With the development of industry and manufacturing, the industrial market of industrial robots is also gradually expanding, more and more enterprises cannot produce without industrial robots, but the machine vision system is also expanded with the expansion of industrial robots, industrial robot vision system can be like the human eye, help industrial robots to measure and judge. The vision system of industrial robots can convert the images taken into digital signals and then analyze and control the work of industrial robots. So what is the role of machine vision system in industrial robots?
I. Visual Inspection
The visual inspection process involves testing products on the production line to identify any quality issues. This stage has significantly replaced manual labor in various industries. In the field of pharmaceuticals, machine vision systems are employed extensively. The primary checks conducted by these systems include measurements for size accuracy, detecting defects on the body and shoulders of bottles, and inspecting bottle caps.
II. High-Precision Detection
Certain products require extremely high precision, achieving tolerances as fine as 0.01 to 0.02 meters, and in some cases even reaching U-level precision. Such fine details are beyond the capability of the human eye, necessitating the use of machines for accurate detection.
III. Recognition
This involves using machine vision systems to process, analyze, and understand images for the purpose of recognizing various patterns, targets, and objects. This technology enables the traceability and collection of data and is widely applied in sectors such as automotive components, food, and pharmaceuticals.
IV. Guidance and Positioning
Visual positioning requires machine vision systems to rapidly and accurately locate test components and determine their positions. In loading and unloading operations, machine vision guides robotic arms for precise handling. A fundamental application in the field of semiconductor packaging involves adjusting pick-and-place heads based on chip location information obtained from machine vision systems. This precision is crucial for accurately picking up chips and performing binding operations, representing a basic yet essential application of visual positioning in the machine vision industry.
