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Sorting of items on a moving conveyor belt. Part 1: A technique for detecting and classifying objects

: Mattone, R.; Campagiorni, G.; Galati, F.


Robotics and Computer-Integrated Manufacturing 16 (2000), No.2-3, pp.73-80
ISSN: 0736-5845
Journal Article
Fraunhofer IPA ()
computer vision; neural net

In many situations of industrial interest, a sorting process has to be performed in order to separate different or undesired items among those flowing on a moving conveyor belt. This process consists of looking at the items distributed on the conveyor, localizing any single item, classifying it on the basis of features that make it acceptable or not and, if applicable, gripping it to perform the necessary separation. Fundamental issues here are therefore sensing, i.e., detecting and classifying the items, and gripping, i.e., realizing the required separation in the most efficient way. The two parts of this work deal with these two issues in automatic sorting and present advanced solutions for the sorting of recyclable packaging, an application where the unstructured work environment represents the main difficulty towards the process automation. In Part 1, in particular, the problem of localizing and identifying the wasted items on the moving belt is addressed. The proposed solution is based on the use of the height profile of the objects on the conveyor belt, sampled through a 3D optical device (laser beam plus CCD camera). With the help of fuzzy techniques, a geometrical description of the items is obtained, on which basis a neural classifier can be built. First experimental results are reported, confirming the validity of the presented approach.