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Amazon robot challenge winner counts on deep learning AI
Amazon's robot Picking Challenge is back for a second year, and it's clear that the competition has learned a lot in that time... in more ways than one. The Netherlands' TU Delft won both parts of the challenge (stowing and picking warehouse items) with a robot that relied on the combination of deep learning artificial intelligence and depth-sensing cameras to get the job done. The machine studied 3D scans of the stockroom items to help it decide how to manipulate items with its gripper and suction cup. That adaptive AI made a big difference, to put it mildly. The arm got a near-flawless score in the stowing half of the event, and was over three times faster at picking objects than last year's champion (100 per hour versus 30).
Amazon crowns winner of first warehouse robot challenge
The robots that joined Amazon's Picking Challenge aren't quite ready to replace human warehouse workers, but some of them seriously showed great promise. Team RBO from the Technical University of Berlin, in particular, demolished all the other 27 competitors by winning the contest with a 60-point lead over the second place team. If you recall, Amazon challenged companies and institutions a few months ago to build a machine that can pick the right items from fully-stocked warehouse shelves to fulfill orders. For the test itself conducted during IEEE's International Conference on Robotics and Automation in Seattle, the e-commerce giant had participants pluck different kinds of items from a standard shelf, including a rubber ducky, a pack of Oreo cookies, various dog toys and a paperback book.
