Visual Pick and Place: Difference between revisions

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Suggested by Brian Jones <bdj23@cam.ac.uk>
Client: Theo Markettos, Computer Lab <theo.markettos@cl.cam.ac.uk>


We have a pick and place robot for assembly of circuit boards, which in principle could operate fully automated by extending the open source OpenPnP software. More automation will involve use of machine vision to correctly identify parts - for example checking barcodes when tapes of parts are lined up for assembly, and then visually confirming that the right part has gone into the right place on the board being assembled.
We have a LitePlacer robot that can automatically assemble circuit boards (https://youtu.be/t__ybwOufyg), with a machine vision system based on OpenPnP. Unlike many computer vision problems, the cameras could in principle be moved around, getting better field of view or details of specific regions. Our robot currently uses the vision capabilities for simple tasks such as recognising board features and component tapes to align components it is placing. We would like to extend the capabilities of the system to automate the setup of the machine, for instance printing part numbers from CAD data on sticky labels that the vision system reads; configuring placement of component tapes; recognising parts from their shape or markings to rotate the tape; detecting parts and boards from text printed on them; and guiding the user through setup with augmented image views.

Latest revision as of 16:50, 13 November 2018

Client: Theo Markettos, Computer Lab <theo.markettos@cl.cam.ac.uk>

We have a LitePlacer robot that can automatically assemble circuit boards (https://youtu.be/t__ybwOufyg), with a machine vision system based on OpenPnP. Unlike many computer vision problems, the cameras could in principle be moved around, getting better field of view or details of specific regions. Our robot currently uses the vision capabilities for simple tasks such as recognising board features and component tapes to align components it is placing. We would like to extend the capabilities of the system to automate the setup of the machine, for instance printing part numbers from CAD data on sticky labels that the vision system reads; configuring placement of component tapes; recognising parts from their shape or markings to rotate the tape; detecting parts and boards from text printed on them; and guiding the user through setup with augmented image views.