Pick and place

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What technologies are available for pick & place applications?

Optic hardware setup

An important component of a pick & place application is the vision setup. It is crucial that vision setup is optimised for the application at hand. It is beneficial to enhance the visibility of the localisation features of the product. To optimise this we use different approaches:

• Position of the light relative to the camera
• 2D vs 3D technology
• Light polarisation

The position of the light relative to the camera can be important to improve the visibility of the edges or the contour of the product. The edges and contour of the product are important features to orientate the products accurately. This is normally done with a light source that is placed underneath the product, called a backlight.

It is also possible to use 3D technology to find and orientation the desired products. Here we acquire 3D information of the product. The benefit of using 3D camera technology is that there is no lightning needed. If for example there is a lot of oil and dirt on the product, it could potentially give problems to the backlight that positioned underneath the product. This would be no problem for a 3D camera.

At last, light polarisation can be used to suppress unwanted reflections of light. Light is build up out of many waves in different orientations. If we polarise the light we can only look at one orientation of the light. The acquired images can be less dependent of external light if a polariser is used. It is even possible to light up some parts of the products with this polarisation technique.

Software development

Once the image quality is optimised it is time to process the images and find the location of the product that has to be picked. These are the possible technologies that can be used:

• Traditional machine vision approaches
• Artificial intelligence

The traditional machine vision approaches commonly use 'handcrafted features' to make a decision. 'Hand crafted features' are properties that are derived using various algorithms that use information that is presented in the image itself. Simple examples of features could be spots, edges, corners and presented colours. Once these features are know it is possible to make a decision about the location of the product. Depending on the available information, it is possible to derive a 2D or 3D orientation. If the resolution of the images are high enough it is possible to have a very accurate picking accuracy.

The traditional machine vision approaches have their limitations but for most pick & place application they will be sufficient. In some exotic cases these traditional machine vision approaches will not work. This is when artificial intelligence, more specifically machine learning, comes in. This is a more advanced and smarter technology that can be optimised for a specific task. Machine learning also uses features in the image but now they are not engineered but learned with images that are made in the past. These machine learning techniques can be used to locate the product.

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Are you interested in working with us for your pick-and-place application?

Contact us via info@covicon.be or continue via contact.

What reference projects does Covicon have?

Have a look at the pick and place applications implemented by Covicon.

Picking fittings

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