{"ID":2921963,"CreatedAt":"2026-06-02T02:42:49.606572591Z","UpdatedAt":"2026-06-02T04:05:25.881865328Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.00515","arxiv_id":"2606.00515","title":"PaCo-VLA: Passivity-Shielded Compliance Prior for Contact-Rich Vision-Language-Action Manipulation","abstract":"Contact-rich manipulation demands both high-level semantic reasoning and the safe regulation of high-frequency contact dynamics. While Vision-Language-Action (VLA) models provide unprecedented semantic generalization, their low-rate outputs lack the reliability required for direct plant authority in force-sensitive tasks. To bridge this semantic-to-control gap, we introduce PaCo-VLA, a passivity-shielded compliance prior that recasts the VLA interface. Rather than trusting VLAs with direct motor commands, PaCo-VLA treats network outputs as task-level compliance proposals: semantic bindings, task stages, and admittance schedules. A high-frequency, proposal-independent passivity shield governs these proposals through energy-tank accounting and boundary checks, preventing invalid, stale, or unverified model predictions from bypassing low-level contact physics. This decoupled architecture also enables causal evaluation, isolating semantic contributions from geometric shortcuts. Extensive simulated and real-world connector-insertion experiments demonstrate that PaCo-VLA achieves superior precision over unshielded VLA baselines, sustaining zero passivity violations even under adversarial compliance shifts. This framework establishes a provably sampled-passive runtime contract at the admittance port and provides a runtime interface for deploying foundation models in contact-rich domains.","short_abstract":"Contact-rich manipulation demands both high-level semantic reasoning and the safe regulation of high-frequency contact dynamics. While Vision-Language-Action (VLA) models provide unprecedented semantic generalization, their low-rate outputs lack the reliability required for direct plant authority in force-sensitive tas...","url_abs":"https://arxiv.org/abs/2606.00515","url_pdf":"https://arxiv.org/pdf/2606.00515v1","authors":"[\"Haofan Cao\",\"Zhaoyang Li\",\"Zhichao You\",\"Liang Guo\",\"Tianrui Li\"]","published":"2026-05-30T04:06:39Z","proceeding":"cs.RO","tasks":"[\"cs.RO\",\"cs.AI\",\"eess.SY\"]","methods":"[]","has_code":false}