What if robotic hands could learn complex maneuvers purely in simulation and work perfectly in reality? ByteDance Seed just unveiled a breakthrough. Their new RL framework bridges the sim-to-real gap for dexterous hands with a fast virtual tactile simulation, current-to-torque calibration (no extra sensors!), and actuator dynamics modeling with randomization to cover real-world quirks. Result? Policies trained 100% in simulation directly enable a five-finger hand to perform precise, controllable grasp force tracking and object reorientation – a first for zero-shot sim-to-real multi-finger manipulation! Closing the Reality Gap: Zero-Shot Sim-to-Real Deployment for Dexterous Force-Based Grasping and Manipulation Paper: arxiv.org/abs/2601.02778 Project: dexmanip-seed.github.io/dexm… Our report: mp.weixin.qq.com/s/7TQC0sJfw… 📬 #PapersAccepted by Jiqizhixin

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