Robot positioning recovery method and device, computer equipment and storage medium

Abstract

The invention relates to a robot positioning recovery method and device, computer equipment and a storage medium, and is applied to the technical field of robot positioning recovery. The method comprises the following steps: maintaining a positioning data frame sequence in real time at a cloud; when it is detected that the positioning data frames are abnormal, detection is started from the first incoming frame of the positioning data frame sequence, and the first frame judged to be good is determined to serve as an initial positioning frame; loading a pre-stored point cloud map according to the initial positioning frame, and performing initial positioning frame matching in the point cloud map according to a preset matching algorithm to obtain a matching position; and when the evaluation of the matched position is good, taking the matched position as the initial position of the solution of the next frame in the positioning data frame sequence, sequentially completing the solution of all the positioning data frames in the positioning data frame sequence, and completing the positioning recovery of the robot. According to the method, system resources of the robot are not occupied when robot positioning recovery is completed.

Description

Technical Field

[0001] The present application relates to the technical field of robot positioning recovery, and in particular to a robot positioning recovery method, device, computer equipment and storage medium. Background Art

[0002] For the operation of the robot, the stable operation of the robot positioning module is crucial. The robot positioning module is the basis for the normal operation of the robot planning module and the decision-making module. If the robot positioning module crashes, most of the functions of the robot will not be able to operate normally. Therefore, it is very important to maintain the robustness and continuous effectiveness of the robot positioning module. Due to the limitations of cost, operating environment and other factors, the main control resources of the robot are usually allocated to the positioning module, planning module, decision module, perception module and other modules. Under normal working conditions, the resource occupation of various modules generally reaches 60%-70% of the overall resources, but under complex working conditions, it will reach more than 90% or even 100% of the overall resources, so that some modules will not be allocated the resources required for normal operation, resulting in module operation errors. The allocation of system resources cannot be easily intervened, so the positioning module will lose positioning due to resource problems, and it will be unable to automatically restore positioning and continue the execution of robot tasks. Summary of the invention

[0003] Based on this, it is necessary to provide a robot positioning recovery method, device, computer equipment and storage medium that can solve the resource occupation problem during robot positioning recovery in response to the above technical problems.

[0004] A robot positioning recovery method, the method comprising:

[0005] Maintaining a positioning data frame sequence in real time in the cloud; storing the latest positioning data frame of a preset frame in the positioning data frame sequence; and arranging the positioning data frame sequence according to a first-in-first-out rule;

[0006] When an abnormal positioning data frame is detected, detection is started from the first input frame of the positioning data frame sequence, and the first frame judged to be good is determined as the starting positioning frame;

[0007] According to the starting positioning frame, a pre-stored point cloud map is loaded, and the starting positioning frame is matched in the point cloud map according to a pre-set matching algorithm to obtain a matching position;

[0008] When the evaluation of the matching position is good, the matching position is used as the initial position for solving the next frame in the positioning data frame sequence, and the solving of all positioning data frames in the positioning data frame sequence is completed in sequence to complete the robot positioning recovery.

[0009] In one of the embodiments, it also includes: receiving the robot's positioning information in real time in the cloud; the positioning information includes: sensor data, positioning results and robot positioning evaluation; the robot positioning evaluation is obtained by scoring the positioning quality, when the positioning score is lower than a threshold, the robot positioning evaluation is abnormal, when the positioning score is not lower than the threshold, the robot positioning evaluation is good.

[0010] In one of the embodiments, the sensor data includes: radar data, camera data or feature point data.

[0011] In one of the embodiments, the method further includes: when the number of positioning data frames in the positioning data frame sequence is less than a preset value, storing the latest positioning data frame into the positioning data frame sequence according to a first-in-first-out rule;

[0012] When the number of positioning data frames in the positioning data frame sequence is equal to a preset value, the latest positioning data frame is stored at the end of the positioning data frame sequence according to a first-in-first-out rule, and the first stored positioning data frame sequence is deleted.

[0013] In one of the embodiments, it further includes: detecting in real time whether there is an abnormal positioning data frame in the positioning data frame sequence; when no abnormal positioning data frame is detected, there is no need to perform positioning recovery.

[0014] In one of the embodiments, the method further includes: when the evaluation of the matching position is abnormal, the positioning recovery fails.

[0015] In one of the embodiments, the matching algorithm includes: an NDT matching algorithm, an ICP matching algorithm or a feature point matching algorithm.

[0016] A robot positioning recovery device, the device comprising:

[0017] A cloud data maintenance module is used to maintain a positioning data frame sequence in real time in the cloud; the positioning data frame sequence stores the latest positioning data frame of a preset frame; the positioning data frame sequence is arranged according to a first-in-first-out rule;

[0018] An abnormality detection module is used to detect the first frame of the positioning data frame sequence when an abnormality is detected in the positioning data frame, and determine the first frame judged to be good as the starting positioning frame;

[0019] A matching module, used to load a pre-stored point cloud map according to the starting positioning frame, and perform matching of the starting positioning frame in the point cloud map according to a preset matching algorithm to obtain a matching position;

[0020] The recovery module is used to use the matching position as the initial position for solving the next frame in the positioning data frame sequence when the matching position is evaluated as good, and to complete the solution of all positioning data frames in the positioning data frame sequence in sequence to complete the robot positioning recovery.

[0021] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0022] Maintaining a positioning data frame sequence in real time in the cloud; storing the latest positioning data frame of a preset frame in the positioning data frame sequence; and arranging the positioning data frame sequence according to a first-in-first-out rule;

[0023] When an abnormal positioning data frame is detected, detection is started from the first input frame of the positioning data frame sequence, and the first frame judged to be good is determined as the starting positioning frame;

[0024] According to the starting positioning frame, a pre-stored point cloud map is loaded, and the starting positioning frame is matched in the point cloud map according to a pre-set matching algorithm to obtain a matching position;

[0025] When the evaluation of the matching position is good, the matching position is used as the initial position for solving the next frame in the positioning data frame sequence, and the solving of all positioning data frames in the positioning data frame sequence is completed in sequence to complete the robot positioning recovery.

[0026] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0027] Maintaining a positioning data frame sequence in real time in the cloud; storing the latest positioning data frame of a preset frame in the positioning data frame sequence; and arranging the positioning data frame sequence according to a first-in-first-out rule;

[0028] When an abnormal positioning data frame is detected, detection is started from the first input frame of the positioning data frame sequence, and the first frame judged to be good is determined as the starting positioning frame;

[0029] According to the starting positioning frame, a pre-stored point cloud map is loaded, and the starting positioning frame is matched in the point cloud map according to a pre-set matching algorithm to obtain a matching position;

[0030] When the evaluation of the matching position is good, the matching position is used as the initial position for solving the next frame in the positioning data frame sequence, and the solving of all positioning data frames in the positioning data frame sequence is completed in sequence to complete the robot positioning recovery.

[0031] The above robot positioning recovery method, device, computer equipment and storage medium maintain the robot's positioning data frame in real time in the cloud in order to solve the problem of positioning loss caused by resource allocation of the robot vehicle controller under complex working conditions. And when an abnormality in the positioning data frame is detected, since multiple frames of positioning data frames are stored in the cloud in advance, the positioning position can be restored in the cloud, so that the robot side can perform positioning recovery without occupying additional controller resources, so as to continue to complete the execution of the robot task under complex working conditions, ensure the continuous effectiveness of the robot positioning, do not delay the execution of the robot task, and improve the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic diagram of a flow chart of a robot positioning recovery method in one embodiment;

[0033] Figure 2 is a structural block diagram of a robot positioning recovery device in one embodiment;

[0034] Figure 3 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0036] In one embodiment, Figure 1 As shown, a robot positioning recovery method is provided, comprising the following steps:

[0037] Step 102: Maintain the positioning data frame sequence in real time in the cloud.

[0038] The latest positioning data frame of the preset frame is stored in the positioning data frame sequence. The number of positioning data frames stored can be set according to actual conditions. For example, in general industrial scenarios, the number of positioning data frames is set to 100.

[0039] The positioning data frame sequence is arranged according to the first-in-first-out rule. First-in-first-out refers to the first stored positioning data frame. When the storage quantity is full, the first stored positioning data frame will be deleted first.

[0040] Step 104 : when it is detected that the positioning data frame is abnormal, detection is started from the first input frame of the positioning data frame sequence, and the first frame judged to be good is determined as the starting positioning frame.

[0041] Step 106, according to the starting positioning frame, load the pre-stored point cloud map, perform starting positioning frame matching in the point cloud map according to a pre-set matching algorithm, and obtain a matching position.

[0042] Step 108, when the evaluation of the matching position is good, the matching position is used as the initial position for solving the next frame in the positioning data frame sequence, and the solving of the positioning data frames in the positioning data frame sequence is completed in sequence to complete the robot positioning recovery.

[0043] It is worth noting that after all positioning data frames are solved, if the positioning evaluation is good, the positioning results with good evaluation will be sent down, and the robot positioning recovery is completed.

[0044] In the above robot positioning recovery method, in order to solve the problem of positioning loss caused by resource allocation of the robot vehicle controller under complex working conditions, the robot's positioning data frame is maintained in real time in the cloud. And when an abnormality in the positioning data frame is detected, since multiple frames of positioning data frames are stored in the cloud in advance, the positioning position can be restored in the cloud, so that the robot side can perform positioning recovery without occupying additional controller resources, so as to continue to complete the execution of the robot task under complex working conditions, ensuring the continuous effectiveness of the robot positioning, not delaying the execution of the robot task, and improving the user experience.

[0045] In one of the embodiments, the positioning information of the robot is received in real time in the cloud, and the positioning information is saved as a positioning data frame sequence; the positioning information includes: sensor data, positioning results and robot positioning evaluation; the robot positioning evaluation is obtained by scoring the positioning quality, when the positioning score is lower than a threshold, the robot positioning evaluation is abnormal, when the positioning score is not lower than the threshold, the robot positioning evaluation is good.

[0046] Specifically, when performing the positioning score quality scoring, the fitness score calculation method in the NDT algorithm can be used. The evaluation parameter can be obtained after matching using the NDT algorithm, and the positioning score quality used for subsequent judgment is obtained after the fitness score is normalized. In this embodiment, the quality score is used as an evaluation method to determine whether the current robot needs to perform positioning recovery. Since the cloud stores real-time positioning data, it can be discovered at the first time whether the robot needs to perform positioning recovery, without the robot requesting positioning recovery from the cloud, which greatly improves the response speed of positioning recovery.

[0047] In one embodiment, the sensor data includes: radar data, camera data or feature point data. Due to different types of sensors, the sensor data in the positioning data frame can be determined according to the selection of the sensor. For example, if radar positioning is adopted, radar data is stored.

[0048] In one of the embodiments, when the number of positioning data frames in the positioning data frame sequence is less than a preset value, the latest positioning data frame is stored in the positioning data frame sequence according to the first-in-first-out rule; when the number of positioning data frames in the positioning data frame sequence is equal to the preset value, the latest positioning data frame is stored at the end of the positioning data frame sequence according to the first-in-first-out rule, and the first stored positioning data frame sequence is deleted. In real-time industrial scenarios, different robots require positioning data frames of different lengths for recovery. Therefore, the number of positioning frame data can be designed according to the actual situation of the robot, while maintaining a certain data margin to prevent the problem of being unable to recover when there are too many abnormal data, and ensure the robustness of positioning recovery.

[0049] In one embodiment, whether there are abnormal positioning data frames in the positioning data frame sequence is detected in real time; when no abnormal positioning data frame is detected, there is no need to perform positioning recovery. Since the positioning data frame detection is performed in the cloud, there is no need to set up logic on the robot side to detect the positioning status in real time, which saves the robot's computing resources to a certain extent.

[0050] In one of the embodiments, when the evaluation of the matching position is abnormal, the positioning recovery fails.

[0051] In one embodiment, the matching algorithm includes: an NDT matching algorithm, an ICP matching algorithm, or a feature point matching algorithm.

[0052] The technical solution of the present invention is described below with specific implementation:

[0053] The present invention is divided into two parts, including a cloud resource maintenance process and a cloud positioning backtracking process.

[0054] The cloud resource maintenance process is as follows:

[0055] 1. The robot sends radar data, odometer data, positioning posture, positioning evaluation and other information to the cloud server platform in data frames;

[0056] 2. The cloud server platform receives the positioning data frames sent by the robot in real time;

[0057] 3. When the robot positioning queue data is greater than 100 frames and the evaluation of the positioning data in the data queue is good, the latest received positioning data will be pushed to the end of the data queue, and the old data at the head of the data queue will be deleted to maintain the positioning data of 100 frames in the data queue.

[0058] 4. When the robot positioning queue data is less than 100 frames or there is a difference in the evaluation of the positioning data in the queue, only the latest received positioning data is pushed to the end of the data queue so that there is enough data for backtracking.

[0059] The cloud positioning backtracking process is as follows:

[0060] 1. The cloud server platform obtains the robot positioning queue data and determines whether there is a poor positioning evaluation in the data queue. If not, the platform will not backtrack. If so, the next backtracking operation will be performed;

[0061] 2. Perform positioning backtracking. Start from the front end of the queue and determine whether the positioning data frame is good. Get the first positioning data frame that is good. Load the point cloud map according to the positioning result of the positioning data frame.

[0062] 3. After the point cloud map is loaded, take this frame as the initial frame, take the positioning result of the initial frame as the initial position pose1, and input the radar data, point cloud map, and initial position pose1 into the ndt matching algorithm to obtain the matching position pose1-1;

[0063] 4. After converting the radar data to the matching position pose1-1, compare the converted radar data with the point cloud map and perform score evaluation to obtain the new positioning score score1 of the frame;

[0064] 5. Determine whether the positioning score score1 is greater than the set threshold. If it is greater than the set threshold, it means that the score evaluation is good. If it is less than the set threshold, it means that the score evaluation is poor, then the positioning backtracking fails, and the positioning backtracking failure message is output. Please ask the operator to check whether the map is good and whether the sensor is normal;

[0065] 6. When the positioning evaluation is good, the positioning matching of the second frame data is performed. First, the initial position is calculated. The initial pose of the second frame is Pose2 = Pose1-1 + (LPPose2-LPPose1). After calculating the initial position of the second frame, the radar data, point cloud map, and initial position pose2 are input into the ndt algorithm to obtain the matching position Pose2-1.

[0066] 7. Repeat steps 4 to 6 in this way. If the positioning data frame is continuously inferred to the end of the data queue, it means that the positioning backtracking is normal. The cloud platform sends the positioning backtracking result, and the vehicle-side platform restores the vehicle-side positioning after receiving it.

[0067] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0068] In one embodiment, Figure 2 As shown, a robot positioning recovery device is provided, including: a cloud data maintenance module 202, an abnormality detection module 204, a matching module 206 and a recovery module 208, wherein:

[0069] The cloud data maintenance module 202 is used to maintain the positioning data frame sequence in real time in the cloud; the positioning data frame sequence stores the latest positioning data frame of the preset frame; the positioning data frame sequence is arranged according to the first-in-first-out rule;

[0070] The abnormality detection module 204 is used to detect the first input frame of the positioning data frame sequence when an abnormality is detected in the positioning data frame, and determine the first frame judged to be good as the starting positioning frame;

[0071] A matching module 206 is used to load a pre-stored point cloud map according to the starting positioning frame, and perform matching of the starting positioning frame in the point cloud map according to a pre-set matching algorithm to obtain a matching position;

[0072] The recovery module 208 is used to, when the evaluation of the matching position is good, use the matching position as the initial position for solving the next frame in the positioning data frame sequence, complete the solution of all positioning data frames in the positioning data frame sequence in sequence, and complete the robot positioning recovery.

[0073] In one of the embodiments, the cloud data maintenance module 202 is also used to receive the robot's positioning information in real time on the cloud, and save the positioning information as a positioning data frame sequence; the positioning information includes: sensor data, positioning results and robot positioning evaluation; the robot positioning evaluation is obtained by scoring the positioning quality, when the positioning score is lower than a threshold, the robot positioning evaluation is abnormal, when the positioning score is not lower than the threshold, the robot positioning evaluation is good.

[0074] In one of the embodiments, the sensor data includes: radar data, camera data or feature point data.

[0075] In one of the embodiments, the cloud data maintenance module 202 is also used to store the latest positioning data frame into the positioning data frame sequence according to a first-in-first-out rule when the number of positioning data frames in the positioning data frame sequence is less than a preset value; when the number of positioning data frames in the positioning data frame sequence is equal to a preset value, store the latest positioning data frame at the end of the positioning data frame sequence according to a first-in-first-out rule, and delete the first stored positioning data frame sequence.

[0076] In one embodiment, the abnormality detection module 204 is further used to detect in real time whether there is an abnormal positioning data frame in the positioning data frame sequence; when no abnormal positioning data frame is detected, there is no need to perform positioning recovery.

[0077] In one embodiment, the recovery module 208 is further configured to fail the positioning recovery when the evaluation of the matching position is abnormal.

[0078] In one of the embodiments, the matching algorithm includes: an NDT matching algorithm, an ICP matching algorithm or a feature point matching algorithm.

[0079] The specific definition of the robot positioning recovery device can be found in the definition of the robot positioning recovery method above, which will not be repeated here. Each module in the above-mentioned robot positioning recovery device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0080] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data of a data positioning frame sequence. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a robot positioning recovery method is implemented.

[0081] Those skilled in the art will understand that Figure 3The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0082] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method in the above embodiment when executing the computer program.

[0083] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method in the above embodiment are implemented.

[0084] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0085] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0086] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A robot positioning recovery method, characterized in that: The method comprises: Maintaining a positioning data frame sequence in real time in the cloud; storing the latest positioning data frame of a preset frame in the positioning data frame sequence; and arranging the positioning data frame sequence according to a first-in-first-out rule; When an abnormal positioning data frame is detected, detection is started from the first input frame of the positioning data frame sequence, and the first frame judged to be good is determined as the starting positioning frame; According to the starting positioning frame, a pre-stored point cloud map is loaded, and the starting positioning frame is matched in the point cloud map according to a pre-set matching algorithm to obtain a matching position; When the evaluation of the matching position is good, the matching position is used as the initial position for solving the next frame in the positioning data frame sequence, and the solving of all positioning data frames in the positioning data frame sequence is completed in sequence to complete the robot positioning recovery.

2. The method according to claim 1, characterized in that The real-time maintenance of the positioning data frame sequence in the cloud includes: The positioning information of the robot is received in real time in the cloud, and the positioning information is saved as a positioning data frame sequence; the positioning information includes: sensor data, positioning results and robot positioning evaluation; the robot positioning evaluation is obtained by scoring the positioning quality, when the positioning score is lower than a threshold, the robot positioning evaluation is abnormal, when the positioning score is not lower than the threshold, the robot positioning evaluation is good.

3. The method according to claim 2, characterized in that The sensor data includes: radar data, camera data or feature point data.

4. The method according to claim 2 or 3, characterized in that: The method further comprises: When the number of positioning data frames in the positioning data frame sequence is less than a preset value, storing the latest positioning data frame into the positioning data frame sequence according to a first-in-first-out rule; When the number of positioning data frames in the positioning data frame sequence is equal to a preset value, the latest positioning data frame is stored at the end of the positioning data frame sequence according to a first-in-first-out rule, and the first stored positioning data frame sequence is deleted.

5. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: Detecting in real time whether there is an abnormal positioning data frame in the positioning data frame sequence; When no abnormal positioning data frame is detected, there is no need to perform positioning recovery.

6. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: When the evaluation of the matching position is abnormal, the positioning recovery fails.

7. The method according to any one of claims 1 to 3, characterized in that: The matching algorithm includes: NDT matching algorithm, ICP matching algorithm or feature point matching algorithm.

8. A robot positioning recovery device, characterized in that: The device comprises: A cloud data maintenance module is used to maintain a positioning data frame sequence in real time in the cloud; the positioning data frame sequence stores the latest positioning data frame of a preset frame; the positioning data frame sequence is arranged according to a first-in-first-out rule; An abnormality detection module is used to detect the first input frame of the positioning data frame sequence when an abnormality is detected in the positioning data frame, and determine the first frame judged to be good as the starting positioning frame; A matching module, used to load a pre-stored point cloud map according to the starting positioning frame, and perform matching of the starting positioning frame in the point cloud map according to a preset matching algorithm to obtain a matching position; The recovery module is used to use the matching position as the initial position for solving the next frame in the positioning data frame sequence when the matching position is evaluated as good, and to complete the solution of all positioning data frames in the positioning data frame sequence in sequence to complete the robot positioning recovery.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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