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Orca's unified world latent space enables superior performance in diverse tasks, outperforming specialized models with a single framework.
High-diversity training improves safety in VLA models, but sub-optimal trajectory synthesis still hinders task success.
Current manipulation policies may excel at basic tasks but often fail to transfer learned skills to new contexts, exposing a significant gap in their real-world applicability.
Robots can now learn contact-rich manipulation skills like humans by feeling the forces involved, thanks to a new multimodal interface that captures synchronized visual, tactile, and force data.
Tactile robotic perception gets a boost with a new pretraining method that explicitly encodes force, geometry, and orientation, leading to a 52% reduction in regression error.
