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Robotic assembly for high-mixture settings requires adaptivity to diverse parts and poses, which is an open challenge.
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Leveraging demonstrations for deep reinforcement learning on robotics problems with sparse rewards
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Assemble Them All: Physics-based planning for generalizable assembly by disassembly
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A brief introduction to path signatures , 2020
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Robot car talk: Introducing Wayve’s new AI model LINGO-1 , 2023
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NIST Manufacturing Objects and Assemblies Dataset (MOAD) , 2023
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