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DRHeC: Differentiable Rendering for Hand-Eye Calibration with RGB-Based Gradients
Accurate hand-eye calibration is crucial for precision manipulation. Traditional methods rely on markers, with their precision dependent on marker accuracy and observability. In contrast, markerless methods, such as learning-based approaches, use deep neural networks to directly extract keypoints or
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