Visual Pick and Place: Difference between revisions

From Computer Laboratory Group Design Projects
Jump to navigationJump to search
No edit summary
No edit summary
 
(One intermediate revision by the same user not shown)
Line 1: Line 1:
Client: Theo Markettos, Computer Lab <atm26@cam.ac.uk>
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), and would like it to self-configure using its machine vision system, which is based on OpenPnP. Our robot currently uses the vision system to recognise board features and component tapes, enabling automated alignment of the components it is placing.  We would like to extend the capabilities of the system to automate the setup of the machine, for instance printing sticky labels from CAD software and reading them via vision, recognising components, detecting their alignment, reading their values and preventing the user making mistakes.
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.