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Researchers at UC Berkeley and Davis train a 16-joint LEAP robotic hand in simulation to manipulate objects. A separate software safeguard reduces drops from 16 to four over 1,200 sequences, though it lowers target-reaching success from 95.2% to 91.5%. The team published these results on arXiv in 2026.
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