Augmentron: Scalable Multi-View Visual Augmentation for Robot Learning
Overview
This research introduces Augmentron, a geometry-aware pipeline that generates reusable scene representations and renders them through recorded camera poses to produce temporally and multi-view consistent environment variations while preserving robot, task objects, actions, and annotations. Replacing half of the real-world training dataset with Augmentron data improves model success across three physical manipulation tasks for both out-of-distribution distractor objects and workspace variation evaluations. In comparisons against alternate augmentation techniques, Augmentron achieves the highest pooled success in all three conditions, demonstrating that introducing augmented data to a training recipe helps policies generalize to dynamic real-world settings.
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- arXiv Robotics — research abstractsSignalAugmentron: Scalable Multi-View Visual Augmentation for Robot Learning
This research introduces Augmentron, a geometry-aware pipeline that generates reusable scene representations and renders them through recorded camera poses to produce temporally and multi-view consistent environment variations while preserving robot, task objects, actions, and annotations. Replacing half of the real-world training dataset with Augmentron data improves model success across three physical manipulation tasks for both out-of-distribution distractor objects and workspace variation evaluations. In comparisons against alternate augmentation techniques, Augmentron achieves the highest pooled success in all three conditions, demonstrating that introducing augmented data to a training recipe helps policies generalize to dynamic real-world settings.
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