Robin uses its suction gripper to pick packages from a conveyor belt.
By Brianna Wessling
Thousands of packages pass through Amazon’s fulfillment centers every day. More and more of those packages are picked up, scanned, and organized by Amazon’s Robin robotic arm.
Robin picks packages from a conveyor belt with its suction gripper, scans them and then places them on a drive robot that routes it to the correct loading dock. Robin’s job is particularly difficult because of its rapidly changing environment. Unlike other robotic arms, Robin doesn’t just perform a series of pre-set motions, it responds to its environment in real-time.
“Robin deals with a world where things are changing all around it. It understands what objects are there — different sized boxes, soft packages, envelopes on top of other envelopes — and decides which one it wants and grabs it,” Charles Swan, a senior manager of software development at Amazon Robotics and AI, said. “It does all these things without a human scripting each move that it makes. What Robin does is not unusual in research. But it is unusual in production.”
Amazon’s team decided to take a unique approach when teaching Robin how to recognize packages coming down a conveyor belt. Instead of teaching computer vision algorithms to segment scenes into individual elements, the team allowed the model to try to find objects in an image on its own. After the model finds an object, the team provides feedback on how accurate it is.
Continue reading… “How Amazon trained its robot Robin to sort packages”