Article

Reproducing Deep Reinforcement Learning Control for In-Hand Object Reorientation with the Revo3 Dexterous Hand

This article reproduces three official pretrained policies for the Revo3 dexterous hand in Isaac Lab for in-hand object reorientation control. The cube random-target reorientation runs 8 times per episode, while the cylinder uses a 22.5° incremental chain, advancing once every 3.4 steps.

Part of the event: Reproduction of Revo3 dexterous hand's three pretrained policies in Isaac Lab

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