PAIR: Proprioception-Aligned Image-Ray Representations for Viewpoint-Robust Manipulation
Overview
This research paper presents PAIR, a framework that aligns joint image-ray representations using robot proprioception to address viewpoint ambiguity in visuomotor policies. By encouraging observations with similar robot states to remain close in representation space across viewpoints, PAIR provides structured grounding for learning viewpoint-robust features. The method is adaptable for training Diffusion Policy or post-training vision-language-action models and demonstrates significant performance improvements over behavior cloning baselines without ray conditioning in both simulated and real-world manipulation benchmarks with camera variation.
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- arXiv Robotics — research abstractsSignalPAIR: Proprioception-Aligned Image-Ray Representations for Viewpoint-Robust Manipulation
This research paper presents PAIR, a framework that aligns joint image-ray representations using robot proprioception to address viewpoint ambiguity in visuomotor policies. By encouraging observations with similar robot states to remain close in representation space across viewpoints, PAIR provides structured grounding for learning viewpoint-robust features. The method is adaptable for training Diffusion Policy or post-training vision-language-action models and demonstrates significant performance improvements over behavior cloning baselines without ray conditioning in both simulated and real-world manipulation benchmarks with camera variation.
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