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Achieving a 37% improvement in success rates for dexterous manipulation tasks, DexPIE redefines the role of real-world experience in policy training.
Achieving state-of-the-art results in pose estimation, this method leverages symmetry-aware features to simplify the complexities of rotation learning in a non-linear space.
Zero-shot robotic manipulation gets a boost: BLaDA grounds open-vocabulary instructions in 3D Gaussian Splatting fields, enabling robots to perform complex dexterous tasks without predefined affordance labels.
