DIVERSE RANGE OF PRODUCTS
Product size can vary from 50 x 50mm to 450 x 250mm. System handles textured or smooth surfaces. Labels of different shapes and sizes can be designed and printed on.
For low volume produce, such as pomegranates or melons, the cost to upgrade from manual labelling to automated has, until now, been unjustifiable – owing to the sheer physical diversity of such products, and the associated complexities of dealing with them.
However, we have developed an adaptable vision-based robotic system that is capable of affixing labels to such produce, and almost anything with a 3D profile, all on a single processing line, with product and batch changes possible at the a touch of a button.
First, boxes of produce are loaded onto a conveyor. Next, they pass through a vision enclosure where it is scanned by a 3D imaging camera. This is analysed by the system to identify the produce and to provide the robot with the precise location the labels should be placed.
The labels are printed as required to minimise wastage. The labels can be of different shapes and sizes.
Label application is performed by two robots which cooperate to optimise the picking and placing of labels. The robot controllers track the movement of the conveyor, enabling the labels to be applied without slowing down the process.
Finally, the fully-labelled produce then leaves the cell via a roller conveyor.
The complexities of the system are hidden from the user with a simple software interface that can be used to train the system to identify new products. Using a browser-based setup interface, a new product can be added to a list of products to be identified even while the machine is in operation. Training requires that a lone specimen be placed on the conveyor and imaged by camera.
The set-up interface also allows a user to:
The approach to training and target identification makes no assumptions about product positioning or presentation. Consequently, the system is impervious to changes in packaging such as the size of boxes, the number of products in a box and damaged boxes.