At present, robots are widely used in the fields of welding, assembly, handling, painting and polishing, and the complexity of tasks is increasing, and users are increasingly pursuing the quality and efficiency of products. In this form, the programming style, programming efficiency and quality of the robot are becoming more and more important. It is the ultimate pursuit of the development of robot programming technology to reduce the difficulty and workload of programming, improve programming efficiency, and achieve adaptive programming, thus improving production efficiency.
Development and application of programming technologyFor industrial robots, there are three main types of programming methods: online programming, offline programming, and autonomous programming. In the current application of robots, manual teaching still dominates the entire robot welding field. Off-line programming is suitable for structured welding environments. However, for three-dimensional welds with complicated trajectories, manual teaching is not only time-consuming but also difficult to meet the welding accuracy requirements. It is a development trend to replace manual teaching with computer-controlled robots under visual guidance.
Teaching programming technology(1) Online teaching programming is usually performed by the operator through the teaching box to control the end of the robot tool to reach the specified posture and position, record the robot pose data and write the robot motion command to complete the trajectory planning, posture, etc. of the robot in normal processing. Collection and recording of joint data information.
The teaching box teaches the advantages of online teaching and is easy and intuitive to operate. As shown in Figure 1, the teaching box mainly has two types of programming and remote sensing. For example, the robot is used to spot weld the automobile body. First, the operator controls the robot to reach each solder joint to manually teach each spot welding track, and reproduces the teaching welding track by means of teaching reproduction during the welding process, thereby The welding of each solder joint at each position of the vehicle body is realized. The body robot spot welding process is shown in Figure 2. However, the position of the vehicle body during welding is difficult to ensure that it is exactly the same every time. Therefore, in actual welding, it is usually necessary to increase the laser sensor to correct and correct the welding path.
Figure 1 robot teaching box
Figure 2 Auto body robot spot welding
(2) Laser sensing assisted teaching
In extreme environments such as space exploration, underwater construction, and nuclear power plant repair, the operator cannot be on the scene, and the completion of the welding task must be done by remote control. The lighting conditions of the environment are poor, the visual information cannot fully feedback the situation on the spot, and stereo vision is used as a visual feedback means, and the teaching period is long. Laser vision sensing can obtain weld contour information and feedback to the robot controller to adjust the torch position tracking weld in real time. Gao Hongming of Harbin Institute of Technology proposed a laser vision sensing-assisted remote teaching technology for remote-controlled welding, which overcomes the shortcomings of remote-based teaching based on stereoscopic display. Laser feature sensing is used to extract weld feature points as teaching points, which improves the recognition accuracy and realizes remote teaching of plane curve welds and complex space welds (see Figure 3).
Figure 3 Remote control operating system based on laser-assisted teaching
(3) Force sense sensing aid teaching
Due to the visual error, the stereo vision teaching accuracy is low, the laser vision sensor can obtain the weld contour information, and the feedback is given to the robot controller to adjust the welding gun position tracking weld seam in real time. However, it is also unable to adapt to all remote welding environments. For example, the surface state of the workpiece has certain influence on laser-assisted teaching, and the extraction of irregular weld feature points is difficult. For this reason, Gao Hongming of Harbin Institute of Technology proposed "remote welding force telemetry teaching technology" The force sensor is used to identify the weld seam, the system structure is simple, the cost is low, the reaction sensitivity is high, the force sense sensor is directly in contact with the weld seam, and the teaching precision is high. Through the force sense televised weld identification model and adaptive control model, the local adaptive control of tele-teaching is realized, and the macro-global monitoring of remote-controlled welding remote teaching is realized through sharing technology and visual presence.
(4) Special tools to assist teaching
In order to make the teaching process of the robot in three-dimensional space more intuitive, some auxiliary teaching tools are introduced into the online teaching process, and the auxiliary teaching tools include a position measuring unit and an attitude measuring unit to measure the spatial position and posture, respectively. Consisting of two arms and one wrist, with 6 degrees of freedom, each key angle is recorded by a photoelectric encoder. During operation, the operator holds the wrist of the device, teaches the machining path, records the position and posture of each point on the path, and then converts the coordinates into the machining path value of the robot to realize teaching programming, which is easy to operate. High precision, no need for the operator to actually operate the robot, which is very convenient for many non-professional operators.
Auxiliary teaching with laser and other devices improves the flexibility and flexibility of the robot, reduces the difficulty of operation, and improves the precision and efficiency of robot processing, which is very practical in many occasions.
2. Offline programming technologyOff-line programming has the following advantages over online programming:
1 Reduce the downtime, the robot can still work on the production line when programming the next task.
2 Improves the programming environment by keeping programmers away from dangerous work environments.
3 Wide range of applications, can be programmed for a variety of robots, and can easily achieve optimal programming.
4 Easy to integrate with CAD/CAM system to achieve CAD/CAM/ROBOTICS integration.
5 Program complex tasks in advanced computer programming languages.
6 Easy to modify the robot program.
(1) Programming key steps Robot offline programming is to use the results of computer graphics, through the three-dimensional modeling of the work unit, to establish a scene corresponding to the real working environment in the simulation environment, using the planning algorithm to control and operate the graphics, The trajectory planning is performed without using an actual robot, and a robot program is generated. The key steps are shown in Figure 4. Figure 5 shows an example of off-line programming using FANUC's Roboguide software. The product is part of the Volkswagen mold, and it needs to be laser-clad on its surface. Because the surface is more complicated, it is impossible to determine the path by manual teaching. Therefore, offline programming software is used to solve it. Firstly, the CAD model of the mold and the geometric position relationship between the robot and the mold are established, and then the trajectory planning and off-line programming simulation are performed according to the specific process. After confirming the error, the download is performed in the robot control, and the practice proves that the better result is obtained.
Figure 4 Key steps in offline programming
Figure 5 Roboguide-based offline programming and simulation
(2) Commercial offline programming software generally includes: geometric modeling function, basic model library, kinematics modeling function, work unit layout function, path planning function, automatic programming function, multi-machine coordinated programming and simulation function.
Third-party offline programming (domestic): RobotArtRobotMaster, RobotWorks, Robomove, RobotCAD, DELMIA
Robot manufacturers (foreign): (ABB) RobotStudio, (Fanaco) RoboGuide, (KUKA) KUKA Sim, (Yakawa) MotoSim
The system layout can be simulated to confirm the reachability of TCP, whether it interferes, or offline programming simulation, and then the offline programming program can be simulated and downloaded to the robot for execution.
3. Independent programming technologyWith the development of technology, various tracking measurement sensing technologies have become more and more mature. People have begun to study the self-teaching technology of welding robots to control the welding path by using the welding measurement information as feedback.
(1) Autonomous programming based on laser structured light The principle of self-planning based on structured light is to install the structured light sensor at the end of the robot to form the "eye in hand" working mode, as shown in Figure 6, using the weld The tracking technique measures the center coordinates of the weld point by point and establishes a database of weld trajectories as a path for the welding gun during welding.
Figure 6 Autonomous programming based on structured light path
South Korea's Pyunghyun Kim installed a line-structured light vision sensor at the end of a 6-DOF welding robot to teach the free-surface welds in a structured environment. A coordinate is created on the weld along with the weld trajectory to express the position and direction of the weld, and combined with the connection type (lap, butt, V-shaped) to form the robot welding path, which also uses 3 splines. The function fits the space weld trajectory, avoiding the errors caused by conventional straight-line connections, as shown in Figure 7.
Figure 7 Sensor scans the weld to obtain the weld path
(2) Autonomous programming based on binocular vision Autonomous teaching based on visual feedback is the key technology for autonomous planning of robot path. The main principle is: under certain conditions, the main control computer automatically tracks along the weld through the visual sensor. Collect and identify the weld image, calculate the spatial trajectory and orientation (ie pose) of the weld, and automatically generate the pose parameters of the robot torch (Torch) according to the optimized welding requirements.
(3) Multi-sensor information fusion autonomous programming Researchers use force controllers, vision sensors and displacement sensors to form a high-precision automatic path generation system. The system configuration is shown in Figure 8. The system integrates displacement, force, and visual control, introduces visual servo, and can perform actions based on sensor feedback information. In this system, the robot can automatically generate the robot path according to the line drawn by the marker. The displacement controller is used to maintain the pose of the robot TCP point. The visual sensor is used to make the robot automatically follow the curve. The force sensor is used to keep the distance between the TCP point and the workpiece surface. Constant.
Figure 8 Automatic path generation system based on vision, force and position sensors
4. Augmented reality based programming technologyAugmented reality technology is derived from virtual reality technology. It is a technology for calculating the position and angle of camera images in real time and adding corresponding images. The goal of this technology is to put the virtual world on the screen and interact with the real world. Technology enables computer-generated 3D objects to be merged into real-world scenes, enhancing user interaction with the real world. The use of augmented reality technology for robot programming is revolutionary.
Augmented reality technology combines real real environment and virtual spatial information. It takes advantage of animation simulation in real environment and provides interactive channel between real environment and virtual space information. For example, a virtual aircraft cleaning robot model is applied to a scaled down aircraft model. The virtual robot is controlled to move along a certain trajectory for the aircraft model to generate a robot program, and then the real robot is calibrated and programmed.
The augmented reality-based robot programming technology (RPAR) enables robot offline programming without a real artifact model in a virtual environment. Since virtual robots can be added to the real world, this technique is a very effective means when in-situ access is required, which avoids the technical problems that may be encountered in calibrating real and virtual environments. The architecture of augmented reality programming is shown in Figure 9. It consists of virtual robot simulation, real-world robot verification, and virtual robot simulation and real-world robot verification.
Figure 9 Augmented reality based robot programming architecture
Summary: The traditional online teaching programming will only be applied in a few occasions. With the update of technology, the latter three will gradually grow, and some will still get the market when there is a breakthrough in the technology development period.
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