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Conventional tabletop and handheld systems rely on skilled operators and patient cooperation. Mobile robot\u2010assisted OCT (RAOCT) systems can address these challenges, but many depend on complex visual servo modules for low\u2010latency eye tracking. We present an intensity variance\u2010guided RAOCT system integrated on a wheeled mobile platform. The system uses one depth camera for coarse eye localization and a single pupil camera for real\u2010time tracking. By calibrating a lookup table between image variance and distance within the near\u2010eye region, the pupil camera provides indirect depth estimation for robotic servoing. A motorized reference arm, an electrically tunable lens, and an automated polarization controller further enable image\u2010quality optimization. Experiments demonstrated 103.50 \u03bcm axial and 20.46 \u03bcm lateral tracking accuracy. The pupil\u2010camera response time was 10.53 ms. Automated retinal OCT imaging was achieved, demonstrating the system's potential for point\u2010of\u2010care diagnostics in resource\u2010limited environments.<\/jats:p>","DOI":"10.1002\/jbio.70343","type":"journal-article","created":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T09:14:38Z","timestamp":1787130878000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Intensity Variance\u2010Guided Automated Robotic Optical Coherence Tomography System for Ophthalmic Applications"],"prefix":"10.1002","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2761-5253","authenticated-orcid":false,"given":"Hang","family":"Su","sequence":"first","affiliation":[{"name":"State Key Laboratory of Photonics and Communications, Department of Electronic Engineering Shanghai Jiao Tong University  Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Zhang","sequence":"additional","affiliation":[{"name":"Clairvo (Wuxi) Medical Technology Co. 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