Mark Van der Merwe – Learning Continuous 3D Reconstructions for Geometrically Aware Grasping

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Faculty mentor: Tucker Hermans

Deep learning has enabled remarkable improvements in robotic grasp synthesis for previously unseen objects from partial object views. However, existing approaches lack the ability to explicitly reason about the full 3D geometry of the object when selecting a grasp, relying on indirect geometric reasoning derived when learning grasp success networks. In this work, we utilize learned reconstructions to explicitly model geometry in a constrained optimization grasp synthesis algorithm.

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Questions or comments? Contact me at: mark.vandermerwe@utah.edu

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