Object recognition in bin picking

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The problem to be investigated is 3D computer vision-based Object Detection, Pose Estimation and Tracking**(OD/PE/Tr) of industrial parts for automated flexible assembly operations. In conventional automated**assembly, robotic devices manipulate parts which are highly structured and precisely aligned, using special**purpose fixtures and jigs. Flexible automation allows an increasing degree of uncertainty in the positions of the**parts to be manipulated, which can significantly reduce the cost and increase the value of the automation**process and equipment. Accommodating this increased uncertainty requires advanced capabilities, including**trajectory and grasp planning, collision avoidance, and computer vision methods of OD/PE/Tr.**The objective of this project is to initiate a research program to provide state-of-the-art 3D computer vision**methods and expertise to the partner company, Bluewrist Inc., a developer of innovative industrial automation**solutions and products in the areas of robotics and machine vision. The applicant, Prof. Michael Greenspan,**has a recognized research expertise in OD/PE/Tr in 3D range data.**This project will launch a meaningful research collaboration, which will increase Bluewrist's profitability**and allow them to hire more personnel to deliver, support and further develop their products. This will help**Canada with increased employment in high value technology development. There will also be a reputational**benefit to Canada, as Bluewrist further entrenches as an industry leader in innovative industrial automation**solutions.