Impedance Matching for Transparency-Optimized Control in Vascular Interventional Robotics

Cardiovascular disease poses a major public health challenge in China, where minimally invasive vascular interventional surgery has been widely adopted due to its short recovery time and reduced trauma. However, such procedures expose physicians to harmful X-ray radiation. Vascular interventional robots offer a solution through master-slave teleoperation, yet most existing systems lack effective force feedback, limiting their precision and safety. This study aims to enhance telepresence in master-slave robotic systems via impedance matching. A two-port network model was established to characterize the force-velocity relationship, and a slave-side impedance model was constructed using finite element simulation and experimental identification. The system integrates bilateral force sensing and a master-side variable impedance module to achieve adaptive impedance matching. Simulations and physical experiments validated the method's effectiveness. Results demonstrate that impedance matching significantly improves force signal transparency: the force RMSE decreased from 0.1141 N to 0.0070 N in simulation, and from 0.82697 N to 0.040608 N in physical experiments. These findings confirm that impedance matching enhances force feedback fidelity and system transparency, thereby improving the safety and efficacy of robot-assisted vascular interventions.