Inspired by the human hand, this work presents a hybrid soft-rigid architecture for a robotic palm to enhance dexterity and robustness. While soft-robotic hands often lack the structural integrity to handle heavy objects, classical rigid designs are sensitive to impacts and frequ…
Advances in learning-based robotic manipulation, such as Vision-Language-Action (VLA) models and Video Action Models (VAMs), heavily rely on high-quality teleoperation data. Their capabilities are strictly upper-bounded by the quality of the underlying human demonstrations. Curre…
Action-conditioned world models allow robots to predict the future consequences of candidate actions without additional physical interaction, supporting policy evaluation, planning, and data augmentation. We present Mask2Real-WM, a two-stage action-conditioned world model for dex…