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Steertuning is introduced, a system that enables robots to learn new tasks in new environments from 5 human demonstrations in under 5 minutes, and achieves a 71% success rate across 12 tasks in 12 new environments, ranging from lab settings to kitchens in new homes.
This work believes Patch Policy provides a pipeline for the robotics community to readily leverage continuing progress in visual representation learning, without sacrificing the training efficiency or inference speed required for high-frequency, reactive control.
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