For a pioneering tech company, Amazon relies quite a bit on human labor, most notably in its warehouses. The company wants to change that via machine learning and robotics, which is why earlier this year it invited 30 teams to a “Picking Contest.”
In order to win the contest, a team needed to build a robot that can outpace other robots in detecting and identifying an object on a shelf, gripping said object without breaking it, and delivering it into a waiting receptacle.
According to Engadget, Team RBO, composed of researchers from the Technical University of Berlin, won last month’s competition by a healthy margin. Their winning design combined a WAM arm (complete with a suction cup for lifting objects) and an XR4000 mobile base into a single unit capable of picking up 12 objects in 20 minutes—not exactly blinding speed, but enough to demonstrate significant promise.
As suggested by a new interactive tool from NPR, itself based on a formula compiled by Oxford researchers, jobs that require a minimum of human interaction and creative problem-solving are at higher risk of automation. Amazon already uses some robots in its warehouses, mostly for retrieving objects from storage, but it remains to be seen whether it’ll expand its cybernetic legions to replace those jobs currently occupied by human workers.
If Amazon’s contest demonstrated anything, however, it’s that it could be quite a long time before robots are capable of identifying and sorting through objects at speeds even remotely approaching human. Chances seem good that Amazon will ask future teams to build machines that are even smarter and faster.