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ETH Zurich uses reinforcement learning to enable WUJI dexterous hand to achieve self-supported locomotion and manipulation

In the paper "Fingers as Legs," the ETH Zurich research team used reinforcement learning to enable the WUJI humanoid dexterous hand to crawl, turn, and recover from falls using its own fingers, without a separate mobility mechanism.

Part of the event: ETH Zurich Uses WUJI Humanoid Hand to Achieve Self-Supporting Walking and Manipulation

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