The core components that industrial robots cannot do without flexible manufacturing
The Robotic Tool Changer makes the robot application more flexible by enabling the robot to automatically replace different end effectors or peripheral equipment. These end effectors and peripherals include, for example, spot welding guns, grippers, vacuum tools, air and electric motors, and more. The tool changer includes a robot side for mounting on the robot arm and a tool side for mounting on the end effector. The tool changer enables different media such as gas, electrical signals, liquids, video, ultrasound, etc. to communicate from the robot arm to the end effector. The advantages of the robotic tool changer are:
1. Production line replacement can be completed within seconds;
2. Maintenance and repair tools can be quickly replaced, greatly reducing downtime;
3. Increase flexibility by using more than 1 end effector in the application;
4. Use the end effector that automatically exchanges a single function to replace the original cumbersome and complex multi-functional tooling effector.
Robot tool quick changer enables a single robot to exchange different end effectors during manufacturing and equipment to increase flexibility, widely used in automatic spot welding, arc welding, material grabbing, stamping, inspection, hemming, assembly, material Removal, burr cleaning, packaging, etc. In addition, the tool quick-change device can provide backup tools for tools in some important applications, effectively avoiding unexpected events. Compared with manual tool changing in hours, the tool quick-change device can automatically replace the spare tool within seconds. At the same time, the device is also widely used in some non-robot fields, including pallet systems, flexible fixtures, manual spot welding and manual material snatch.
Industrial Robot Vision Guidance and Positioning
For industrial Robots working on automated production lines, the most common type of operation is the “grab-and-place” action. In order to complete this kind of operation, it is necessary to obtain the positioning information of the operated object. First, the robot must know the pose of the object before it is operated to ensure that the robot can grasp it accurately; secondly, it must know the target pose of the object after it is operated. , to ensure that the robot completes the task accurately.
In most industrial robot applications, the robot only operates according to a fixed program, the initial pose and end pose of the object are predetermined, and the quality of the task completion is guaranteed by the positioning accuracy of the production line. In order to operate with high quality, the production line is required to be relatively fixed and the positioning accuracy is high. The result is that the production flexibility is reduced, but the cost is greatly increased. At this time, the flexibility of the production line and the product quality are contradictory.
Visual guidance and orientation are ideal tools to resolve the above contradictions.
Industrial robots can understand changes in the working environment in real time through the vision system, and adjust actions accordingly to ensure the correct completion of tasks. In this case, even if there is a large error in the adjustment or positioning of the production line, it will not have much impact on the accurate operation of the robot. The vision system actually provides an external closed-loop control mechanism to ensure that the robot automatically compensates for errors caused by environmental changes.
The ideal visual guidance and positioning should be based on visual servoing. First observe the approximate orientation of the object, and then observe the deviation between the robot and the object while the robot moves, and adjust the movement direction of the robot according to this deviation until the robot and the object are in accurate contact. However, there are many difficulties in the realization of this positioning method.
Direct visual guidance and localization is to describe the spatial pose of objects in the robot environment in detail at one time, and guide the robot to complete the action directly. Compared with the method based on visual servoing, the computational load of direct vision guidance is greatly reduced, which creates conditions for practical application, but this must be based on a premise: the vision system can accurately determine the three-dimensional object in the robot space (in the base coordinate system). pose information.
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