CN107838922A - A kind of robot exempts from the method for repeating teaching - Google Patents
A kind of robot exempts from the method for repeating teaching Download PDFInfo
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- CN107838922A CN107838922A CN201711005740.4A CN201711005740A CN107838922A CN 107838922 A CN107838922 A CN 107838922A CN 201711005740 A CN201711005740 A CN 201711005740A CN 107838922 A CN107838922 A CN 107838922A
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- information
- robot
- opc
- teaching
- semantization
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/0081—Programme-controlled manipulators with master teach-in means
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
Abstract
The present invention relates to a kind of method that robot exempts to repeat teaching, carries out semantization modeling to environmental unit information, robot information and teaching information, and write in the node of OPC UA service end address spaces；OPC UA clients access the node of OPC UA service end address spaces, parse semantization modeling information and are converted into XML file and are sent to cloud server；Cloud server parses XML file, according to robot body model information storehouse, carries out robot behavior resolving and asks for robot planning instruction, form movement locus point configuration file；OPC UA clients receive movement locus point configuration file, are transferred to one or more corresponding robot controller through OPC UA communication stacks, robot performs operation according to the movement locus point of acquisition.The present invention is packaged using semantization to device model information and job description information, realizes the interconnection of equipment room, is rapidly completed configuration, equipment replacement and function renewal by OPC UA synchronizations, is greatly improved application efficiency.
Description
Technical field
The present invention relates to a kind of method that robot exempts to repeat teaching.The present invention, which is applied to industrial robot, to be needed to repeat to show
Application scenarios are taught, the more industrial robots that are particularly suitable for use in complete the intelligent plant field of same task.
Background technology
When replacing people's progress operation with robot, it is necessary to send instruction to robot in advance, regulation robot is carried out should
The action of completion and the particular content of operation.This process is known as the teaching to robot or the programming to robot.Want
Robot is allowed to realize desired action, it is necessary to assign robot various information, be the letter of robot motion order first
The coordination information of breath and external equipment；Next to that the additional condition information with machine man-hour；It is the position of robot again
And attitude information.The first two aspect is largely that the technological requirement of the work and correlation to be completed with robot is relevant,
The teaching of position and posture is typically the emphasis of robot teaching.
Robot teaching mode substantially has two kinds at present:Teaching machine teaching and off-line programing.Teaching machine teaching, it is logical to refer to us
Often described teach-by-doing teaching, the arm that robot is directly moved by people complete sequence of operations, and robot controller record is deposited
Each motor point information is stored up, robot afterwards can repeat the task automatically according to instruction.Off-line programing, be by software,
The three-dimensional virtual environment of whole operative scenario is rebuild in computer, then software can be according to the size, shape, material of part to be processed
Material, while coordinate the certain operations of software operator, the movement locus of robot, i.e. control instruction are automatically generated, then soft
Emulation and adjustment track, ultimately produce robot program and are transferred to robot in part.Off-line programing then makes full use of computer graphic
The achievement in research of shape, robot and its environment thing model are established, then utilize computer visualization programming language Visual C+
+ (or Visual Basic) carries out operation segregation reasons, emulation, but it can not accomplish simply directly, to need on job description
User is wanted to possess the knowledge of certain robotic programming.Teaching machine teaching programming threshold it is low, it is simple and convenient, do not need environment mould
Type；When carrying out teaching to actual robot, the error that mechanical structure is brought can be corrected.Teaching machine teaching is simple direct with it
The advantages of be widely used in robot control field.
Traditional robot demonstrator mode, when robot location changes, basis coordinates system, user coordinate system
All changed, and the information after change can not be known in the good robot of teaching, teaching before all cancel, it is necessary to
Again teaching is carried out to robot.It is substantial amounts of which results in needing and the method and process of teaching do not change
Staff come the work that is repeated, meanwhile, the teaching machine of each robot is multifarious, and operation is also different, and programming refers to
Order is also different.To stop robot work during teaching, this can bring very big workload.
Therefore, for problem above, the cumbersome repetition teaching problem of traditional robot is broken through, research is based on OPC UA semantizations
Teaching method, realize data-reusing, improve operating efficiency.
The content of the invention
The problem of for existing teaching machine teaching, the invention provides a kind of method that robot exempts to repeat teaching, method
Core concept be relevant rudimentary configuration information to robot environment's facility information, robot body, the motion ginseng of robot
Data message caused by number and the direct teaching of teaching machine carries out semantic modeling respectively, and being uploaded to high in the clouds by OPC UA services takes
Business device；High in the clouds carries out robot behavior resolving based on dimension information storehouse, program results is passed into robot by semantic analysis
Controller completes robotic programming；If desired other robot completes same work, directly by OPC UA from cloud service
Device is downloaded to local, is automatically performed data configuration, omits the teaching process of cumbersome repetition.
The technical solution adopted for the present invention to solve the technical problems is：A kind of robot exempts from the method for repeating teaching, bag
Include following steps：
Step 1：Semantization modeling is carried out to environmental unit information, robot information and teaching information, and writes OPC UA
In the node of service end address space；
Step 2：OPC UA clients access the node of OPC UA service end address spaces, and obtain semantization modeling letter
Breath；Parse semantization modeling information and be converted into XML file and be sent to cloud server；
Step 3：Cloud server parsing XML file obtains environmental unit information, robot information and teaching information, according to
Robot body model information storehouse, carry out robot behavior resolving and ask for robot planning instruction, form the configuration of movement locus point
File；
Step 4：OPC UA clients receive the movement locus point configuration file of cloud server transmission, are communicated through OPC UA
Stack is transferred to one or more corresponding robot controller, and robot performs operation according to the movement locus point of acquisition；
Step 5：End node is serviced by OPC UA client query OPC UA, if nodal information has a change, return to step S2,
Otherwise local task, repeat step 5 are continued executing with.
Nodal information has change to be obtained by following steps：To in environmental unit information, robot information and teaching information
One or more are modified, and then carry out semantization modeling to environmental unit information, robot information and teaching information, and write
In the node for entering OPC UA service end address spaces.
It is described that semantization modeling is carried out to environmental unit information, robot information and teaching information, and write OPC UA clothes
It is engaged in comprising the following steps in the node of end address space：
By Information Level based on environmental unit information, robot information and teaching information architecture, OPC UA service ends are write
In node；
It is semantic information layer by the environmental unit information, robot information and teaching information architecture of semantic description, writes institute
In the child node for belonging to OPC UA service end nodes；
Back ground Information layer and semantic information layer are combined, semantic model layer is configured to, writes next sub- section of the child node
Point in.
Communicated between the OPC UA service ends and OPC UA clients using OPC UA communications protocol, OPC UA visitors
Communicated between family end and high in the clouds using http protocol.
The robot information includes the model information of robot body, the kinematic parameter of robot.
The environmental unit information includes the model information for workpiece, fixture used in robot application.
The teaching information is the psychomotor task description information that robot records during artificial teaching.
The invention has the advantages that and advantage：
1. using supporting the robot controller of cloud service platform to carry out application and development, suitable for robot application environment
Characteristic complicated and changeable, the problem of robot repeats teaching is avoided, saves substantial amounts of manpower and materials.
2. use OPC UA communication interfaces, the facility information of application environment can be linked into automatic identification, robot can be with
According to job description file, Mobile state adjustment is entered to robot application, improves flexibility and the adaptability of robot application.
3. being packaged using semantization to device model information and job description information, realize that the intercommunication of equipment room is mutual
Connection, configuration, equipment replacement and function renewal are rapidly completed by OPC UA synchronizations, greatly improves application efficiency.
Brief description of the drawings
Fig. 1 is the composition frame chart of the embodiment of the present invention；
Fig. 2 is the workflow diagram of the embodiment of the present invention.
Embodiment
With reference to embodiment, the present invention is described in further detail.
Multirobot operative scenario as shown in Figure 1, to robot A workpiece, fixture, robot body relevant information,
Kinematic parameter, teaching information etc. carry out semantization modeling, and the data of semantization are write to OPC UA server end address space
Node in.OPC UA clients access server, according to semantic model, parse all information, and by information in xml form,
Cloud server is transmitted to by http protocol.Cloud server parses XML file information, based on robot body model information
Storehouse, robot behavior resolving is carried out, and module is resolved by robot behavior and asks for robot planning instruction, form controller
Configuration file.When other robots such as robot B needs to carry out the operation same with robot A, or environmental unit generation
During change, teaching is repeated without artificial, by OPC UA synchronized updates, sends and asks to cloud server, passes through OPC UA visitors
Family end, other robot controller is passed to, complete to automatically configure, automatic teaching can be realized.
Described semantic modeling is the modelling of semantic modeling, and semanteme is loaded into data model, including basic mould
Type layer, semantic information layer, semantic model layer.Basic model layer represents the basic component set of equipment, and semantic information layer is used
The basic component attribute of semantic description, semantic model layer combine the data of lower two layers, and composition one is with semantic number
According to model.
As shown in Fig. 2 its implementation procedure workflow：
Step S1：To the environmental unit such as robot workpiece, fixture information, the relevant information of robot body, robot
Kinematic parameter and teaching information carry out semantization modeling, and semantization information is write in the node of OPC UA address spaces.Example
Such as：The object A that presss from both sides is needed to illustrate in robot, by its essential information such as size, shape, opposed robots' terminal position structure
Back ground Information layer is built, is write in OPC UA nodes；The information of semantic description such as bigsmall, shape, position are built into language
Adopted Information Level, write in OPC UA child nodes；Back ground Information layer and semantic information layer are combined, build semantic model layer, it is such as bright
True corresponding relation, bigsmall represents size attribute, shape represents shape attribute, position represents positional information, semantic mould
In the type layer write-in next child nodes of OPC UA.
Step S2：Motion control main program is performed, while triggers and performs OPC UA communication threads.
Step S3：OPC UA clients identify server device, and reference address space by the stack addressing service end that communicates
Node obtain semantization modeling information；Parsing obtains environmental unit information, the relevant information of robot body, the fortune of robot
Dynamic parameter and teaching information, and be converted into XML file form and be sent to cloud server.
Step S4：Cloud server parses XML file, obtains robot environment's facility information, the locally associated letter of robot
Breath, robot motion's parameter and teaching machine information.Such as needing the object A that presss from both sides to illustrate in robot, obtain size,
Shape, opposed robots' positional information.Based on robot body model information storehouse, and module is resolved by robot behavior and asked for
Robot planning instructs, and forms movement locus point configuration file.
Step S5：OPC UA clients receive the movement locus point configuration file of cloud server transmission, lead to through OPC UA
Believe stack, be transferred to one or more corresponding robot controller, controller parsing configuration file, installation movement locus point fortune
It is dynamic, it have updated robot manipulation.
Step S6：Service end node is accessed by OPC UA clients, poll checks nodal information, if there is nodal information change
Change, perform step S3, if not local task is then continued executing with, repeat step S6 judgement.
Robot controller is the universal computer platform based on X86-based, runs QNX real time operating systems；
Communication protocol, uses OPC UA communications protocol between OPC UA servers and client, OPC UA clients with
Using http protocol between cloud platform；
Environmental unit passes through including that may be used in robot application for equipment such as workpiece, fixture, robot bodies
UA interfaces can be by device model information transmission to robot controller；
Teaching information is the teaching message file that robot records during artificial teaching, is a series of actions task
File is described, and robot controller is passed to by UA interfaces；
Robot behavior settlement module, it is to combine the positive inverse arithmetic of robot, application task, the physics chi of equipment in environment
Very little information, obtained robot control instruction, it can be used for instructing robot to run.
3 application scenarios cases that the present invention uses.
1. the Duo Tai robots of model of the same race need to complete same action.Such as use robot screwing bottle cap, it is only necessary to
Artificial teaching is carried out to one of robot, the action message that the body configuration parameter of robot and teaching are obtained encapsulates
Cloud server is uploaded into XML.Other robot is downloaded from cloud server, is automatically configured, you can is completed without teaching
Identical acts.
2. when known to the pose and user coordinates of robot, but equipment to be operated has carried out known direction and distance
It is mobile when.Such as the teaching of screwing bottle cap robot is completed, and can turn on the bottle cap put on desk.But now desk is united
One has moved forward 5cm, and all robots, only need to be moving direction and distance in semantization modeling without repeating teaching
Modify, then configuration file is resend to robot, re-start configuration, you can online updating acts, and saves big
Measure manpower and materials.
3. when the pose and unknown user coordinates of robot, but when all robots all carry out identical change.
Such as the desk of pendulum bottle moves a segment distance to some direction, distance and direction are unknown.By artificial teaching wherein
One robot, records the configuration used and action message, is packaged into XML and is uploaded to cloud server, other robot is only
Needing to download and reconfiguring can complete to operate accordingly.
In summary, the present invention is with good expansibility and applicability, uses the robot for supporting cloud service platform
It controller, can significantly shorten the deployment cycle of robot application, reduce robot application implementation cost.Semantization simultaneously
Description, OPC UA communication services robot controller of the present invention can be allowed to be adapted to various industrial production scenes.
Claims (7)
1. a kind of robot exempts from the method for repeating teaching, it is characterised in that comprises the following steps：
Step 1：Semantization modeling is carried out to environmental unit information, robot information and teaching information, and writes OPC UA services
In the node for holding address space；
Step 2：OPC UA clients access the node of OPC UA service end address spaces, and obtain semantization modeling information；Solution
Analyse semantization modeling information and be converted into XML file and be sent to cloud server；
Step 3：Cloud server parsing XML file obtains environmental unit information, robot information and teaching information, according to machine
Human body's model information storehouse, carry out robot behavior resolving and ask for robot planning instruction, form movement locus point configuration file；
Step 4：OPC UA clients receive the movement locus point configuration file of cloud server transmission, are passed through OPCUA communication stacks
One or more corresponding robot controller is defeated by, robot performs operation according to the movement locus point of acquisition；
Step 5：End node is serviced by OPC UA client query OPC UA, if nodal information has a change, return to step S2, otherwise
Continue executing with local task, repeat step 5.
2. a kind of robot according to claim 1 exempts from the method for repeating teaching, it is characterised in that：Nodal information has accommodation
Following steps are crossed to obtain：One or more in environmental unit information, robot information and teaching information are modified, then
Semantization modeling is carried out to environmental unit information, robot information and teaching information, and writes OPC UA service end address spaces
Node in.
3. a kind of robot according to claim 1 or 2 exempts from the method for repeating teaching, it is characterised in that described that environment is set
Standby information, robot information and teaching information carry out semantization modeling, and write in the node of OPC UA service end address spaces
Comprise the following steps：
By Information Level based on environmental unit information, robot information and teaching information architecture, write-in OPC UA service end nodes
In；
It is semantic information layer by the environmental unit information, robot information and teaching information architecture of semantic description, OPC belonging to write-in
In the child node of UA service end nodes；
Back ground Information layer and semantic information layer are combined, semantic model layer is configured to, writes in next child node of the child node.
4. a kind of robot according to claim 1 exempts from the method for repeating teaching, it is characterised in that：The OPC UA services
End is communicated between OPC UA clients using OPC UA communications protocol, and HTTP is used between OPC UA clients and high in the clouds
Agreement is communicated.
5. a kind of robot according to claim 1 exempts from the method for repeating teaching, it is characterised in that the robot information
Model information including robot body, the kinematic parameter of robot.
6. a kind of robot according to claim 4 exempts from the method for repeating teaching, it is characterised in that：The environmental unit letter
Breath includes the model information for workpiece, fixture used in robot application.
7. a kind of robot according to claim 1 exempts from the method for repeating teaching, it is characterised in that：The teaching information is
The psychomotor task description information that robot records during artificial teaching.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711005740.4A CN107838922B (en) | 2017-10-25 | 2017-10-25 | Robot repetition-free teaching method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711005740.4A CN107838922B (en) | 2017-10-25 | 2017-10-25 | Robot repetition-free teaching method |
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| CN107838922A true CN107838922A (en) | 2018-03-27 |
| CN107838922B CN107838922B (en) | 2020-02-21 |
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| CN201711005740.4A Expired - Fee Related CN107838922B (en) | 2017-10-25 | 2017-10-25 | Robot repetition-free teaching method |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108828995A (en) * | 2018-05-31 | 2018-11-16 | 苏州浪潮智能软件有限公司 | Study of Intelligent Robot Control system and control method based on cloud platform |
| WO2020024183A1 (en) * | 2018-08-01 | 2020-02-06 | 西门子股份公司 | Interconnection device, communication method and system comprising robot |
| CN111142487A (en) * | 2019-12-30 | 2020-05-12 | 浪潮通用软件有限公司 | Equipment data acquisition system based on OPC UA unified architecture protocol |
| CN111203853A (en) * | 2018-11-21 | 2020-05-29 | 本田技研工业株式会社 | Robot device, robot system, robot control method, and storage medium |
| CN113615147A (en) * | 2019-04-10 | 2021-11-05 | Abb瑞士股份有限公司 | Selective address space aggregation |
| CN113836702A (en) * | 2021-09-03 | 2021-12-24 | 深圳市如本科技有限公司 | Robot teaching programming method and robot teaching programming device |
| CN114571471A (en) * | 2022-05-07 | 2022-06-03 | 广东隆崎机器人有限公司 | Method and system for centralized control of multiple SCARA robots |
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| CN108828995A (en) * | 2018-05-31 | 2018-11-16 | 苏州浪潮智能软件有限公司 | Study of Intelligent Robot Control system and control method based on cloud platform |
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| CN111142487A (en) * | 2019-12-30 | 2020-05-12 | 浪潮通用软件有限公司 | Equipment data acquisition system based on OPC UA unified architecture protocol |
| CN113836702A (en) * | 2021-09-03 | 2021-12-24 | 深圳市如本科技有限公司 | Robot teaching programming method and robot teaching programming device |
| CN114571471A (en) * | 2022-05-07 | 2022-06-03 | 广东隆崎机器人有限公司 | Method and system for centralized control of multiple SCARA robots |
| CN114571471B (en) * | 2022-05-07 | 2022-10-14 | 广东隆崎机器人有限公司 | Method and system for centralized control of multiple SCARA robots |
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