A Warehouse Robot Learns to Sort Out the Tricky Stuff

Programming a robotic arm to deal with every situation, one rule at a time, is impossible. At Knapp, Mr. Puchwein and his partners had tried and failed for years to create a robot with the dexterity and flexibility needed for the job.

Covariant, which is working with Knapp, built software that could learn through trial and error. First, the system learned from a digital simulation of the task — a virtual recreation of a bin filled with random items. Then, when Mr. Chen and his colleagues transferred this software to a robot, it could pick up items in the real world.

The robot could continue to learn as it sorted through items it had never seen before. Inside the German warehouse, the robot can pick and sort more than 10,000 different items, and it does this with more than 99 percent accuracy, according to Covariant.

This represents a significant change for the online retail and logistics industries.

Late last year, the international robot maker ABB ran a contest. It invited 20 companies to design software for its robot arms that could sort through bins of random items, from cubes to plastic bags filled with other objects.

Article source: https://www.nytimes.com/2020/01/29/technology/warehouse-robot.html?emc=rss&partner=rss