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Robots can pick up boxes, sort packages, and screw in bolts without breaking a sweat. Some of them can even walk and run like humans. Hand one a floppy, slippery piece of raw salmon, though, and everything starts falling apart.
A team at the Norwegian University of Science and technologies set out to solve that problem. The result is the Sashimi-Bot, a three-armed robot that can prepare sashimi from a raw salmon loin without a chef in sight.
It divides the job neatly between its three arms. The first arm stabilizes and positions the salmon on the cutting board. The second holds a chef’s knife and slices. The third picks up each finished slice with chopsticks and transfers it to a serving tray.
What makes this more than just clever arm arrangement is how the robot learned to do it. Lead researcher Sverre Herland and the team trained it using deep reinforcement learning inside a virtual simulation.
The technologies let the robot practice thousands of movements and learn through trial and error, without any practice on real fish.
The knife arm also carries a GelSight tactile sensor, a soft gel surface with an embedded camera that tells the robot exactly when it has reached the cutting board.
During testing, the robot cut 34 slices of salmon. It successfully grasped 26 of the 28 slices that fell onto the cutting board with chopsticks. An additional six slices that had stuck to the knife blade were retrieved directly from it.
Each cut cycle averaged 27.9 seconds. The study is published in npj Robotics (via TechXplore). While most robots do best with rigid, predictable objects, the Sashimi-Bot is more significant than its culinary application suggests.
It is an example of robots handling delicate, irregular materials by making real-time movements and adjustments.