Amazon's robotic Picking Challenge this past weekend demonstrated the advancement in deep learning robots and showed how they may come to rule fulfillment warehouses in the future.
Engadget.com reported that the TU Delft robot from the Netherlands won the stowing and picking contests this year. By combining deep learning artificial intelligence and deep-sensing cameras it handily outshined the competition.
"The machine studied 3D scans of the stockroom items to help it decide how to manipulate items with its gripper and suction cup," Engadget explained. "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)."
TechRepublic.com wrote Monday that the robots were judged on their ability to correctly select individual items from shelves, with more points given for picking out items that were mixed in with other products.
"The robot needs to be able to handle variety and operate in an unstructured environment," Carlos Hernández Corbato from TU Delft Robotics Institute told TechRepublic.com. "We are really happy that we have been able to develop this successful system."
The competition items were a cross section of products that can be found commonly in Amazon's warehouses, from clothing to toothbrushes. The robots performed better this year than in 2015, with just under half scoring more than 40 points, which would have gotten them third place last year.
"It was inspiring to see 16 top teams with so many different approaches to the same problem," Tye Brady, chief technologist at Amazon Robotics, told Tech Republic. "And we also saw the advancements robotic technology has made since last year."
The robots, though, still can't top humans, who can pick up to 400 items per hour. The Picking Challenge robots still have a 16.7 percent failure rate.
"Compared with human pickers, the performance of the robot arms in this year's competition looks sub-par," TechRepublic.com explained. "They are slower to spot items with their cameras and more likely to drop them with their grippers and suction cups. But compared with the robots that competed in last year's event they excelled."
© 2025 Newsmax. All rights reserved.