Quanta AI Labs

NVIDIA Isaac · Robotics

CHORD

Framework that learns dexterous manipulation from human demos via an object-centric contact-wrench representation (6D force+torque), converting demonstrated contacts into RL rewards; on 1,831 eval tasks it averages 82.12% success (90.77% whole-body from hand-only demos) and ships a 4,739-task benchmark.

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