A Minimalist Retargeting-Guided Reinforcement Learning Recipe for Dexterous Manipulation
Recent work in humanoid whole-body control has found success with a simple recipe: retarget human motion to robot kinematic references, then train policies via reinforcement learning (RL) to track them. But how does this recipe transfer to dexterous manipulation? The answer is not obvious, as manipulation involves complex, contact-rich dynamics and requires delicate regulation of contact modes and forces. We present REGRIND, a minimalist retargeting-guided RL pipeline that learns dexterous manip
Record details
Published: 13 July 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy
Retrieved: 14 July 2026
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ethics.ai (13 July 2026), “A Minimalist Retargeting-Guided Reinforcement Learning Recipe for Dexterous Manipulation,” evidence record 2, https://ethics.ai/record/2 (originally published by arXiv).
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