Innovative robot takes stock

Andyvision is the name of this ET-looking robot.  You can find it at the CMU store near the Carnegie Mellon University, checking the inventory.

Andyvision[…] scans the shelves to generate a real-time interactive map of the store, which customers can browse via an in-store screen. At the same time, the robot performs a detailed inventory check, identifying each item on the shelves, and alerting employees if stock is low or if an item has been misplaced.

The prototype has been rolling around the floors of the store since mid-May. This Tuesday, Priya Narasimhan, a professor at CMU who heads the Intel Science and Technology Center in Embedded Computing, demonstrated the system to attendees at an Intel Research Labs event in San Francisco.

While making its rounds, the robot uses a combination of image-processing and machine-learning algorithms; a database of 3-D and 2-D images showing the store’s stock; and a basic map of the store’s layout—for example, where the T-shirts are stacked, and where the mugs live. The robot has proximity sensors so that it doesn’t run into anything.

The map generated by the robot is sent to a large touch-screen system in the store and a real-time inventory list is sent to iPad-carrying staff.

This is not a break-through discovery, there is nothing technologically new.  It is a great example of innovation, of what can be done by just combining existing types of algorithms in a novel way.  It is based on many computer-vision programs, as scanning barcodes, reading text, and using visual information of shape, size or color to identify an item.  But it can also infer the identity from the knowledge it has of the structure of the shop and its proximity to other items:

“If an unidentified bright orange box is near Clorox bleach, it will infer that the box is Tide detergent,” she says.

Narasimhan’s group developed the system after interviewing retailers about their needs. Stores lose money when they run low on a popular item, and when a customer puts down a jar of salsa in the detergent aisle where it won’t be found by someone who wants to buy it; or when customers ask where something is and clerks don’t know. So far, the robotic inventory system seems to have helped increase the staff’s knowledge of where everything is. By the fall, Narasimhan expects to learn whether it has also saved the store money.

Narasimhan thinks computer-vision inventory systems will be easier to implement than wireless RFID tags, which don’t work well in stores with metal shelves and need to be affixed to every single item, often by hand. A computer vision system doesn’t need to be carried on a robot; the same job could be done by cameras mounted in each aisle of a store. [..]  The biggest challenge for such a system, she says, is whether it “can deal with different illuminations and adapt to different environments.”

After its initial test at the campus store, Narasimhan says, the Carnegie Mellon system will be put to this test in several local stores sometime next year.

I particularly find it cute to have an ET wandering around, so let’s hope their economical expectations are fulfilled, and think of for more innovative ideas of this order!

 

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