AutoDex automates the full perception-execution-labeling-reset loop for real-world dexterous grasping data collection, delivering 4.8x throughput over teleoperation and 76% success for retrieved grasps versus 34% from simulation-only data.
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KPGrasp is a scalable Transformer flow-matching model using 3D hand keypoints that achieves 76.3% success on Dexonomy (47.4% improvement) and best average on DexGrasp Anything without contact losses or test-time refinement.
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AutoDex: An Automated Real-World System for Dexterous Grasping Data Collection
AutoDex automates the full perception-execution-labeling-reset loop for real-world dexterous grasping data collection, delivering 4.8x throughput over teleoperation and 76% success for retrieved grasps versus 34% from simulation-only data.
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KPGrasp: Scalable Keypoint Flow Matching for Dexterous Grasp Generation
KPGrasp is a scalable Transformer flow-matching model using 3D hand keypoints that achieves 76.3% success on Dexonomy (47.4% improvement) and best average on DexGrasp Anything without contact losses or test-time refinement.