ProgressVLA: Progress-Guided Diffusion Policy for Vision-Language Robotic Manipulation

• URL: http://arxiv.org/abs/2603.27670v1
• Date: Sun, 29 Mar 2026 12:38:11 GMT
• Title: ProgressVLA: Progress-Guided Diffusion Policy for Vision-Language Robotic Manipulation
• Abstract summary: Most existing vision-language-action (VLA) models for robotic manipulation lack progress awareness.<n>In this work, we investigate the estimation and integration of task progress, proposing a novel model named textbf vla<n>Experiments on the CALVIN and LIBERO benchmarks, alongside real-world robot deployment, consistently demonstrate substantial improvements in success rates.
• Score: 57.07494675832939
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Most existing vision-language-action (VLA) models for robotic manipulation lack progress awareness, typically relying on hand-crafted heuristics for task termination. This limitation is particularly severe in long-horizon tasks involving cascaded sub-goals. In this work, we investigate the estimation and integration of task progress, proposing a novel model named {\textbf \vla}. Our technical contributions are twofold: (1) \emph{robust progress estimation}: We pre-train a progress estimator on large-scale, unsupervised video-text robotic datasets. This estimator achieves a low prediction residual (0.07 on a scale of $[0, 1]$) in simulation and demonstrates zero-shot generalization to unseen real-world samples, and (2) \emph{differentiable progress guidance}: We introduce an inverse dynamics world model that maps predicted action tokens into future latent visual states. These latents are then processed by the progress estimator; by applying a maximal progress regularization, we establish a differentiable pipeline that provides progress-piloted guidance to refine action tokens. Extensive experiments on the CALVIN and LIBERO benchmarks, alongside real-world robot deployment, consistently demonstrate substantial improvements in success rates and generalization over strong baselines.

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