A new robot hand provides extremely fast and flexible finger movements, while also being tough enough to survive intense damage. That durability helps the hand, which is already being used in Google DeepMind’s robotics experiments, during the trial-and-error learning required to train artificial intelligence. This latest robotic hand developed by the UK-based Shadow Robot Company can go from fully open to closed within 500 milliseconds and perform a fingertip pinch with up to 10 newtons of force. It can also withstand repeated punishment such as pistons punching the fingers from multiple angles or a person smashing the device with a hammer. The new hand’s robust design is well suited for AI-powered robotics experiments based on reinforcement learning, which allows robots to gradually learn how to interact with environments by fumbling through tasks using trial and error, says Ram Ramamoorthy at the University of Edinburgh in the UK. “Any interaction with the world is a collision damage risk,” said Rich Walker, director of the Shadow Robot Company, during a press conference. One trade-off is that the hand is “heavier than some other options because the design decisions are aimed at reliability over long-term usage”, says Ramamoorthy. The new Shadow Hand’s chunky, three-fingered set-up weighs 4.1 kilograms in total and 1.2 kilograms per finger.
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