Locating overlapping industrial parts for robotic assembly

The problem of recognising overlapping parts is of considerable interest in industrial automation. While it is possible to employ carriers or pallets to separate or prearrange the parts for robotic assembly tasks, a vision system which can recognise the parts even though they may be partially overlapped and in random positions is much flexible.In this paper, we employ a Hough transform technique to determine the poses (translations and rotations) of overlapping parts in the image. Shapes of parts are broken down into fragments, each representing either a line or a circular arc primitive. The geometrical relations and properties of primitives are used to derive the matching of primitive pairs between the model and the image. This paper also presents methods to determine the top-bottom relation of overlapping parts in grey-level image by tracing the shadowed points along the overlapping boundaries. The detected poses along with the top-bottom relation of overlapping parts provide sufficient information for robotic assembly in complex environment.

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