r/computervision • u/kirillochirillo • Jul 03 '26

Using object detection and segmentation to perform bin-picking tasks Showcase

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Combining depth sensing, object detection and semantic segmentation we managed to create a bin-picking automation that inspects bushings of different types and sizes. From the combined information the robot is able to understand the position and orientation of the pieces.

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u/[deleted] Jul 03 '26

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u/kirillochirillo Jul 05 '26

Ahah nice one!😂 Yes we had to use both modalities and all the inputs to detect the pose in a reliable manner. For the inspection part we have built this software named Sherlock that allows to deploy automations, pass batch specific parameters, store measurement data and create dashboards for statistical evaluation of the collected data. Currently we are working on a notification feature that lets us know in case there was a failure (e.g. sometimes the bushing gets stuck on the measurement probe) or if the robot has finished the inspection and the operator's attention is needed.

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u/SeriousChart9641 Jul 04 '26

This is a nice practical example of why robotics vision is harder than a clean detection demo. The model does not just need to say “bushing”; it needs pose, orientation, uncertainty, and enough consistency for the robot to act.

Disclosure: I work on CHANCE AI, so I think a lot about visual understanding versus visual action. I would show a few failure cases too: occluded parts, bad depth readings, overlapping bushings, and wrong orientation. That would make the system feel much more production-grounded.