in the target map according to the first estimated coordinates of the second positioning marker.

13. A computer-readable storage medium, characterized in that, A computer program is stored in the computer-readable storage medium, where when the computer program is executed by a processor, the steps of the method described in any one of claims 1 to 11 are implemented.

14. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, the steps of the method described in any one of claims 1 to 11 are implemented.

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