Eaches picking with Brightpick mobile manipulators at Brightpick

The Robot Report Podcast · 9 Nov 2023 · 1h 28m

AI in practice: 3 real uses of AI described

What this episode covers

Jan Zizka, CEO of Brightpick (a spinoff of Photoneo), explains how their mobile manipulator solves eaches picking in warehouses by pulling totes from shelves, using 3D vision to pick items, and returning the tote immediately, a workflow he calls 'Robot to Goods' (RTG). Joyce Sidopoulis and Marita McGinn from MassRobotics discuss their new equity-free accelerator program, which provides $100,000 to 10 startups to help technical founders bridge the gap between engineering and business scaling. The episode also covers recent robotics funding trends, including a $1 billion round for Stack AV, and Boston Dynamics' use of Spot for Fukushima decommissioning and generative AI experiments.

AI in practice

Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.

Engineering & simulationPhotoneo 3D cameras / Photoneo vision technologyautomate 95% of the entire process

The Brightpick mobile manipulator uses onboard Photoneo 3D cameras to image totes pulled from shelves, enabling the robot to identify and pick specific items from random assortments without human intervention.

“they already know and have a solution for 3D vision and and robot guidance. So it's equipped with a photo nail camera. And so they pull the bin into the imaging area. They select an item out of the, uh, or more out of the bin for specific order…”

Speaker 2 · Hear it at 50:33

Engineering & simulationmachine learning picking enginearound 80% of items from the from the basket we see

Brightpick developed its own machine learning-based picking engine that allows the robot to generalize to unseen items, achieving high pick rates in unstructured grocery environments where items vary in appearance.

“Over the time, we develop our own mission learning, uh, a picking engine. Today we can tell that it's, you know, general enough to pick invisible, very high number of items. For example, in grocery ambient environment, it's around 80% of items from the from the basket we see.”

Speaker 5 · Hear it at 56:34

Engineering & simulationmachine learning / AInot possible 5 to 6 years ago

The company leverages recent advances in artificial intelligence and machine learning to generalize to unseen items, a capability they state was not possible 5-6 years ago and is critical for handling the variability of grocery items.

“all the things which are happening over the last 2 years, simply there, that was not possible 5 to 6 years ago, you know, it's like, this is a really serious breakthrough that simply your machine learning can generalize to unseen items, period.”

Speaker 5 · Hear it at 1:09:35

Mentioned

Companies
Photoneo, Boston Dynamics, Stack AV, MassRobotics, DHL
Products
Brightpick, Spot, MassRobotics Accelerator, Handle, Stretch

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