Hang Su, Jie Zhang, Maoyuan Qu, Xiru Gao, Hongqin Chen, Congyu Hu, Pengfei Song, Xingchen Ji, Yikai Su
Optical coherence tomography (OCT) enables non-invasive volumetric retinal imaging. Conventional tabletop and handheld systems rely on skilled operators and patient cooperation. Mobile robot-assisted OCT (RAOCT) systems can address these challenges, but many depend on complex visual servo modules for low-latency eye tracking. We present an intensity variance-guided 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-time tracking. By calibrating a lookup table between image variance and distance within the near-eye 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-quality optimization. Experiments demonstrated 103.50 μm axial and 20.46 μm lateral tracking accuracy. The pupil-camera response time was 10.53 ms. Automated retinal OCT imaging was achieved, demonstrating the system's potential for point-of-care diagnostics in resource-limited environments.