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.