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Thermal imaging & vision systems


Picking the unknown


T


he global pandemic has radically impacted the supply chain and logistics industry, making the need for robotic


automation more urgent than ever. With more than 70 per cent of labour in warehousing being dedicated to picking and packing, numerous companies are gradually investing in logistics automation. But what happens when the robots must handle an unlimited number of (unknown) stock keeping units? These companies need a fast, reliable, and robust way to automate picking and placing of a large variety of objects.


This challenge was taken up successfully by the Dutch company Fizyr. The computer vision company based in Delft focuses on enabling robots to pick unknown objects even in harsh logistics environments. The result is an automated vision solution that enables logistic automation in various conditions and applications, like item picking, parcel handling, depalletising, truck unloading or baggage handling. To complete the system with the optimal hardware, Fizyr integrates compact, robust Ensenso 3D cameras in combination with high performance GigE uEye cameras from IDS.


Ensenso 3D camera allows robots individual handling of unknown objects


Instead of providing a proprietary picking cell,


like most players in the market do, Fizyr has created a plug-and-play modular software product that integrates smoothly with any system, giving integrators the freedom to choose the best hardware (e.g. Cobots or Industrial robots) for their picking cell. While facilitating cost, robustness, and speed optimisation, IDS is the preferred partner in terms of cameras. In essence, the camera sees products to be picked or classified. Depending on the individual customer application, up to four Ensenso 3D cameras in combination with powerful GigE uEye CMOS cameras are used. The integrated IDS industrial cameras ensure


a reliable, precise image capture that is needed for Fizyr’s software algorithms which provide over 100 grasp poses each second, including the classification to handle objects differently. The software also performs quality controls and detects defects to prevent damaged items from being placed on a sorter – with the help of IDS cameras as sharp eyes of the automatic system. Thus these algorithms are able to provide all relevant information about segmentation as well as about classification of type of parcel (including box, bag, envelope/flat, tube, cylinder, deformable, etc.). The system recognises outliers or non- conveyables (i.e. damaged goods), best possible grasp poses in six DoF (degrees of freedom) and multiple ordered poses per object. It allows sensors or robots to deal with closely stacked or overlapping objects, highly reflective items and apparel in polybags, white-on-white and black- on-black flats, as well as transparent objects.


48 April 2021 Instrumentation Monthly


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