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Object-agnostic grasp planning can achieve state-of-the-art performance without the need for object-specific training data, revolutionizing how robots learn to manipulate diverse objects.
Achieving state-of-the-art grasp synthesis without the need for expensive, object-annotated datasets could revolutionize dexterous manipulation in robotics.