CN113189994A - Automatic guidance method, system, equipment and storage medium based on industrial internet - Google Patents
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Abstract
The application discloses an automatic guidance method, a system, equipment and a storage medium based on an industrial internet, wherein an identification travel track range of an automatic guidance instruction is obtained by identifying an initial travel track and an identification termination travel track of the automatic guidance instruction according to the automatic guidance instruction, the identification travel track range and an allowable error range value of a distinguishing identification correction model and an identification termination model divided by a sample track are compared, if the identification travel track range exceeds the allowable error range value, the model is identified as the termination model, and if not, the model is identified and corrected. According to the method and the device, whether the automatic guide command is the recognition termination model or the recognition correction model is obtained by comparing the recognition travel track range of the automatic guide command with the allowable error range value of the recognition correction model and the recognition termination model divided according to the sample track, so that the problem that the obtained travel track is inaccurate due to the error between the track of the travel track range and the sample track is solved.
Description
Technical Field
The present disclosure relates to the field of automated guidance and internet of things, and in particular, to an automated guidance method, system, device, and storage medium based on an industrial internet.
Background
The Automatic Guided Vehicle (AGV) track tracking method aims at the problem of track tracking of the AGV. Firstly, establishing a kinematic equation of the AGV, and taking the transverse deviation and the course deviation as input variables of a control system; and secondly, introducing a Hamilton optimal control function to obtain an AGV optimal deviation path and an optimal control equation based on an optimal deviation conversion strategy.
AGVs are acronyms of Automated Guided vehicles (Automated Guided vehicles), which refer to unmanned Automated vehicles having magnetic strips, rails, or laser Automated guidance devices, traveling along a planned path, powered by batteries, equipped with safety protection and various auxiliary mechanisms (e.g., transfer and assembly mechanisms). Usually, a plurality of AGVs, a control computer (console), a navigation device, a charging device and peripheral accessory devices form an AGV system, and the main working principle of the AGV system is that the AGVs can accurately walk according to a specified path to reach a task designated position under the monitoring and task scheduling of the control computer.
Therefore, there may be a case where the travel locus has an error or the travel distance is not accurate, so that it is difficult to accurately perform automatic guidance.
Disclosure of Invention
To solve the technical problems of the related art in the background art, the present disclosure provides an industrial internet-based automatic guidance method, system, device, and storage medium.
The application provides an automatic guidance method based on industrial Internet, which comprises the following steps:
acquiring an automatic guide instruction, and obtaining an identification travel track range of the automatic guide instruction according to an identification initial travel track and an identification termination travel track of the automatic guide instruction;
comparing the recognition travel track range of the automatic guide command with the allowable error range value of the distinguishing recognition correction model and the recognition termination model divided according to the sample track;
and if the identified driving track range exceeds the allowable error range value, the automatic guiding instruction is an identified termination model, otherwise, the automatic guiding instruction is an identified correction model.
Further, still include:
when an automatic guide instruction is obtained, obtaining a movement distance corresponding to the automatic guide instruction according to the identification initial driving distance and the identification ending driving distance of the automatic guide instruction;
when the automatic guide instruction is an identification correction model, comparing the movement distance corresponding to the automatic guide instruction with a first running length value for distinguishing the identification correction movement distance and the identification target movement distance divided according to the sample track;
and if the movement distance exceeds the first running length value, the automatic guide instruction is the movement distance of the recognition target, otherwise, the automatic guide instruction is the movement distance of the recognition correction.
Further, still include:
when an automatic guide instruction is obtained, obtaining the length difference between the automatic guide instruction and the last recognition and correction movement distance of the automatic guide instruction according to the recognition initial driving distance of the automatic guide instruction and the recognition ending driving distance of the last recognition and correction movement distance of the automatic guide instruction;
when the automatic guide instruction is a recognition correction movement distance, comparing a length difference between the automatic guide instruction and the last recognition correction movement distance of the automatic guide instruction with a second driving length value for distinguishing and recognizing a first movement distance and a second movement distance according to sample track division;
and if the length difference exceeds the second running length value, the automatic guiding instruction identifies a first movement distance, otherwise, the automatic guiding instruction identifies a second movement distance.
Further, still include:
acquiring an identification initial running track and an identification termination running track of the movement distance under each identification correction model, obtaining a running track range of the movement distance under each identification correction model according to the identification initial running track and the identification termination running track, and reading an average running track range of the movement distance under the identification correction model;
acquiring an identification initial running track and an identification termination running track of the movement distance under each identification termination model, obtaining a running track range of the movement distance under each identification termination model according to the identification initial running track and the identification termination running track, and reading an average running track range of the movement distance under the identification correction model;
and dividing and distinguishing allowable error range values of the recognition correction model and the recognition termination model according to the average travel track range of the movement distance under the recognition correction model and the average travel track range of the movement distance under the recognition correction model.
Further, still include:
acquiring an identification initial driving distance and an identification ending driving distance of each identification correction movement distance, obtaining the movement distance of each identification correction movement distance according to the identification initial driving distance and the identification ending driving distance, and reading the average movement distance of the identification correction movement distance;
acquiring an identification initial driving distance and an identification ending driving distance of each identification target movement distance, obtaining the movement distance of each identification target movement distance according to the identification initial driving distance and the identification ending driving distance, and reading the average movement distance of the identification target movement distance;
and distinguishing a first driving length value of the recognition correction movement distance and the recognition target movement distance according to the average movement distance of the recognition correction movement distance and the average movement distance of the recognition target movement distance.
Further, when the identifying the corrected moving distance is the identifying the second moving distance, the acquiring the identifying initial travel distance and the identifying end travel distance each time the corrected moving distance is identified includes:
acquiring a first recognition ending travel distance and a second recognition initial travel distance of each second movement distance, acquiring a length difference between two continuous correction movement distances in the second movement distance according to the first recognition ending travel distance and the second recognition initial travel distance, and reading an average length difference; and dividing and distinguishing a second running length value of the recognition correction model and a second running length value of the recognition termination model according to the average length difference.
The application provides an automatic guidance system based on industry internet, including terminal equipment and the data acquisition end of traveling, terminal equipment with the data acquisition end of traveling, terminal equipment includes:
the data identification module is used for acquiring an automatic guide instruction and obtaining an identification travel track range of the automatic guide instruction according to an identification initial travel track and an identification termination travel track of the automatic guide instruction;
the range comparison module is used for comparing the recognition travel track range of the automatic guide instruction with the allowable error range value of the distinguishing recognition correction model and the recognition termination model divided according to the sample track;
and the data judgment module is used for judging whether the range of the identified driving track exceeds the allowable error range value or not, wherein the automatic guiding instruction is an identification termination model, and otherwise, the automatic guiding instruction is an identification correction model.
The application provides a terminal device, its characterized in that includes:
a memory for storing a computer program;
a processor coupled to the memory for executing the computer program stored by the memory to implement the method of any of the above.
The present application provides a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and the computer program is executed to perform any one of the above methods.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects.
The method and the device for sample recognition target model self-adaptation provided by the embodiment of the invention obtain whether the automatic guidance command is a recognition ending model or a recognition correcting model by comparing the recognition travel track range of the automatic guidance command with the allowable error range value of the recognition correcting model and the recognition ending model divided according to the sample track, and solve the problem that the obtained travel track is inaccurate due to the error between the track of the travel track range and the sample track.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a schematic diagram of an architecture of an industrial internet-based automatic guidance system according to an embodiment of the present invention;
fig. 2 is a flowchart of an industrial internet-based automatic guidance method according to an embodiment of the present invention;
fig. 3 is a functional block diagram of an industrial internet-based homing device according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
To facilitate the description of the method, system, device and storage medium for industrial internet based automatic guidance, please refer to fig. 1, which provides a schematic diagram of a communication architecture of an industrial internet based automatic guidance system 100 according to an embodiment of the present invention. The industrial internet-based automatic guidance system 100 may include a terminal device 300 and a driving data collection terminal 200, wherein the terminal device 300 is in communication connection with the driving data collection terminal 200.
In a specific embodiment, the terminal device 300 may be a desktop computer, a tablet computer, a notebook computer, a mobile phone, or other terminal devices capable of implementing data processing and data communication, which is not limited herein.
On the basis of the above, please refer to fig. 2, which is a flowchart illustrating an industrial internet-based automatic guiding method according to an embodiment of the present invention, the industrial internet-based automatic guiding method may be applied to the terminal device 300 in fig. 1, and further, the industrial internet-based automatic guiding method may specifically include the contents described in the following steps S21 to S23.
And step S21, acquiring an automatic guide instruction, and obtaining the identification travel track range of the automatic guide instruction according to the identification initial travel track and the identification termination travel track of the automatic guide instruction.
For example, the initial travel track represents a start position of the automatic guidance, and the end travel track represents a stop position of the automatic guidance.
And step S22, comparing the recognition travel track range of the automatic guidance instruction with the allowable error range values of the discrimination recognition correction model and the recognition termination model divided according to the sample track.
For example, the travel track range is used for automatically guiding the travel path corresponding to the travel track.
And step S23, if the identified driving track range exceeds the allowable error range value, the automatic guiding command is an identified termination model, otherwise, the automatic guiding command is an identified correction model.
For example, the allowable error range value represents an allowable reasonable error range of the travel trajectory.
It can be understood that, according to the method and the apparatus for model adaptation of a sample recognition target provided in the embodiments of the present invention, whether the automatic guidance instruction is the recognition termination model or the recognition termination model is obtained by comparing the recognition travel track range of the automatic guidance instruction with the allowable error range value of the recognition termination model and the recognition modification model divided according to the sample track, so that a problem that an obtained travel track is inaccurate due to an error between a track of the travel track range and the sample track is solved.
In an alternative embodiment, the following may also be included.
And when the automatic guide instruction is acquired, obtaining the movement distance corresponding to the automatic guide instruction according to the identification initial driving distance and the identification ending driving distance of the automatic guide instruction. And when the automatic guide instruction is an identification correction model, comparing the movement distance corresponding to the automatic guide instruction with a first running length value for distinguishing the identification correction movement distance and the identification target movement distance divided according to the sample track. And if the movement distance exceeds the first running length value, the automatic guide instruction is the movement distance of the recognition target, otherwise, the automatic guide instruction is the movement distance of the recognition correction.
It can be understood that the moving distance of the target is identified by the moving distance corresponding to the automatic guide command, so that the automatic guide command is accurately determined.
In an alternative embodiment, the following may also be included.
When an automatic guide instruction is obtained, the length difference between the automatic guide instruction and the last recognition correction movement distance of the automatic guide instruction is obtained according to the recognition initial driving distance of the automatic guide instruction and the recognition ending driving distance of the last recognition correction movement distance of the automatic guide instruction. And when the automatic guide instruction is the identification correction movement distance, comparing the length difference between the automatic guide instruction and the last identification correction movement distance of the automatic guide instruction with a second driving length value for identifying the first movement distance and the second movement distance according to the distinguishing of the sample track division. And if the length difference exceeds the second running length value, the automatic guiding instruction identifies a first movement distance, otherwise, the automatic guiding instruction identifies a second movement distance.
It can be understood that the length difference is determined by correcting the movement distance according to the last recognition of the automatic guidance instruction, and in order to ensure the accuracy of the length difference, the accuracy of the second run length value is ensured by adopting a plurality of movement distances, so that the integrity and the practicability of the related data are ensured by the fact that the length difference exceeds the second run length value.
In an alternative embodiment, the following may also be included.
Acquiring an identification initial running track and an identification termination running track of the movement distance under each identification correction model, obtaining the running track range of the movement distance under each identification correction model according to the identification initial running track and the identification termination running track, and reading the average running track range of the movement distance under the identification correction model. And acquiring an identification initial running track and an identification termination running track of the movement distance under each identification termination model, obtaining the running track range of the movement distance under each identification termination model according to the identification initial running track and the identification termination running track, and reading the average running track range of the movement distance under the identification correction model. And dividing and distinguishing allowable error range values of the recognition correction model and the recognition termination model according to the average travel track range of the movement distance under the recognition correction model and the average travel track range of the movement distance under the recognition correction model.
It is understood that the allowable error range value can be accurately divided by identifying the average travel track range of the corrected model and identifying the average travel distance range of the stopped model.
In an alternative embodiment, the following may also be included.
Acquiring an identification initial driving distance and an identification ending driving distance of each identification correction movement distance, obtaining the movement distance of each identification correction movement distance according to the identification initial driving distance and the identification ending driving distance, and reading the average movement distance of the identification correction movement distance. Acquiring an identification initial driving distance and an identification ending driving distance of each identification target movement distance, obtaining the movement distance of each identification target movement distance according to the identification initial driving distance and the identification ending driving distance, and reading the average movement distance of the identification target movement distance. And distinguishing a first driving length value of the recognition correction movement distance and the recognition target movement distance according to the average movement distance of the recognition correction movement distance and the average movement distance of the recognition target movement distance.
It can be understood that the first run length value of the recognition correction moving distance and the recognition target moving distance can be accurately distinguished by recognizing the average running track of the correction moving distance and the average moving distance of the recognition target moving distance.
In an alternative embodiment, "when the identifying the corrected moving distance is the identifying the second moving distance, the obtaining identifies the initial travel distance and the identifying the ending travel distance each time the corrected moving distance is identified" may include the following.
Acquiring a first recognition ending travel distance and a second recognition initial travel distance of each second movement distance, acquiring a length difference between two continuous correction movement distances in the second movement distance according to the first recognition ending travel distance and the second recognition initial travel distance, and reading an average length difference; and dividing and distinguishing a second running length value of the recognition correction model and a second running length value of the recognition termination model according to the average length difference.
It can be understood that when the corrected movement distance is identified as the second movement distance, the problem of identification errors is effectively avoided, so that the identification initial travel distance and the identification ending travel distance of each identified corrected movement distance can be accurately acquired.
In an alternative embodiment, "comparing the recognized travel track range of the automated guidance instruction with the allowable error range value of the recognition correction model and the recognition termination model according to the distinction of the sample track division" may include the following.
The method comprises the steps of pre-storing average running time of a sample track, running time of a target to be detected in each time period and error of the running time of the target to be detected;
it is determined that a sample time data set exists within the preset database. Before each sample time data set is detected, the sample time data set is used as a current time data set to be detected, and the sum of the time consumption values of the detected time data set and the current time data set to be detected in the preset database is determined to be larger than the target driving time to be detected corresponding to the sample time weight value. And controlling the detection rate by carrying out errors on the current time data set, and finishing the detection of the current time data set at the time node corresponding to the sample time weight value. And after all the time data in the preset database are detected, adjusting the running time of the target to be detected in each time period to meet the error of the running time of the detected target.
It can be understood that whether the automated guidance driving route is consistent with the automated guidance instruction or not is determined by the driving time, a sample time data set can be obtained according to the distance and the driving speed, and the accuracy of automated guidance can be accurately and really achieved by comparing the actual consumed time and the corresponding content in the sample time data set.
Based on the same inventive concept, an automatic guidance system based on the industrial internet is further provided, the system comprises a driving data acquisition end and a terminal device, the driving data acquisition end is in communication connection with the terminal device, and the terminal device is specifically used for:
acquiring an automatic guide instruction, and obtaining an identification travel track range of the automatic guide instruction according to an identification initial travel track and an identification termination travel track of the automatic guide instruction;
comparing the recognition travel track range of the automatic guide command with the allowable error range value of the distinguishing recognition correction model and the recognition termination model divided according to the sample track;
and if the identified driving track range exceeds the allowable error range value, the automatic guiding instruction is an identified termination model, otherwise, the automatic guiding instruction is an identified correction model.
Based on the same inventive concept, please refer to fig. 3, which also provides a functional block diagram of the industrial internet based automatic guiding device 500, and the detailed description about the industrial internet based automatic guiding device 500 is as follows.
An industrial internet-based automatic guidance device 500 applied to a terminal device, the device 500 comprising:
the data identification module 510 is configured to obtain an automatic guidance instruction, and obtain an identified travel track range of the automatic guidance instruction according to an identified initial travel track and an identified final travel track of the automatic guidance instruction;
a range comparison module 520, configured to compare the identified travel track range of the automatic guidance instruction with an allowable error range value of a distinguishing identification correction model and an identification termination model divided according to a sample track;
and a data judgment module 530, configured to determine that the automatic guidance instruction is an identification termination model if the identified driving trajectory range exceeds the allowable error range value, and determine that the automatic guidance instruction is an identification correction model if the identified driving trajectory range exceeds the allowable error range value.
A terminal device, comprising: a memory for storing a computer program; a processor coupled to the memory for executing the computer program stored by the memory to implement the method shown in fig. 2.
A computer-readable storage medium, in which a computer program is stored which, when executed, implements the method shown in fig. 2.
In summary, based on the automatic guidance method, system, device and storage medium of the industrial internet, the method and apparatus for model adaptation for a sample recognition target according to the embodiments of the present invention obtain whether the automatic guidance instruction is the recognition termination model or the recognition modification model by comparing the recognition travel track range of the automatic guidance instruction with the allowable error range values of the recognition modification model and the recognition termination model divided according to the sample track, thereby solving the problem that the obtained travel track is inaccurate due to the error between the travel track range and the sample track.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is to be controlled solely by the appended claims.
Claims (9)
1. An automatic guidance method based on industrial internet is characterized by comprising the following steps:
acquiring an automatic guide instruction, and obtaining an identification travel track range of the automatic guide instruction according to an identification initial travel track and an identification termination travel track of the automatic guide instruction;
comparing the recognition travel track range of the automatic guide command with the allowable error range value of the distinguishing recognition correction model and the recognition termination model divided according to the sample track;
and if the identified driving track range exceeds the allowable error range value, the automatic guiding instruction is an identified termination model, otherwise, the automatic guiding instruction is an identified correction model.
2. The method of claim 1, further comprising:
when an automatic guide instruction is obtained, obtaining a movement distance corresponding to the automatic guide instruction according to the identification initial driving distance and the identification ending driving distance of the automatic guide instruction;
when the automatic guide instruction is an identification correction model, comparing the movement distance corresponding to the automatic guide instruction with a first running length value for distinguishing the identification correction movement distance and the identification target movement distance divided according to the sample track;
and if the movement distance exceeds the first running length value, the automatic guide instruction is the movement distance of the recognition target, otherwise, the automatic guide instruction is the movement distance of the recognition correction.
3. The method of claim 2, further comprising:
when an automatic guide instruction is obtained, obtaining the length difference between the automatic guide instruction and the last recognition and correction movement distance of the automatic guide instruction according to the recognition initial driving distance of the automatic guide instruction and the recognition ending driving distance of the last recognition and correction movement distance of the automatic guide instruction;
when the automatic guide instruction is a recognition correction movement distance, comparing a length difference between the automatic guide instruction and the last recognition correction movement distance of the automatic guide instruction with a second driving length value for distinguishing and recognizing a first movement distance and a second movement distance according to sample track division;
and if the length difference exceeds the second running length value, the automatic guiding instruction identifies a first movement distance, otherwise, the automatic guiding instruction identifies a second movement distance.
4. The method according to any one of claims 1-3, further comprising:
acquiring an identification initial running track and an identification termination running track of the movement distance under each identification correction model, obtaining a running track range of the movement distance under each identification correction model according to the identification initial running track and the identification termination running track, and reading an average running track range of the movement distance under the identification correction model;
acquiring an identification initial running track and an identification termination running track of the movement distance under each identification termination model, obtaining the running track range of the movement distance under each identification termination model according to the identification initial running track and the identification termination running track, and reading the average running distance range of the movement distance under the identification correction model;
and dividing and distinguishing allowable error range values of the recognition correction model and the recognition termination model according to the average travel track range of the movement distance under the recognition correction model and the average travel distance range of the movement distance under the recognition correction model.
5. The method of claim 4, further comprising:
acquiring an identification initial driving distance and an identification ending driving distance of each identification correction movement distance, obtaining the movement distance of each identification correction movement distance according to the identification initial driving distance and the identification ending driving distance, and reading an average driving track of the identification correction movement distance;
acquiring an identification initial driving distance and an identification ending driving distance of each identification target movement distance, obtaining the movement distance of each identification target movement distance according to the identification initial driving distance and the identification ending driving distance, and reading the average movement distance of the identification target movement distance;
and distinguishing a first driving length value of the recognition correction movement distance and the recognition target movement distance according to the average movement distance of the recognition correction movement distance and the average movement distance of the recognition target movement distance.
6. The method of claim 5, wherein when the identifying the modified movement distance is identifying a second movement distance, the obtaining an identified initial travel distance and an identified ending travel distance each time the modified movement distance is identified comprises:
acquiring a first recognition ending travel distance and a second recognition initial travel distance of each second movement distance, acquiring a length difference between two continuous correction movement distances in the second movement distance according to the first recognition ending travel distance and the second recognition initial travel distance, and reading an average length difference; and dividing and distinguishing a second running length value of the recognition correction model and a second running length value of the recognition termination model according to the average length difference.
7. The utility model provides an automatic guidance system based on industry internet which characterized in that, includes terminal equipment and the data acquisition end that traveles, terminal equipment with the data acquisition end that traveles, terminal equipment includes:
the data identification module is used for acquiring an automatic guide instruction and obtaining an identification travel track range of the automatic guide instruction according to an identification initial travel track and an identification termination travel track of the automatic guide instruction;
the range comparison module is used for comparing the recognition travel track range of the automatic guide instruction with the allowable error range value of the distinguishing recognition correction model and the recognition termination model divided according to the sample track;
and the data judgment module is used for judging whether the range of the identified driving track exceeds the allowable error range value or not, wherein the automatic guiding instruction is an identification termination model, and otherwise, the automatic guiding instruction is an identification correction model.
8. A terminal device, comprising:
a memory for storing a computer program;
a processor coupled to the memory for executing the computer program stored by the memory to implement the method of any of claims 1-6.
9. A computer-readable storage medium, in which a computer program is stored which, when running, performs the method of any one of claims 1-6.
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| CN106020190A (en) * | 2016-05-26 | 2016-10-12 | 山东大学 | Track learning controller, control system and method with initial state error correction |
| CN108983762A (en) * | 2017-06-02 | 2018-12-11 | 北京京东尚科信息技术有限公司 | Control method, device and the automated guided vehicle of automated guided vehicle |
| CN112346446A (en) * | 2019-08-08 | 2021-02-09 | 阿里巴巴集团控股有限公司 | Code-shedding recovery method and device for automatic guided transport vehicle and electronic equipment |
| CN111474938A (en) * | 2020-04-30 | 2020-07-31 | 内蒙古工业大学 | Inertial navigation automatic guided vehicle and track determination method thereof |
| CN111538334A (en) * | 2020-05-13 | 2020-08-14 | 合肥卓科智能技术有限公司 | Path tracking system of AGV dolly |
| CN112148017A (en) * | 2020-09-30 | 2020-12-29 | 杭州海康机器人技术有限公司 | Error calibration method and device, electronic equipment and storage medium |
| CN112379351A (en) * | 2020-10-23 | 2021-02-19 | 劢微机器人科技(深圳)有限公司 | AGV trolley parameter calibration method, device, equipment and storage medium |
| CN112678726A (en) * | 2020-12-18 | 2021-04-20 | 江苏智库智能科技有限公司 | Forklift AGV kinematics model-based goods taking positioning method and system |
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Denomination of invention: Automatic guidance method, system, equipment and storage medium based on industrial Internet Granted publication date: 20230303 Pledgee: China Construction Bank Corporation Shanghai Changning Branch Pledgor: SHANGHAI DATACENTER SCIENCE Co.,Ltd. Registration number: Y2024980022877 |