Applications of machine vision in industrial robotics

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Machine vision is a part of artificial intelligence and is based on the use of different technologies to recognize images, shapes, faces, colors, etc. Machine vision applications are as diverse as intrusion detection, road safety maintenance or process control in industrial automation. And it is in this last field where robotics and machine vision come together to take automation to the next level. To a stadium in which the machines can modify their activity based on what they perceive in their environment. In other words, they no longer only act with preprogrammed movements, but can modify them after processing what they see.

Machine vision in quality control processes

Machine vision allows total control of production, identifying if there is any defect in the product. Its precision exceeds that of the human eye, discovering flaws in sizes smaller than 0.05mm. It is applicable to any type of industry or product: cracks in metal can be identified; a faulty print; inadequate size; etc.

When it comes to more complex composite products, machine vision makes it possible to check that each piece is in place and verify that the final assembly is correct.

Machine vision applied to a palletizing robot

According to DZOptics, machine vision emulates human vision, but with one big difference. Human vision has characteristics that tend towards the qualitative, while machine vision focuses more on quantitative observations. That is why it becomes an extraordinary tool when it comes to making exact measurements: sizes, parallelisms, straightness.

This system, applied to a palletizing robot-of boards, for example- allows checking that the thickness of the sheet is correct, verifying the cutting angles, or that there is no damage to the surface. If the robot detects that something does not meet the established criteria, it will discard the wooden plank in a disposal basin.

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Machine vision is key for “pick and place” robots

A “pick and place” system is an industrial solution that consists of taking a product and positioning it in another place. When the product advances disorderly along the picking line, the robot must be able to calculate the trajectory, the speed, the position of the product… or even the type of product (differentiation by color) in order to understand the best way to pick up the product. part and reposition it in the correct position. And this information comes through the machine vision system.

Types of machine vision system

There are different machine vision systems that can be integrated into an automation project. Some are simple sensors and others use quite complex technology. The use of one type or another will depend on the needs of the project.

  • Vision sensors: they are simple systems to install, but also more basic. Its task is limited to detecting the passage -of an object- or the failure.
  • Smart cameras and integrated vision systems: they offer better performance than vision sensors and have great computing power. This allows them to provide a solution to most industrial vision applications.
  • Advanced vision systems: they have many similarities with the previous ones, but they have much more powerful hardware. This allows the system to analyze a large amount of data simultaneously and work with more advanced analysis algorithms.

Talking about machine vision seems to talk about the future, but it is a reality that is taking place now. It is a solution that already has a very advanced technological development. Machine vision represents a new opportunity to further develop the field of industrial automation. Thanks to it, some processes that previously had to be done manually in non-ergonomic workstations can be completed.

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