[
    {
        "id": "osp-26344",
        "type": "article-journal",
        "title": "VLPSA: Vision-Language-Poisson-Safe Actions for Full-Body Safety of Learned Policies",
        "author": [
            {
                "family": "Wilkinson",
                "given": "Meg"
            },
            {
                "family": "Fourney",
                "given": "Emily"
            },
            {
                "family": "Burdick",
                "given": "Joel W."
            },
            {
                "family": "Ames",
                "given": "Aaron D."
            }
        ],
        "URL": "https://omanscience.com/en/articles/vlpsa-vision-language-poisson-safe-actions-for-full-body-safety-of-learned-policies",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "abstract": "Vision-language-action (VLA) models enable increasingly general-purpose robotic manipulation, but such learned policies do not provide safety guarantees for collision avoidance---especially in environments outside of training distributions. This work presents Vision-Language-Poisson-Safe Actions (VLPSA), a safety filtering framework that provides full-body safety for VLA policies in cluttered and dynamic environments without retraining. VLPSA synthesizes Poisson Safety Functions (PSF) online from perception data, yielding a Control Barrier Function (CBF) that is enforced through a CBF-QP safety filter over the full body and any grasped object, treated as an extension of the final robot link. To enable real-time deployment while maintaining fine spatial resolution in critical task regions, VLPSA combines dual resolutions of this PSF using Boolean CBF compositions. We evaluate VLPSA on SafeLIBERO against safety-filtering baselines, where it achieves the highest collision avoidance rate among the evaluated methods, increasing collision avoidance from 23.1% for the base $π_{0.5}$ policy to 91.2% while surpassing its task success rate. We further deploy VLPSA on a Franka FR3 in cluttered scenes with dynamic obstacles and human interference, demonstrating real-time full-body safety during manipulation tasks."
    }
]