RoboPaint: From Human Demonstration to Any Robot and Any View

• URL: http://arxiv.org/abs/2602.05325v2
• Date: Sat, 07 Feb 2026 02:08:06 GMT
• Title: RoboPaint: From Human Demonstration to Any Robot and Any View
• Abstract summary: We propose a Real-Sim-Real data collection and data editing pipeline to transform human demonstrations into robot-executable, environment-specific training data.<n>We show that retargeted dex-hand trajectories achieve an 84% success rate across 10 diverse object manipulation tasks.<n>We offer a scalable, cost-effective alternative to teleoperation with minimal performance loss for complex dexterous manipulation.
• Score: 9.083647729839688
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Acquiring large-scale, high-fidelity robot demonstration data remains a critical bottleneck for scaling Vision-Language-Action (VLA) models in dexterous manipulation. We propose a Real-Sim-Real data collection and data editing pipeline that transforms human demonstrations into robot-executable, environment-specific training data without direct robot teleoperation. Standardized data collection rooms are built to capture multimodal human demonstrations (synchronized 3 RGB-D videos, 11 RGB videos, 29-DoF glove joint angles, and 14-channel tactile signals). Based on these human demonstrations, we introduce a tactile-aware retargeting method that maps human hand states to robot dex-hand states via geometry and force-guided optimization. Then the retargeted robot trajectories are rendered in a photorealistic Isaac Sim environment to build robot training data. Real world experiments have demonstrated: (1) The retargeted dex-hand trajectories achieve an 84\% success rate across 10 diverse object manipulation tasks. (2) VLA policies (Pi0.5) trained exclusively on our generated data achieve 80\% average success rate on three representative tasks, i.e., pick-and-place, pushing and pouring. To conclude, robot training data can be efficiently "painted" from human demonstrations using our real-sim-real data pipeline. We offer a scalable, cost-effective alternative to teleoperation with minimal performance loss for complex dexterous manipulation.

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