{"ID":2831038,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.08271","arxiv_id":"2512.08271","title":"Zero-Splat TeleAssist: A Zero-Shot Pose Estimation Framework for Semantic Teleoperation","abstract":"We introduce Zero-Splat TeleAssist, a zero-shot sensor-fusion pipeline that transforms commodity CCTV streams into a shared, 6-DoF world model for multilateral teleoperation. By integrating vision-language segmentation, monocular depth, weighted-PCA pose extraction, and 3D Gaussian Splatting (3DGS), TeleAssist provides every operator with real-time global positions and orientations of multiple robots without fiducials or depth sensors in an interaction-centric teleoperation setup.","short_abstract":"We introduce Zero-Splat TeleAssist, a zero-shot sensor-fusion pipeline that transforms commodity CCTV streams into a shared, 6-DoF world model for multilateral teleoperation. By integrating vision-language segmentation, monocular depth, weighted-PCA pose extraction, and 3D Gaussian Splatting (3DGS), TeleAssist provides...","url_abs":"https://arxiv.org/abs/2512.08271","url_pdf":"https://arxiv.org/pdf/2512.08271v1","authors":"[\"Srijan Dokania\",\"Dharini Raghavan\"]","published":"2025-12-09T05:59:38Z","proceeding":"cs.RO","tasks":"[\"cs.RO\",\"cs.CV\",\"cs.LG\",\"eess.IV\"]","methods":"[]","has_code":false}