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3D Vision Technology Advances to Keep Pace With Bin Picking Challenges


Author: Jimmy Carroll

Topics: machine vision, convolutional neural network

Organizations: Zivid, CapSen Robotics, IDS Imaging Development Systems, Photoneo, Universal Robots, Allied Moulded

When a bin has one type of object with a fixed shape, bin picking is straightforward, as CAD models can easily recognize and localize individual items. But randomly positioned objects can overlap or become entangled, presenting one of the greatest challenges in bin picking. Identifying objects with varying shapes, sizes, colors, and materials poses an even larger challenge, but by deploying deep learning algorithms, it is possible to find and match objects that do not conform to one single geometrical description but belong to a general class defined by examples, according to Andrea Pufflerova, Public Relations Specialist at Photoneo.

“A well-trained convolutional neural network (CNN) can recognize and classify mixed and new types of objects that it has never come across before,”

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