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A Sim-to-Real Integration Pipeline for Training and Deployment of Chunk-Based VLA Manipulation Policies

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

Vision-Language-Action (VLA) models have become a prominent paradigm for mapping multimodal inputs, including semantic instructions, visual observations of the scene, and proprioceptive observations, to robot actions. Most state-of-the-art models predict actions in the end-effector pose space as sequences of action chunks. Training and evaluating these models requires large-scale collections of real-world demonstrations, pairing robot actions with the corresponding visual and proprioceptive observations. Collecting such data on real hardware typically relies on human teleoperation, making the

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