ROBOTICS


‘Approximately 3,000 blood samples are delivered… [which] need to be sorted and analysed with different machines’


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Object recognition Te system uses two Kuka robots: a small KR 3 and a medium-sized KR 10. Both of these models fall under Kuka’s KR Agilus series, which benefits from its VisionTech capabilities. Tese are particularly useful tools when it comes to 2D object recognition in quality control applications, thanks to the camera within the robot’s housing. Te robots are able to pick up the transport boxes – which consist of an outer and an


inner box – and then take these apart and open them. Te next step is to check that all of the samples are placed correctly. ‘We check this with a 3D camera,’ explained Madsen. Te camera used here is Sick’s TriSpector1000. Tis model was chosen for its


reliability, providing accuracy even if there are variations in the part colour, position and height of an object. With time a key factor in sorting these samples, ease-of-use for the


operator was important. In addition, factory calibrated data allows for a simplified set-up, as well as a reduction in time and effort. It also helps that the camera is a robust and waterproof model when being used in sometimes unpredictable medical environments. After checking for placement


with the 3D camera, it is the turn again of the robots, which pull out the samples and place them in a buffer. ‘Tis is where


g JUNE/JULY 2020 IMAGING AND MACHINE VISION EUROPE 21


Kuka


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