CN114473324A - Multi-mechanical-arm collaborative splicing welding control method and system based on teaching learning - Google Patents

Multi-mechanical-arm collaborative splicing welding control method and system based on teaching learning Download PDF

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CN114473324A
CN114473324A CN202210154801.8A CN202210154801A CN114473324A CN 114473324 A CN114473324 A CN 114473324A CN 202210154801 A CN202210154801 A CN 202210154801A CN 114473324 A CN114473324 A CN 114473324A
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welding
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mechanical arm
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grabbing
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CN114473324B (en
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徐文福
程天泓
陈涛
李兵
宋小刚
吴志伟
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Shenzhen Graduate School Harbin Institute of Technology
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
    • B23K37/00—Auxiliary devices or processes, not specially adapted to a procedure covered by only one of the preceding main groups
    • B23K37/02—Carriages for supporting the welding or cutting element
    • B23K37/0252—Steering means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1679—Programme controls characterised by the tasks executed
    • B25J9/1682—Dual arm manipulator; Coordination of several manipulators

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  • Mechanical Engineering (AREA)
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Abstract

The invention provides a teaching learning-based multi-mechanical-arm collaborative splicing welding control method and system, wherein the multi-mechanical-arm comprises a welding mechanical arm and a grabbing mechanical arm, the grabbing mechanical arm carries out carrying and overturning support of a plurality of workpieces to be welded, the welding robot carries out front and back double-side welding after splicing of different workpieces, and the multi-mechanical-arm collaborative welding method comprises the following steps: step 1, communication is established between a demonstrator and a master controller cooperatively controlled by multiple machines, the demonstrator sends a request to the master controller to acquire system parameters, and initialization is carried out according to the acquired system parameters; step 2, communication is established between the main controller and the welding mechanical arm and between the main controller and the grabbing mechanical arm so as to carry out data communication and control on the welding mechanical arm and the grabbing mechanical arm; step 3, artificial teaching; step 4, executing a welding task; the invention can realize the automatic feeding and discharging and welding operation of the workpiece by the cooperation of the multiple mechanical arms, and has the advantages of rapid deployment and high welding efficiency.

Description

Multi-mechanical-arm collaborative splicing welding control method and system based on teaching learning
Technical Field
The invention belongs to the technical field of mechanical arm control, and particularly relates to a teaching learning-based multi-mechanical arm collaborative splicing welding control method and system.
Background
The welding robot is an industrial robot for welding work, and the industrial robot is a multipurpose automatic control manipulator capable of being programmed repeatedly, so that welding of different joints can be realized through program design, and particularly, operations such as program compiling, parameter configuration and the like are performed through a teaching programmer (demonstrator).
The teaching method of the robot is generally called a playback mode. In the playback method, an operator operates a teaching operation panel to actually move the robot to a teaching position by jog feed, and sequentially stores robot positions corresponding to the teaching position as position data in the robot; alternatively, the teaching task may be performed by a manual guidance method in which the operator manually moves the robot to the teaching position and similarly stores the teaching position.
In the prior art, teaching learning is generally performed only for a single mechanical arm, and therefore a welding method and a welding system based on teaching learning, which are used for multi-mechanical arm collaborative splicing welding, need to be provided.
Disclosure of Invention
The invention aims to provide a teaching learning-based multi-mechanical arm collaborative splicing welding control method and system, which can realize automatic feeding and discharging and welding operation of workpieces by collaborative cooperation of multiple mechanical arms and have the advantages of rapid deployment and high welding efficiency.
In order to achieve the above object, in one aspect, the present invention provides a teaching learning-based multi-robot-arm cooperative-splicing welding control method, where the multi-robot arm includes a welding robot arm and a grabbing robot arm, where the grabbing robot arm performs carrying and turning support of a plurality of workpieces to be welded, and the welding robot performs front-back double-side welding after splicing different workpieces, and the multi-robot-arm cooperative-welding method includes the following steps:
step 1, communication is established between a demonstrator and a master controller cooperatively controlled by multiple machines, the demonstrator sends a request to the master controller to acquire system parameters, and initialization is carried out according to the acquired system parameters;
step 2, communication is established between the main controller and the welding mechanical arm and between the main controller and the grabbing mechanical arm so as to carry out data communication and control on the welding mechanical arm and the grabbing mechanical arm;
step 3, artificial demonstration
The method comprises the steps that path planning is carried out on a grabbing mechanical arm based on a carrying task and an overturning supporting task of a workpiece to be welded, a demonstrator generates a first motion control instruction and sends the first motion control instruction to a main controller, the main controller analyzes the acquired first motion control instruction, a Cartesian space motion track of the grabbing mechanical arm is acquired and generates a first position control instruction, and the first position control instruction is sent to the grabbing mechanical arm through a controller node to execute corresponding actions;
the welding mechanical arm is subjected to path planning based on the welding seam, the demonstrator generates a second motion control instruction and sends the second motion control instruction to the main controller, the main controller analyzes the acquired second motion control instruction, a Cartesian space motion track of the grabbing mechanical arm is acquired, a second position control instruction is generated, and the second position control instruction is sent to the welding mechanical arm through a controller node to execute corresponding actions;
step 4, executing welding task
And (3) when a welding task is executed, carrying and overturning support of the workpiece to be welded are carried out by adopting the track of the grabbing mechanical arm generated in the step (3), and welding the workpiece to be welded is carried out by adopting the track of the welding mechanical arm generated in the step (3).
In another embodiment of the present invention, in step 1, the teach pendant and the master communicate with each other via HTTP protocol.
As another specific embodiment of the present invention, in step 2, the master controller performs data communication and control with the welding manipulator and the grabbing manipulator by calling an EtherCAT communication node.
As another embodiment of the present invention, the welding robot and the grabbing robot are both six-axis robots, and in step 3, the trajectories of all joints in the six-axis robots are calculated according to the acquired cartesian space motion trajectories, and the position control command of each joint in the six-axis robots is calculated by using a PID algorithm.
As another specific embodiment of the present invention, in step 3, the teach pendant generates a first motion control instruction set having a plurality of first motion control instructions, and sequentially sends the first motion control instructions in the first motion control instruction set at one time or a plurality of times; and the demonstrator generates a second motion control instruction set with a plurality of second motion control instructions, and transmits the second motion control instructions in the second motion control instruction set once or for a plurality of times in sequence.
As another specific embodiment of the invention, the master controller is provided with a reconfigurable algorithm module, and the algorithm module comprises a joint position control module, a Cartesian space position control module, an impedance control module and a visual servo control module.
As another embodiment of the present invention, while the welding task is performed in step 4, the teach pendant requests the current status of the gripping robot and the welding robot from the status issuer on the controller node in a periodic fashion, and displays the enabled status and the movement status on the interface of the teach pendant.
As another embodiment of the present invention, a device list corresponding to the welding task is predefined in the master controller, and before the welding task is executed in step 4, the controller node is called to query the online device and compare it with the predefined device list, and the welding task is executed only when it is matched.
As another specific embodiment of the present invention, in steps 3 and 4, two or more grabbing mechanical arms are used to cooperatively perform a conveying task and a turning supporting task of the to-be-welded workpiece, wherein a force/position coupling algorithm is used to cooperatively control the two or more grabbing mechanical arms.
On the other hand, the invention provides a system for realizing the teaching learning-based multi-mechanical-arm collaborative splicing welding control method.
The invention has the following beneficial effects:
the teaching learning is applied to the multi-mechanical-arm cooperative splicing welding, and the cooperative welding between the multiple mechanical arms can be carried out only by manual teaching, so that the complex calibration operation is avoided, the adaptability to the environment is good, the deployment can be rapidly completed, and the welding efficiency is improved.
The present invention will be described in further detail with reference to the accompanying drawings.
Drawings
FIG. 1 is a general framework schematic of the present invention;
FIG. 2 is a block diagram of a master controller according to the present invention;
FIG. 3 is a schematic diagram of an interface and function menu of the teach pendant of the present invention;
fig. 4 is a schematic diagram of the framework of the force-position coupling control method of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
Example 1
A teaching learning-based multi-mechanical-arm collaborative splicing welding control method is disclosed, as shown in figures 1-3, the multi-mechanical-arm comprises a welding mechanical arm and a grabbing mechanical arm, wherein the grabbing mechanical arm carries out carrying and overturning supporting of a plurality of workpieces to be welded, the welding robot carries out front and back double-side welding after splicing of different workpieces, and the multi-mechanical-arm collaborative welding method comprises the following steps:
step 1, communication is established between a demonstrator and a master controller cooperatively controlled by multiple machines, the demonstrator sends a request to the master controller to acquire system parameters, and initialization is carried out according to the acquired system parameters;
the main controller is provided with a reconfigurable algorithm module, and the algorithm module comprises a joint position control module, a Cartesian space position control module, an impedance control module, a visual servo control module and the like;
specifically, the demonstrator and the master controller communicate with each other through an HTTP (hyper text transport protocol);
step 2, communication is established between the main controller and the welding mechanical arm and between the main controller and the grabbing mechanical arm so as to carry out data communication and control on the welding mechanical arm and the grabbing mechanical arm;
specifically, the main controller carries out data communication and control with the welding mechanical arm and the grabbing mechanical arm by calling an EtherCAT communication node;
step 3, artificial demonstration
The method comprises the steps that path planning is carried out on a grabbing mechanical arm based on a carrying task and an overturning supporting task of a workpiece to be welded, a demonstrator generates a first motion control instruction and sends the first motion control instruction to a main controller, the main controller analyzes the acquired first motion control instruction, a Cartesian space motion track of the grabbing mechanical arm is acquired and generates a first position control instruction, and the first position control instruction is sent to the grabbing mechanical arm through a controller node to execute corresponding actions;
further, the demonstrator generates a first motion control instruction set with a plurality of first motion control instructions, and sends the first motion control instructions in the first motion control instruction set one time or multiple times in sequence;
the welding mechanical arm is subjected to path planning based on the welding seam, the demonstrator generates a second motion control instruction and sends the second motion control instruction to the main controller, the main controller analyzes the acquired second motion control instruction, a Cartesian space motion track of the grabbing mechanical arm is acquired, a second position control instruction is generated, and the second position control instruction is sent to the welding mechanical arm through a controller node to execute corresponding actions;
further, the demonstrator generates a second motion control instruction set with a plurality of second motion control instructions, and transmits the second motion control instructions in the second motion control instruction set at one time or multiple times in sequence;
in step 3, calculating the track of all joints in the six-axis mechanical arm according to the acquired Cartesian space motion track, and calculating the position control instruction of each joint in the six-axis mechanical arm by using a PID algorithm.
Step 4, executing welding task
And (3) when a welding task is executed, carrying and overturning support of the workpiece to be welded are carried out by adopting the track of the grabbing mechanical arm generated in the step (3), and welding the workpiece to be welded is carried out by adopting the track of the welding mechanical arm generated in the step (3).
Correspondingly, before the welding task is executed in the step 4, the controller node is called to inquire the on-line equipment and compare the on-line equipment with a predefined equipment list, and the welding task is executed only when the on-line equipment is matched with the predefined equipment list.
Accordingly, while the welding task is being performed, the teach pendant requests the current state of the grasping robot arm and the welding robot arm from the state publisher on the controller node in a periodic manner, and displays the enabled state and the motion state on the interface of the teach pendant.
In the embodiment, the demonstrator APP is communicated with a computer running a master controller program through an HTTP protocol, the demonstrator APP adopts a Web-based Vue + Typescript framework, and has rich interface components, and the currently realized functional interface comprises motion, functions, monitoring, setting and the like.
For expansion, the demonstrator has the following special functions suitable for multi-machine cooperation:
manual control: coordinated trajectory control under position/force constraint, manual control of any multiple axes, and manual adjustment of position constraint;
parameter configuration: relative position/force constraint, robot relative base coordinate system;
data monitoring: multi-machine joint data, terminal pose data and a servo communication state;
the safety function is as follows: linkage of safety states of multiple robots and detection of collision among robots;
writing a control logic: calling an algorithm process of the multi-machine cooperative controller, and customizing an interface component;
software function package: welding a function package, polishing the function package, spraying the function package and visually positioning the package;
other functions are as follows: user login, real-time simulation display, physical key pressing and data import and export;
for example, in step 3 and step 4, two grabbing mechanical arms are adopted to cooperatively perform a conveying task and a turning supporting task of a to-be-welded workpiece, wherein the two grabbing mechanical arms are cooperatively controlled by using a force/position coupling algorithm, and one of the force/position coupling algorithms of the three mechanical arms is as follows, as shown in fig. 4:
firstly, establishing a kinematic model of a plurality of mechanical arms to obtain:
Figure BDA0003511927640000061
wherein
Figure BDA0003511927640000062
Respectively representing a homogeneous transformation matrix of a robot arm base relative to a world coordinate system, an object coordinate system relative to the world coordinate system, a robot arm tail end coordinate relative to the object coordinate system and a grabbing robot arm tail end relative to a base coordinate, wherein i represents the ith grabbing robot arm;
wherein two grabbing mechanical arms and welding mechanical arms are distributed in an equilateral triangle shape, and the base coordinate is positioned at the center of the equilateral triangle.
Secondly, mapping the motion trail of the workpiece to the joint space of the mechanical arm to obtain:
Figure BDA0003511927640000071
wherein ,qri,frobotIK(.) respectively representing the joint vector of the ith grabbing mechanical arm and the inverse kinematics of the mechanical arm;
then, establishing a kinematic equation of the workpiece through a Newton Euler equation to obtain:
Figure BDA0003511927640000072
wherein m, I and g respectively represent the mass, the inertia matrix and the gravity acceleration of the workpiece;
fe、τerepresenting environmentally applied forces and moments;
v, omega represent linear velocity and angular velocity of the work piece;
Figure BDA0003511927640000073
representing the force and moment exerted by the grabbing mechanical arm;
further, WrCan be derived from the capture matrix G, i.e. Wr＝GWC (4)
wherein ,
Figure BDA0003511927640000074
a force applied to the workpiece for grasping the robotic arm;
Figure BDA0003511927640000075
from equation (4):
Figure BDA0003511927640000076
wherein
Figure BDA0003511927640000077
Being a generalized inverse matrix, wsRepresents an internal force;
Figure BDA0003511927640000078
can be decomposed into internal force W according to the force exerted on the workpiece by the grabbing mechanical armIAnd an external force WEObtaining:
Figure BDA0003511927640000079
Figure BDA00035119276400000710
finally, a force position coupling algorithm of the three mechanical arms is obtained as follows:
Figure BDA0003511927640000081
Figure BDA0003511927640000082
Figure BDA0003511927640000083
Figure BDA0003511927640000084
Figure BDA0003511927640000085
Figure BDA0003511927640000086
wherein WEc、WEd、TEc、TEd、ME、BE、KE、αE and βERespectively representing the contact force of the workpiece and the environment, expected external force, actual track, expected track, mass matrix, damping parameter matrix, rigidity parameter, sampling period and updating rate, WIc、WId、TIc、TId、MI、BI、KI、αI and βIThe representations represent the contact force of the workpiece with the end of the robot arm, the expected internal force, the actual trajectory, the expected trajectory, the mass matrix, the damping parameter matrix, the stiffness parameter, the sampling period, and the update rate, respectively.
The operation process of the teaching aid for the three mechanical arms (one welding mechanical arm and two grabbing mechanical arms) to carry out the cooperative motion is as follows:
(1) and opening the demonstrator APP, and connecting the demonstrator and the master controller under the same local area network.
(2) Setting the IP address of the master controller computer, and inputting a user name and a password for logging in.
(3) The demonstrator sends an HTTP request to a system parameter server to acquire system parameters for initialization.
(4) Operating a demonstrator interface, generating a motion control instruction by the demonstrator and sending an HTTP request; 4.1) selecting the three searched mechanical arms, setting a cooperative motion mode as a fixed constraint, setting the motion direction as x +, setting the speed as 20%, and selecting a 'step mode' in reverse;
4.2) pressing a 'movement' button, sending a request 'fiexd _ constraints: x0, 20' by the demonstrator, and analyzing by the main controller by obtaining an instruction, so that the tail ends of the three mechanical arms move towards the positive direction of the base mark x at the same speed;
4.3) releasing a 'movement' button, sending a request 'fiexd _ constraints: x0, 0' by the demonstrator, and analyzing by the main controller by obtaining an instruction to stop the three mechanical arms at the same time;
4.4) the request can also be manually written in a program writing interface, and a plurality of instructions are sent at one time;
(5) the demonstrator requests the current state from the state publisher on the master node in a periodic manner, and displays the enabling state and the motion state on the interface.
The master controller node (i.e. controller node) in this embodiment adopts a layered design, and is specifically divided into a user layer, a task layer, a control algorithm layer, an equipment layer and a hardware layer;
user layer: the system comprises a controller debugging interface, a demonstrator interface, a simulation visualization function, a programming interface, a user configuration file and safety monitoring equipment, is directly operated by a user and provides visual display for the user, and can write programs by the user.
Task layer: the task layer comprises force planning, position planning and process settingAnd the control device is responsible for analyzing the instruction sequence generated by the user operation, generating the position and force track of the robot or other control algorithm input, and calling the function of the process equipment.
Controller layer: the controller layer comprises reconfigurable controller algorithm modules, such as joint position control, Cartesian space position control, impedance (admittance) control, visual servo control and the like, each controller is provided with an input interface and an output interface which are adapted to specific single or multiple devices, the controllers can be mutually invoked to form a plurality of control closed loops, the top controller receives the input of the task layer and the feedback of the device layer, generates output and inputs the output to the next one or more controllers, and finally sends instructions to the device layer, and the controller layer also comprises a controller manager which is used for loading, executing and destroying the plurality of controllers.
Device layer: for the multi-machine system characteristic, the equipment layer manages any number of actual or simulated robots and process equipment, and sets the equipment into a plurality of equipment groups containing any number of equipment, and the same equipment can exist in the plurality of equipment groups. The device layer receives the device group command and feeds back the state of the device group, and the application object of the controller layer control module can be any device group which meets the requirements of the number and the characteristics of the devices.
Hardware layer: the hardware layer comprises functions of hardware data collection, a motor control interface, bottom layer soft limiting and the like, and further comprises an EtherCAT communication module.
The main controller is realized as follows:
(1) and starting a controller program, reading a predefined equipment list file, calling an EtherCAT communication node, and inquiring the number of slave stations by the EtherCAT to compare with the equipment list.
(2) And calling a process equipment function package according to the equipment list to search process equipment, and prompting when the equipment is lacked.
(3) Taking the coordinated motion as an example, when a command of 'fiexd _ constraints: x0, 20' generated by a user layer through interface operation or programming is sent to a task layer, the task layer plans a cartesian space constant motion position trajectory of three specified mechanical arms and sends the trajectory to a cartesian space motion controller of a controller layer.
(4) The controller layer generates a Cartesian space motion controller, joint tracks of all the mechanical arms are calculated, and the Cartesian space motion controller calls a plurality of single-joint controllers.
(5) The single joint controller calculates and returns a plurality of position commands using a PID algorithm.
(6) The cartesian space motion controller gets the return and inputs it to a group of three devices.
(7) The device layer provides the position command to the communication node, and the communication node is finally executed by the driver and acquires the state feedback.
Although the present invention has been described with reference to the preferred embodiments, it is not intended to limit the scope of the invention. It will be appreciated by those skilled in the art that changes may be made without departing from the scope of the invention, and it is intended that all matter contained in the above description or shown in the accompanying drawings shall be interpreted as illustrative and not in a limiting sense.

Claims (10)

1. The utility model provides a multi-robot arm is in coordination with concatenation welding control method based on teaching study, multi-robot arm is including welding robot arm and snatching the arm, wherein snatch the arm and carry and the upset support of a plurality of work pieces of waiting to weld, and welding robot carries out the positive and negative double-sided welding after the concatenation of different work pieces, its characterized in that, multi-robot arm is in coordination with welding method includes following step:
step 1, communication is established between a demonstrator and a master controller cooperatively controlled by multiple machines, the demonstrator sends a request to the master controller to acquire system parameters, and initialization is carried out according to the acquired system parameters;
step 2, communication is established between the main controller and the welding mechanical arm and between the main controller and the grabbing mechanical arm so as to carry out data communication and control on the welding mechanical arm and the grabbing mechanical arm;
step 3, artificial demonstration
The method comprises the steps that path planning is carried out on a grabbing mechanical arm based on a carrying task and an overturning supporting task of a workpiece to be welded, a demonstrator generates a first motion control instruction and sends the first motion control instruction to a main controller, the main controller analyzes the acquired first motion control instruction, a Cartesian space motion track of the grabbing mechanical arm is acquired and generates a first position control instruction, and the first position control instruction is sent to the grabbing mechanical arm through a controller node to execute corresponding actions;
the welding mechanical arm is subjected to path planning based on the welding seam, the demonstrator generates a second motion control instruction and sends the second motion control instruction to the main controller, the main controller analyzes the acquired second motion control instruction, a Cartesian space motion track of the grabbing mechanical arm is acquired, a second position control instruction is generated, and the second position control instruction is sent to the welding mechanical arm through a controller node to execute corresponding actions;
step 4, executing welding task
And (3) when a welding task is executed, carrying and overturning support of the workpiece to be welded are carried out by adopting the track of the grabbing mechanical arm generated in the step (3), and welding the workpiece to be welded is carried out by adopting the track of the welding mechanical arm generated in the step (3).
2. The multi-robot-arm collaborative splicing welding control method based on teaching learning of claim 1, wherein in the step 1, the teaching device and the master controller communicate with each other through an HTTP protocol.
3. The multi-mechanical-arm collaborative splicing welding control method based on teaching learning of claim 1, wherein in the step 2, the master controller calls an EtherCAT communication node to perform data communication and control with the welding mechanical arm and the grabbing mechanical arm.
4. The teaching learning-based multi-robot-arm collaborative splicing welding control method according to claim 1, wherein the welding robot and the grabbing robot are both six-axis robots, and in step 3, trajectories of all joints in the six-axis robots are calculated according to the acquired cartesian space motion trajectories, and position control commands for each joint in the six-axis robots are calculated by using a PID algorithm.
5. The multi-robot-arm collaborative splicing welding control method based on teaching learning of claim 1, wherein in the step 3, the teach pendant generates a first motion control instruction set having a plurality of first motion control instructions, and sequentially transmits the first motion control instructions in the first motion control instruction set once or for a plurality of times; and the demonstrator generates a second motion control instruction set with a plurality of second motion control instructions, and transmits the second motion control instructions in the second motion control instruction set once or for a plurality of times in sequence.
6. The teaching learning-based multi-robot collaborative splicing welding control method according to claim 1, wherein the master controller is provided with reconfigurable algorithm modules, and the algorithm modules comprise a joint position control module, a Cartesian space position control module, an impedance control module and a visual servo control module.
7. The teaching learning-based multi-robot collaborative mosaic welding control method according to claim 1, wherein the teach pendant requests the current state of the gripping robot and the welding robot from a state publisher on the controller node in a periodic manner while performing the welding task at step 4, and displays the enabled state and the motion state on an interface of the teach pendant.
8. The teaching learning-based multi-robot collaborative splicing welding control method according to claim 1, wherein a device list corresponding to the welding task is predefined in the master controller, and before the welding task is executed in step 4, the controller node is called to inquire the on-line device and compare the on-line device with the predefined device list, and the welding task is executed only when the on-line device is matched with the predefined device list.
9. The teaching learning-based multi-robot-arm collaborative splicing welding control method is characterized in that two or more grabbing robots are adopted to cooperatively carry out a conveying task and a turning supporting task of a workpiece to be welded in step 3 and step 4, wherein a force/position coupling algorithm is adopted to cooperatively control the two or more grabbing robots.
10. A system for implementing the teaching learning-based multi-robot collaborative splicing welding control method according to any one of claims 1 to 9.
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