A multimodal RGB-depth fusion backbone with vision transformer, masked-token contrastive learning, and curriculum domain randomization outperforms baselines in simulation and enables zero-shot real-world robot manipulation.
Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks
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Multimodal Fusion for Sim2real Transfer in Visual Reinforcement Learning
A multimodal RGB-depth fusion backbone with vision transformer, masked-token contrastive learning, and curriculum domain randomization outperforms baselines in simulation and enables zero-shot real-world robot manipulation.