Husnu H. Alabay Tuan Anh Le Hakan Ceylan ^*

• Mayo Clinic Arizona, Scottsdale, United States

In developing medical interventions using untethered milli-and microrobots, ensuring safety and effectiveness relies on robust methods for real-time robot detection, tracking, and precise localization within the body. The inherent non-transparency of human tissues significantly challenges these efforts, as traditional imaging systems like fluoroscopy often lack crucial anatomical details, potentially compromising intervention safety and efficacy. To address this technological gap, in this study, we build a virtual reality environment housing an exact digital replica (digital twin) of the operational workspace and a robot avatar. We synchronize the virtual and real workspaces and continuously send the robot position data derived from the image stream into the digital twin with short average delay time around 20-25 ms. This allows the operator to steer the robot by tracking its avatar within the digital twin with near real-time temporal resolution.We demonstrate the feasibility of this approach with millirobots steered in confined phantoms. Our concept demonstration herein can pave the way for not only improved procedural safety by complementing fluoroscopic guidance with virtual reality enhancement, but also provides a platform for incorporating various additional real-time derivative data, e.g. instantaneous robot velocity, intraoperative physiological data obtained from the patient, e.g., blood flow rate, and preoperative physical simulation models, e.g., periodic body motions, to further refine robot control capacity.