DexSim2Real integrates FM-guided domain randomization, cross-attention visuo-tactile RL policies, and LLM-based progressive curricula to reach 78.2% average real-world success on six dexterous tasks with an 8.3% sim-to-real gap.
In: Conference on Robot Learning (CoRL)
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DexSim2Real: Foundation Model-Guided Sim-to-Real Transfer for Generalizable Dexterous Manipulation
DexSim2Real integrates FM-guided domain randomization, cross-attention visuo-tactile RL policies, and LLM-based progressive curricula to reach 78.2% average real-world success on six dexterous tasks with an 8.3% sim-to-real gap.