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CN111381815B - Offline programming post code conversion method and dual-robot cooperative intelligent manufacturing system and method based on same - Google Patents

Offline programming post code conversion method and dual-robot cooperative intelligent manufacturing system and method based on same Download PDF

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CN111381815B
CN111381815B CN202010093954.7A CN202010093954A CN111381815B CN 111381815 B CN111381815 B CN 111381815B CN 202010093954 A CN202010093954 A CN 202010093954A CN 111381815 B CN111381815 B CN 111381815B
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吕红强
周小勇
韩九强
郑辑光
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Xian Jiaotong University
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Abstract

离线编程后置代码转换方法和基于该方法的双机器人协同智造系统、方法,在仿真系统中导入仿真机器人、加工工具及零件的实体模型,根据加工需求对系统进行合理布局和标定,生成加工轨迹;仿真检验轨迹点是否可达,对不可达、轴超限等异常轨迹点进行调整;利用后置代码转换算法,将调整好的轨迹点转换为相应型号的实体机器人的运行代码,两台实体机器人在满足相互通信的条件下,通过运行代码,既可完成单机加工、双机同步独立加工,也可进行双机协同加工。整个系统安全可靠,精度高,鲁棒性强,并且适应多种不同品牌型号的机器人与多种类型的加工需求,能够满足双机器人协同智造的应用。

Figure 202010093954

The off-line programming post-code conversion method and the dual-robot collaborative intelligent manufacturing system and method based on the method, import the solid model of the simulated robot, processing tools and parts into the simulation system, and arrange and calibrate the system reasonably according to the processing requirements, and generate processing. trajectory; simulation checks whether the trajectory points are reachable, and adjusts abnormal trajectory points such as unreachable and axis overruns; using the post-code conversion algorithm, the adjusted trajectory points are converted into the running code of the corresponding model of the entity robot. Under the condition of mutual communication, the physical robot can complete single-machine processing, dual-machine synchronous independent processing, and dual-machine collaborative processing by running the code. The whole system is safe and reliable, with high precision and strong robustness, and is suitable for various types of robots of different brands and various types of processing needs, and can meet the application of dual-robot collaborative intelligent manufacturing.

Figure 202010093954

Description

Offline programming post code conversion method and dual-robot cooperative intelligent manufacturing system and method based on same
Technical Field
The invention belongs to the technical field of intelligent manufacturing and robots, and particularly relates to an off-line programming post code conversion method, and a dual-robot cooperative intelligent manufacturing system and method based on the method.
Background
With the rapid development of the industry, the application of industrial robots is more popular, and traditionally, the motions of the robots are designed by repeatedly teaching, but the mode is low in efficiency, and for some complex tasks, the requirements are difficult to achieve through teaching. Meanwhile, a single robot often cannot complete complex work tasks due to some limitations of the robot. The duplex robot has the advantages of strong adaptability and good flexibility, and is an effective way for realizing intelligent manufacturing. However, the problems of collaborative path planning, system calibration, trajectory error compensation, collaborative control and the like of the duplex robot are key technical problems which are urgently needed to be solved in the application and popularization processes of the robot in the industrial environment. The existing off-line programming software is lack of double-robot simulation and cooperative control functions, so that the cooperative track planning and off-line programming of double robots cannot be carried out, and the efficient cooperative intelligent construction based on the off-line programming cannot be realized.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide an off-line programming post-code conversion method and a two-robot cooperative intelligent manufacturing system and method based on the method, which ensure the consistency of simulation and actual working environment through system calibration, introduce a neural network training error compensation model and improve the precision of a robot in actual application; the post code conversion is to convert track point information which passes the simulation link verification into a program which can run on an industrial robot controller, establish communication with the industrial robot, and control the robot to reappear actions finished in the simulation working environment in the actual working environment. In addition, in order to enhance flexibility, a post-code editing function is added. The robot collaborative intelligent system is a collaborative intelligent system based on an offline programming calibration key technology and a post code conversion method, can realize collaborative processing of double robots, can also switch a single-machine mode to use a single robot to perform offline programming, and has the advantages of good robustness, high precision and high efficiency under different processing tasks. The model system that can regard as intelligent automation system carries out deep research, has fully embodied industrial robot collaborative operation's notion and industrial robot and has replaced the notion of manual work, and scalability is strong, provides the basis for further research crowd industrial robot intelligent automation system.
In order to achieve the purpose, the invention adopts the technical scheme that:
an off-line programming post code conversion method is characterized in that according to the brand model of a robot actually used, the track of a simulation robot is subjected to corresponding Euler angle conversion and is converted into a corresponding instruction set; and then, post code editing is carried out, namely instruction editing, modification operation and file access are carried out on the post code, and communication is established with a plurality of entity robots so as to control the entity robots to finish processing, so that the cooperative intelligence under the simulation environment is reproduced in the actual working environment.
The post code conversion adopts a track posture information conversion method, firstly converts the track posture information of the simulation robot generated in the simulation into the definitions of three Euler angles alpha, beta and gamma, and then translates the three definitions into corresponding instructions according to the instruction format of the entity robot, and the specific operation comprises the following steps:
step 1: converting the attitude information of the track of the simulation robot into the attitude of a terminal local coordinate system which is adaptive to the entity robot according to the zero point definition of the entity robot;
step 2: converting the attitude of the terminal local coordinate system converted in the step 1 into three euler angle definitions of alpha, beta and gamma according to an euler angle definition mode of the physical robot;
and step 3: and (3) translating the track point information obtained in the step (2) into a corresponding instruction which can be recognized by the entity robot according to the model of the actually used industrial robot and the mode of the instruction. And selecting a joint value motion instruction mode, writing the values of all joint axes solved by the inverse kinematics corresponding to each track point into the entity robot operation instruction according to a corresponding format, and writing the position and posture information of the track points into the entity robot operation instruction according to a corresponding format by selecting a pose value motion instruction mode. Meanwhile, an instruction for controlling the IO port level output of the entity robot is added behind the track point which needs to control the opening and closing of the air pump of the entity industrial robot.
In the step 2, the changed track posture information is used as a rotation matrix between the local coordinate system of the tail end of the actual robot and the base coordinate system of the actual robot, an euler angle is calculated according to the rotation matrix and an euler angle definition mode of the actual robot, a ZYX euler angle definition mode is adopted, and the calculation formula is as follows:
Figure GDA0003288311860000031
in the formula: c is shorthand for cos, s is shorthand for sin;
known slave base coordinate system COTransformation into a local coordinate system CO'Of the rotation matrix
Figure GDA0003288311860000032
Obtaining three Euler angles corresponding to the terminal attitude matrix of the actual robot according to the conversion matrix;
Figure GDA0003288311860000033
Figure GDA0003288311860000034
Figure GDA0003288311860000035
wherein alpha, beta and gamma represent three Euler angles of the actual robot, r11~r33Torque matrix R from top spinCAnd (6) obtaining.
In the post code editing, a program editor is added to display post-converted codes and the functions of instruction editing, modification operation and file access are included, wherein in the instruction editing, the instruction in a menu bar is clicked, and parameter values are filled in a popped dialog box to finish the instruction editing; the modification operation comprises double-click modification, copying, pasting, upward shifting and downward shifting; the file access comprises the steps of saving an existing program into a file, reading the program in the file into a program editor for display, directly importing the program subjected to simulation verification into the program editor through the file access, and downloading the program into the entity robot controller to control the robot to move through establishing communication with the entity robot.
After the conversion of the post code is completed, before the converted instruction is downloaded to an entity robot controller, the error compensation of joint values is carried out, a joint value error compensation model is trained based on a BP neural network, the joint values are compensated, the pose error during movement is reduced, and the pose precision of the robot is further improved, and the method specifically comprises the following steps:
step 1: acquiring theoretical joint values and actual joint values corresponding to a plurality of groups of poses of the robot;
step 2: substituting a plurality of groups of data of theoretical joint values and actual joint values corresponding to a certain posture, which are obtained in the step 1, into a BP neural network for training, wherein the theoretical joint values are input data of the network, and the actual joint values are expected output data of the network;
and step 3: writing a trained neural network compensation model in an entity robot controller, substituting a theoretical joint value obtained by solving the inverse kinematics of the robot into the model, and controlling the robot to move by the output corrected joint value; if the industrial robot manufacturer does not open the compensation port of the controller model, a real-time error compensation method based on a neural network is used, or the correction is directly carried out through a trained error compensation model when a post code is converted to output a joint motion mode program.
In the post code communication, Socket is used for communication based on a TCP/IP protocol, the converted program is downloaded to an entity robot controller to control the robot to move, and for the double robots, two communication threads are arranged to respectively communicate with the two robots; the method is specifically implemented by translating a communication point obtained by generating a simulation track into a communication instruction, starting a brother thread when the current thread is in operation and meeting the communication instruction, stopping the current thread, and completing dual-machine cooperation through mutual communication between the two threads. The procedure for establishing the communication procedure is as follows:
(a) building a server-side program of Socket communication based on TCP:
creating a socket through a socket function; binding the socket just created with an IP address and a port number through a bind function; monitoring a connection request from a client side through a listen function; receiving a connection request from a client side through an accept function; the server communicates with the client by sending and receiving data through the send function and the recv function, and waits for the requests of other clients; closing the socket;
(b) building a client program of Socket communication based on TCP:
creating a socket through a socket function; connecting the socket with the IP and the port number of the server side through a connect function; the server side sends data and receives data to communicate through the send function and the recv function; closing the socket;
(c) and setting double-thread communication to enable the computer to respectively download programs to the controllers of the two entity robots, and finishing double-machine cooperation through communication between threads.
The invention also provides a double-robot collaborative intelligent system based on the off-line programming post-code conversion method, which is characterized by comprising an off-line programming software simulation area 1, a robot control area 2 and robot processing working areas 3, 4 and 5, wherein:
the off-line programming software simulation area 1 comprises a computer 7 and a display screen 6 and is responsible for finishing the layout, trajectory planning and simulation work of the collaborative intelligent system;
the robot control area comprises a computer 7, robot control cabinets 10 and 11 and communication routing modules 8 and 9, wherein the communication routing modules 8 and 9 undertake communication work between the computer 7 and the robot control cabinets 10 and 11;
the robot processing working area comprises a double-robot cooperative processing working area 3 and single-robot processing working areas 4 and 5; the tail ends of the two industrial robots are respectively provided with a clamping jaw 14 and a processing tool 15;
the computer 7 controls the two robots 12 and 13 simultaneously to complete double-robot cooperative machining or independent work of the two robots, restores an actual machining environment by calibrating 1:1 in the simulation environment, performs simulation verification on a track planning result under the condition of not using the actual robot, and adjusts an abnormal track point in advance.
The invention further provides a dual-robot-based robotIn the intelligent manufacturing method of the same intelligent manufacturing system, two robots 12 and 13 are respectively calibrated by using a system calibration method, a group of characteristic points are respectively selected from a simulation working environment and an actual working environment, each group of characteristic points is respectively provided with three and not collinear, two groups of characteristic points are in one-to-one correspondence, the specific correspondence is that the characteristic points in the simulation environment and the characteristic points in the actual environment are in the same corresponding positions, and the position and pose conversion matrixes from a base coordinate system to a workpiece coordinate system in the simulation working environment and the actual working environment are respectively calculated
Figure GDA0003288311860000051
And
Figure GDA0003288311860000052
according to
Figure GDA0003288311860000053
And
Figure GDA0003288311860000054
obtaining a pose transformation matrix from a workpiece coordinate system in a simulation working environment to a workpiece coordinate system in an actual working environment
Figure GDA0003288311860000055
According to
Figure GDA0003288311860000056
And moving the workpiece in the simulation working environment to an appointed pose, and ensuring the consistency of the relative positions of the robot and the workpiece in the simulation working environment and the actual working environment.
The method comprises the following steps of transmitting track information into an actual robot controller through an offline programming post-code conversion method, controlling two robots in an actual environment to complete two-robot cooperative intelligent manufacturing work, and specifically comprises the following steps:
step 1: starting the double-robot cooperative intelligent system;
step 2: the system calibration method is operated in the computer 7, the robot is led in, a machining tool is defined, a workpiece is led in, three important factors, namely the machining requirement of the workpiece 16, the motion range of the robot and the posture of the workpiece are comprehensively considered, and the corresponding layout is carried out on the machining system;
and step 3: calibrating each model by using a system calibration method, and storing the coordinate information and calibration data of the workpiece in the computer 7;
and 4, step 4: the respective motion tracks of the two robots 12 and 13 are planned, the sequence execution sequence and the communication points of each track of the two robots are determined according to the processing requirements of the two robots, and then simulation verification is carried out;
and 5: aiming at inaccessible points, shaft overrun points and jump points detected by simulation, the processing position is changed, the layout is adjusted or the track editing function is utilized to adjust;
step 6: correcting the track through a joint value error compensation model;
and 7: converting the track generated in the simulation environment into an executable code by an off-line programming post-code conversion method;
and 8: setting the two robots 12 and 13 to be in an online mode, starting the communication routing modules 8 and 9 to connect the two robots 12 and 13, and operating the executable codes generated in the step 7;
and step 9: and after the cooperative intelligent manufacturing work is finished, the robots 12 and 13 are restored to the zero state, and the dual-robot cooperative intelligent manufacturing system is closed.
Compared with the prior art, the invention has the beneficial effects that:
the two-robot cooperative intelligent system fully embodies the concept of industrial robot cooperative operation. Compared with the existing offline programming software technology, the invention provides the track planning and simulation and dual-robot cooperative control technology for dual-robot cooperative intelligence, and has high working efficiency and strong expandability. On the basis of the software technology and the hardware device, the mode of the intelligent operation of the group industrial robots can be further researched, and a powerful basis is provided for relevant research and practice of enterprises and colleges.
The off-line programming post code conversion method provided by the invention improves the working precision and programming efficiency of the robot. Compared with the existing offline programming software technology, the error compensation and double-robot cooperative control technology based on the neural network is added, so that the adaptability is high, and the transportability is strong.
Drawings
FIG. 1 is a flowchart of post-transcoding for a robot according to the present invention.
Fig. 2 is an architecture diagram of the dual-robot cooperative intelligence system of the present invention.
FIG. 3 is a flow chart of the implementation of the scaling algorithm in off-line programming according to the present invention.
FIG. 4 is a diagram illustrating a calibration algorithm in off-line programming according to the present invention.
FIG. 5 is a flow chart of the operation of the two-robot cooperative intelligent system of the present invention.
Detailed Description
The embodiments of the present invention will be described in detail below with reference to the drawings and examples.
Referring to fig. 1, the off-line programming post-code conversion is to perform corresponding euler angle transformation on the track of the simulation robot and convert the euler angle transformation into a corresponding instruction set according to the brand and model of the actually used robot so as to control the entity robot to complete the processing; and then, post code editing and communication are carried out, namely, instruction editing, modification operation and file access are carried out on the post code, and communication is established with a plurality of robots, so that the cooperative intelligence under the simulation environment is reproduced in the actual working environment.
As shown in fig. 1, in combination with an example of workpiece processing, the post-code conversion of the present invention adopts a track posture information conversion method, which firstly converts track posture information into three euler angles α, β, γ definitions, and then translates into corresponding commands according to an actual robot command format, and the specific steps are as follows:
step 1: according to the zero point definition of the actual robot, changing all the tracks according to the posture change relation of the local coordinate system at the tail end of the actual robot when the postures of the actual robot and the simulation robot are consistent, and converting track posture information into the posture of the local coordinate system at the tail end of the actual robot;
step 2: and converting the corresponding robot tail end local coordinate system posture into three Euler angles alpha, beta and gamma for definition according to the rotation matrix and an Euler angle definition mode of the actual robot by taking the changed track posture information as the rotation matrix between the actual robot tail end local coordinate system and the actual robot base coordinate system.
Taking the ZYX euler angle definition as an example, the calculation method is as follows:
Figure GDA0003288311860000071
in the formula: c is shorthand for cos, s is shorthand for sin;
known slave base coordinate system COTransformation into a local coordinate system CO'Of the rotation matrix
Figure GDA0003288311860000081
Obtaining three Euler angles corresponding to the attitude matrix of the tail end of the robot according to the conversion matrix;
Figure GDA0003288311860000082
Figure GDA0003288311860000083
Figure GDA0003288311860000084
wherein alpha, beta and gamma represent three Euler angles of the actual robot, r11~r33Torque matrix R from top spinCAnd (6) obtaining.
And step 3: and converting the track position information and the converted attitude information into a control instruction of the actual robot according to a specified format. Translating and filling information of the track points into corresponding instructions according to the model of the actually used industrial robot and the mode of the instructions, selecting a joint value motion instruction mode, writing each joint value solved by inverse kinematics corresponding to each track point into the instructions according to a corresponding format, selecting a pose value motion instruction mode, and writing the position and posture information of the track points into the instructions according to the corresponding format; meanwhile, an instruction for controlling the level output of the IO port is added to track points needing to control the opening and closing of the air pump of the industrial robot.
The post code editing is to add a program editor for displaying a program after post code conversion, and comprises the functions of instruction editing, modification operation, file access and the like, wherein the instruction editing completes the editing of an instruction by clicking the instruction in a menu bar and filling parameter values in a pop-up dialog box. The modification operation comprises double-click modification, copying, pasting, moving up, moving down and the like. The file access comprises the steps of saving the existing program into the file and reading the program in the file into the program editor for display, the program subjected to simulation verification can be conveniently and directly led into the program editor through the file access, the program is downloaded into the robot controller to control the robot to move through communication with the robot, the track generation and simulation are not needed to be carried out again, and the time is saved.
Further, a joint value error compensation model can be trained based on a BP neural network, namely, a robot inverse kinematics calibration method based on the neural network compensates joint values, so that the pose error during movement is reduced, the pose precision of the robot is further improved, and the specific flow is as follows:
(a) acquiring theoretical joint values and actual joint values corresponding to a plurality of groups of poses of the robot;
(b) substituting a plurality of groups of data of theoretical joint values and actual joint values corresponding to a certain posture, which are obtained in the step 1, into a BP neural network for training, wherein the theoretical joint values are input data of the network, and the actual joint values are expected output data of the network;
(c) writing a trained neural network compensation model in an entity robot controller, substituting a theoretical joint value obtained by solving the inverse kinematics of the robot into the model, and controlling the robot to move by the output corrected joint value; if the industrial robot manufacturer does not open the compensation port of the controller model, a real-time error compensation method based on a neural network can be used, or the correction can be directly carried out through a trained error compensation model when a post-code conversion outputs a joint motion mode program.
And 4, step 4: and establishing a communication connection with the industrial robot, wherein the communication mode is based on the wired local area network communication of a TCP/IP (transmission control protocol/Internet protocol), namely, Socket is used for carrying out communication based on a TCP/IP protocol, and a program is downloaded to a robot controller to control the robot to move. For the double robots, two communication threads are arranged to respectively communicate with the two robots; the method is specifically implemented by translating the communication point obtained by track generation into a communication instruction, starting a brother thread when the current thread is in operation and encountering the communication instruction, stopping the current thread, and completing dual-machine cooperation through mutual communication between the two threads.
The procedure for establishing the communication procedure is as follows:
(a) a server-side program of Socket communication based on TCP is built, and the flow is as follows:
creating a socket through a socket function; binding the socket just created with an IP address and a port number through a bind function; monitoring a connection request from a client side through a listen function; receiving a connection request from a client side through an accept function; the server communicates with the client by sending and receiving data through the send function and the recv function, and waits for the requests of other clients; the socket is closed.
(b) A client program of Socket communication based on TCP is established, and the flow is as follows:
creating a socket through a socket function; connecting the socket with the IP and the port number of the server side through a connect function; the server side sends data and receives data to communicate through the send function and the recv function; the socket is closed.
(c) And setting double-thread communication to enable the computer to respectively download programs to the two robot controllers, and completing double-machine cooperation through communication between threads.
As shown in fig. 2, the two-robot cooperative intelligent system based on the off-line programming post-code conversion method of the present invention includes an off-line programming software simulation area 1, a robot control area 2, and robot processing work areas 3, 4, and 5.
The off-line programming software simulation area 1 comprises a computer 7 and a display screen 6 and is responsible for finishing the layout, trajectory planning and simulation work of the collaborative intelligent system; the robot control area comprises a computer 7, robot control cabinets 10 and 11 and communication routing modules 8 and 9, wherein the communication routing modules 8 and 9 undertake communication work between the computer 7 and the robot control cabinets 10 and 11; the robot processing working area comprises a double-robot cooperative processing working area 3 and single-robot processing working areas 4 and 5; the tail ends of the two industrial robots are respectively provided with a clamping jaw 14 and a processing tool 15; the clamping jaws at the tail end of the slave robot are used for clamping workpieces to a preset processing position, and the master robot carries a tool to process.
On the basis of normal communication, the two robots can clamp the workpiece in one mode, the two robots perform cooperative processing in the mode of processing in one mode, and finally the two robots can complete a complete workpiece processing task together in the mode of mutual cooperation. Particularly, when the two robots do not need to cooperate with each other, the two robots can be switched to a single-machine mode or a double-machine simultaneous independent motion mode, and independent intelligent processing is carried out in an independent workpiece processing area.
The double-robot collaborative intelligent manufacturing system can restore the actual machining environment in a simulation environment by 1:1 through a calibration key technology, can use various different robots, tools and parts for simulation and planning in simulation, and meets various actual machining requirements; for some complex processing requirements, compared with the traditional teaching programming, the off-line programming can greatly improve the track planning efficiency and the programming process; meanwhile, the operation simulation verification of the track planning result can be realized under the condition that an actual robot is not used, some abnormal track points can be adjusted in advance, and the efficiency of overall collaborative intelligence creation is improved.
The system can use one computer 7 to control two robots 12 and 13 simultaneously to complete double-machine cooperative processing, and can also control the two robots to work independently without mutual interference; meanwhile, the robot can be switched to a single-machine mode, and a single robot is used for independently working, so that various industrial use requirements can be met.
According to the manufacturing method of the double-robot cooperative intelligent system based on the off-line programming post-code conversion method, the two robots (12 and 13) are calibrated by using a system calibration method respectively, and then trajectory planning and simulation are carried out.
The invention provides an off-line programming system calibration method, as shown in fig. 3, and in combination with an example of workpiece processing, the specific steps of a calibration algorithm flow are as follows:
step 1: selecting a group of three feature points which are not collinear on a workpiece in the actual working environment, and recording the coordinates of the three feature points, as shown in FIG. 4, wherein the feature points in the group are P respectively in the actual working environmentR1(xs1,ys1,zs1)、PR2(xs2,ys2,zs2)、PR3(xs3,ys3,zs3);
Step 2: selecting a group of three feature points which are not collinear in the simulation working environment and correspond to the actual working environment, and recording coordinates of the three feature points, as shown in FIG. 4, wherein the feature points in the simulation working environment are Ps1(xs1,ys1,zs1)、Ps2(xs2,ys2,zs2)、Ps3(xs3,ys3,zs3). The two groups of feature points are in one-to-one correspondence, the specific correspondence is shown in fig. 4, and the feature points in the simulation environment and the feature points in the actual environment are in the same corresponding positions;
and step 3: selecting a group of three feature points P which are not collinear on a workpiece in an actual working environmentR1(xs1,ys1,zs1)、PR2(xs2,ys2,zs2)、PR3(xs3,ys3,zs3) In the method, one point is selected as the origin of the workpiece coordinate system at will, and then the position and pose transformation matrix from the base coordinate system to the workpiece coordinate system in the actual working environment can be obtained
Figure GDA0003288311860000111
And 4, step 4: the position and pose transformation matrix from the base coordinate system to the workpiece coordinate in the simulation working environment can be obtained by the method of the step 3
Figure GDA0003288311860000112
And 5: according to
Figure GDA0003288311860000113
And
Figure GDA0003288311860000114
can obtain a pose transformation matrix from the coordinates of the workpiece in the simulation working environment to the coordinate system of the workpiece in the actual working environment
Figure GDA0003288311860000121
Step 6: according to
Figure GDA0003288311860000122
The workpiece in the simulation working environment can be moved to an appointed pose, and therefore consistency between the simulation working environment and the actual working environment is guaranteed.
As shown in fig. 5, the operation flow of the two-robot cooperative intelligent system is as follows:
(a) starting the double-robot cooperative intelligent system;
(b) running off-line programming software in the computer 7, importing the robot, defining a processing tool, importing a workpiece, comprehensively considering three important factors of the processing requirement of the workpiece 16, the motion range of the robot and the posture of the workpiece, reasonably distributing a processing system, and ensuring that the position of the workpiece in the processing process is always within the working range of the two robots 12 and 13;
(c) using the relevant models of the calibration key technology and calibrating each model, and storing the coordinate information and calibration data of the workpiece in the computer 7;
(d) planning respective motion tracks of the two robots 12 and 13 according to the processing requirements of the dual-robot cooperation, determining the sequence execution sequence and communication points of each section of track of the two robots, inserting the communication points into the tracks for cooperation, and then performing simulation verification;
(e) aiming at inaccessible points, shaft overrun points and jump points detected by simulation, the machining position is reasonably changed, and the layout or the track is adjusted through rotation; adjusting the area with large change of the pose of the adjacent track points in the partial processing area by using track editing functions such as track splitting, z-axis fixing and the like;
(f) after all the abnormal points are adjusted, performing simulation verification on the simulation project for multiple times, and if the simulation is not wrong, indicating that the track planning work is finished;
(g) correcting the track through a joint value error compensation model in offline programming software;
(h) running post code conversion in the off-line programming software, and converting the track generated in the simulation environment into an executable code;
(i) setting the two robots to be in an online mode, establishing TCP/IP communication, starting communication routing modules 8 and 9 to connect the two robots, operating the executable codes generated in the step 7, and controlling the two robots 12 and 13 to move;
(j) and after the cooperative intelligent work is finished, the robots 12 and 13 are restored to the zero state, and the system is closed.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that these embodiments are merely preferred embodiments of the invention, and that any modifications, equivalents, improvements and the like made within the spirit of the invention and the scope of the claims are included in the scope of the invention.
In summary, the invention is based on off-line programming, introduces the entity models of the robot, the processing tool and the part into the simulation system, and carries out reasonable layout and calibration on the system according to the processing requirement to generate the processing track; simulating to check whether the track point can be reached, and adjusting the abnormal track points such as unreachable track point, over-limit axle and the like; and converting the adjusted track points into the running codes of the entity robots of corresponding models by using a post code conversion algorithm, wherein the two entity robots can complete single-machine processing, double-machine synchronous independent processing and double-machine cooperative processing by running the codes under the condition of meeting the mutual communication. The whole system is safe and reliable, high in precision and strong in robustness, meets the processing requirements of various robots with different brands and models and various types, and can meet the application of double-robot cooperative intelligent construction.

Claims (4)

1. An off-line programming post code conversion method is characterized in that according to the brand model of the robot actually used, the track of the simulation robot is subjected to corresponding Euler angle conversion and is converted into a corresponding instruction set; then, post code editing is carried out, namely instruction editing, modification operation and file access are carried out on the post code, and communication is established with a plurality of entity robots so as to control the entity robots to complete processing, so that the cooperative intelligence under the simulation environment is reproduced in the actual working environment;
the post-code conversion adopts a track attitude information conversion method, firstly converts track attitude information of a simulation robot generated in simulation into three Euler angles alpha, beta and gamma for definition, and then translates the track attitude information into a corresponding instruction according to an instruction format of an entity robot, and the specific operation comprises the following steps:
step 11: converting the attitude information of the track of the simulation robot into the attitude of a terminal local coordinate system which is adaptive to the entity robot according to the zero point definition of the entity robot;
step 12: converting the attitude of the terminal local coordinate system converted in the step 11 into three euler angles alpha, beta and gamma for definition according to an euler angle definition mode of the physical robot;
step 13: translating the track point information obtained in the step (12) into a corresponding instruction which can be recognized by the entity robot according to the model of the actually used industrial robot and the mode of the instruction; if a joint value motion instruction mode is selected, writing the values of all joint axes solved by inverse kinematics corresponding to each track point into an entity robot operation instruction according to a corresponding format; if the pose value motion instruction mode is selected, writing the position and posture information of the track points into an entity robot operation instruction according to a corresponding format; meanwhile, adding a command for controlling the level output of an IO port of the entity robot behind a track point needing to control the opening and closing of the air pump of the entity industrial robot;
the method comprises the steps that a program editor is added to display post-converted codes and comprises the functions of instruction editing, modification operation and file access, wherein the instruction editing is realized by clicking an instruction in a menu bar and filling parameter values in a popped dialog box to finish the instruction editing; the modification operation comprises double-click modification, copying, pasting, upward shifting and downward shifting; the file access comprises the steps of storing an existing program into a file, reading the program in the file into a program editor for display, directly importing the program subjected to simulation verification into the program editor through the file access, establishing communication with the entity robot, and downloading the program into the entity robot controller to control the robot to move;
after the conversion of the post code is completed, before the converted instruction is downloaded to an entity robot controller, the error compensation of joint values is carried out, a joint value error compensation model is trained based on a BP neural network, the joint values are compensated, the pose error during movement is reduced, and the pose precision of the robot is further improved, and the method specifically comprises the following steps:
step 21: acquiring theoretical joint values and actual joint values corresponding to a plurality of groups of poses of the robot;
step 22: substituting the multiple groups of data of theoretical joint values and actual joint values corresponding to a certain posture, which are obtained in the step 21, into a BP neural network for training, wherein the theoretical joint values are input data of the network, and the actual joint values are expected output data of the network;
step 23: writing a trained neural network compensation model in an entity robot controller, substituting a theoretical joint value obtained by solving the inverse kinematics of the robot into the model, and controlling the robot to move by the output corrected joint value; if the industrial robot manufacturer does not open the compensation port of the controller model, a real-time error compensation method based on a neural network is used, or the correction is directly carried out through a trained error compensation model when a post code is converted to output a joint motion mode program.
2. The off-line programming post-code conversion method according to claim 1, wherein in the step 12, the changed trajectory posture information is used as a rotation matrix between a local coordinate system of the end of the actual robot and a base coordinate system of the actual robot, an euler angle is calculated according to the rotation matrix and an euler angle definition mode of the actual robot, a ZYX euler angle definition mode is adopted, and a calculation formula is as follows:
Figure FDA0003288311850000021
in the formula: c is shorthand for cos, s is shorthand for sin;
known slave base coordinate system COTransformation into a local coordinate system CO'Of the rotation matrix
Figure FDA0003288311850000022
Obtaining three Euler angles corresponding to the terminal attitude matrix of the actual robot according to the conversion matrix;
Figure FDA0003288311850000031
Figure FDA0003288311850000032
Figure FDA0003288311850000033
wherein alpha, beta and gamma represent three Euler angles of the actual robot, r11~r33By a rotation matrix RCAnd (6) obtaining.
3. The off-line programming postcode conversion method according to claim 1, wherein Socket is used for communication based on TCP/IP protocol, the converted program is downloaded to an entity robot controller to control the robot to move, and for the double robots, two communication threads are arranged to respectively communicate with the two robots; specifically, the communication point obtained by generating the simulation track is translated into a communication instruction, when the current thread is in operation, the brother thread is started first when the communication instruction is encountered, the current thread is stopped, the dual-machine cooperation is completed through the mutual communication between the two threads, and the flow of establishing the communication program is as follows:
(a) building a server-side program of Socket communication based on TCP:
creating a socket through a socket function; binding the socket just created with an IP address and a port number through a bind function; monitoring a connection request from a client side through a listen function; receiving a connection request from a client side through an accept function; the server communicates with the client by sending and receiving data through the send function and the recv function, and waits for the requests of other clients; closing the socket;
(b) building a client program of Socket communication based on TCP:
creating a socket through a socket function; connecting the socket with the IP and the port number of the server side through a connect function; the server side sends data and receives data to communicate through the send function and the recv function; closing the socket;
(c) and setting double-thread communication to enable the computer to respectively download programs to the controllers of the two entity robots, and finishing double-machine cooperation through communication between threads.
4. The two-robot cooperative intelligent system based on the off-line programming post-transcoding method as claimed in claim 1, comprising an off-line programming software simulation area (1), a robot control area (2) and a robot processing work area (3, 4, 5), wherein:
the off-line programming software simulation area (1) comprises a computer (7) and a display screen (6) and is responsible for finishing the layout, trajectory planning and simulation work of the collaborative intelligent manufacturing system;
the robot control area comprises a computer (7), robot control cabinets (10, 11) and communication routing modules (8, 9), wherein the communication routing modules (8, 9) undertake communication work between the computer (7) and the robot control cabinets (10, 11);
the robot processing working area comprises a double-robot cooperative processing working area (3) and single-robot processing working areas (4, 5); the tail ends of the two industrial robots are respectively provided with a clamping jaw (14) and a processing tool (15);
the computer (7) controls the two robots (12 and 13) simultaneously to complete double-machine cooperative machining or respective independent work, restores an actual machining environment by calibrating 1:1 in a simulation environment, performs simulation verification on a track planning result under the condition of not using the actual robots, and adjusts abnormal track points in advance;
the two robots (12, 13) are respectively calibrated by using a system calibration method, a group of feature points are respectively selected from a simulation working environment and an actual working environment, each group of feature points is respectively provided with three and not collinear feature points, two groups of feature points are in one-to-one correspondence, the specific correspondence is that the feature points in the simulation environment and the feature points in the actual environment are in the same corresponding positions, and pose transformation matrixes from a base coordinate system to a workpiece coordinate system in the simulation working environment and the actual working environment are respectively calculated
Figure FDA0003288311850000041
And
Figure FDA0003288311850000042
according to
Figure FDA0003288311850000043
And
Figure FDA0003288311850000044
obtaining a pose transformation matrix from a workpiece coordinate system in a simulation working environment to a workpiece coordinate system in an actual working environment
Figure FDA0003288311850000045
According to
Figure FDA0003288311850000046
Moving the workpiece in the simulation working environment to an appointed pose, and ensuring the consistency of the relative positions of the robot and the workpiece in the simulation working environment and the actual working environment;
the two robots (12, 13) respectively use the system calibration method to carry out system calibration, then carry out trajectory planning and simulation, transmit trajectory information into an actual robot controller through an off-line programming post-code conversion method, and control the two robots in an actual environment to complete double-robot cooperative intelligent work, specifically comprising the following steps:
step 1: starting the double-robot cooperative intelligent system;
step 2: the method comprises the steps of operating a system calibration method in a computer (7), importing a robot, defining a machining tool, importing a workpiece, and carrying out corresponding layout on a machining system by comprehensively considering three important factors, namely the machining requirement of the workpiece (16), the motion range of the robot and the attitude of the workpiece;
and step 3: calibrating each model by using a system calibration method, and storing coordinate information and calibration data of the workpiece in a computer (7);
and 4, step 4: respective motion tracks of the two robots (12 and 13) are planned, the execution sequence and the communication point of each track of the two robots are determined according to the processing requirement of the two robots in cooperation, and then simulation verification is carried out;
and 5: aiming at inaccessible points, shaft overrun points and jump points detected by simulation, the processing position is changed, the layout is adjusted or the track editing function is utilized to adjust;
step 6: correcting the track through a joint value error compensation model;
and 7: converting the track generated in the simulation environment into an executable code by an off-line programming post-code conversion method;
and 8: setting the two robots (12, 13) to be in an online mode, starting the communication routing modules (8, 9) to connect the two robots (12, 13), and operating the executable code generated in the step 7;
and step 9: and after the cooperative intelligent construction work is finished, the robots (12 and 13) are restored to the zero state, and the dual-robot cooperative intelligent construction system is closed.
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JP7490979B2 (en) * 2020-02-17 2024-05-28 オムロン株式会社 Processing device and processing method
CN111993419B (en) * 2020-08-10 2022-04-19 广州瑞松北斗汽车装备有限公司 PDPS-based robot offline manufacturing method and device and computer terminal equipment
CN114968217A (en) * 2021-02-25 2022-08-30 西门子股份公司 Programming method and device of numerical control machine tool system
CN113021348B (en) * 2021-03-23 2021-10-15 深圳群宾精密工业有限公司 Method applied to point position high-precision conversion among different robots
CN113001523A (en) * 2021-04-09 2021-06-22 山东大学 Four-foot double-arm robot and operation mode thereof
CN113110544A (en) * 2021-04-19 2021-07-13 乐聚(深圳)机器人技术有限公司 Robot control method, device, equipment and storage medium
CN114089644A (en) * 2021-11-12 2022-02-25 中冶赛迪技术研究中心有限公司 Method, system, device and medium for remote simulation calibration and online programming based on openvpn
CN114347038A (en) * 2022-02-17 2022-04-15 西安建筑科技大学 A dual-arm collaborative welding robot and control system for intersecting pipelines
CN114505869A (en) * 2022-02-17 2022-05-17 西安建筑科技大学 A chemical reagent intelligent dispensing machine control system
CN115061724A (en) * 2022-05-12 2022-09-16 厦门航天思尔特机器人系统股份公司 A Robot Program Transplanting Method
CN116294987B (en) * 2022-11-25 2023-12-08 无锡中车时代智能装备研究院有限公司 Coordinate conversion method and system in automatic measurement polishing system with double robots

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101092031A (en) * 2007-07-12 2007-12-26 上海交通大学 Off line programming tool for industrial robot
CN109760045A (en) * 2018-12-27 2019-05-17 西安交通大学 An offline programming trajectory generation method and a dual-robot collaborative assembly system based on the method

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9390203B2 (en) * 2004-06-15 2016-07-12 Abb Ab Method and system for off-line programming of multiple interacting robots
CN105171745B (en) * 2015-08-31 2017-07-07 上海发那科机器人有限公司 A kind of robot Off-line Programming System
CN105945942A (en) * 2016-04-05 2016-09-21 广东工业大学 Robot off line programming system and method

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101092031A (en) * 2007-07-12 2007-12-26 上海交通大学 Off line programming tool for industrial robot
CN109760045A (en) * 2018-12-27 2019-05-17 西安交通大学 An offline programming trajectory generation method and a dual-robot collaborative assembly system based on the method

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
6 自由度机器人位姿误差建模与补偿方法研究;覃志奎;《中国优秀硕士学位论文全文数据库信息科技辑》;20190615;第I140-173页 *
冗余双臂机器人在工业缝制过程中的应用研究;丁磊;《中国优秀硕士学位论文全文数据库信息科技辑》;20180115;第I140-325页,附图5-4 *
机器人离线编程系统的开发及其应用;邓华健;《中国优秀硕士学位论文全文数据库信息科技辑》;20180215;第I140-856页,附图4-13 *

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