OBJECTIVE: Inadequate visual and force feedback while navigating surgical tools elevate the risk of endovascular procedures. It also poses occupational hazard due to repeated exposure to X-rays. A teleoperated robotic system that augments surgeon's actions is a solution. METHOD: We have designed and developed an endovascular robotic system that augments surgeon's actions using conventional surgical tools, as well as generates feedback in order to ensure safety during the procedure. The reaction force from vasculature is estimated from motor current that drives the surgical tool. Calibration required for force estimation is based on bilevel optimization. Input shaping is used in conjunction with a cascaded controller to avoid large responses due to faster inputs and to track tool position. The design, realization, and testing of our system are presented. RESULTS: The responses of the system in comparison with the dynamics model is similar vis-à-vis the same input commands. Any error in the position tracking is reduced by the cascaded controller. Phase-portrait analysis of the system showed that the system is stable. The reaction force estimation is validated against load cell measurements. The safety mechanism in the events of excessive reaction forces while interacting with vasculature is demonstrated. CONCLUSION AND SIGNIFICANCE: Our system is a step toward intelligent robots that can assist surgeons during endovascular procedures by monitoring and alerting the surgeons regarding detrimental parameters. It arrests any unintended excursions of the surgical tools or surgeon's actions. This will also eliminate the need for surgeons to be in radiation environment.
OBJECTIVE: Inadequate visual and force feedback while navigating surgical tools elevate the risk of endovascular procedures. It also poses occupational hazard due to repeated exposure to X-rays. A teleoperated robotic system that augments surgeon's actions is a solution. METHOD: We have designed and developed an endovascular robotic system that augments surgeon's actions using conventional surgical tools, as well as generates feedback in order to ensure safety during the procedure. The reaction force from vasculature is estimated from motor current that drives the surgical tool. Calibration required for force estimation is based on bilevel optimization. Input shaping is used in conjunction with a cascaded controller to avoid large responses due to faster inputs and to track tool position. The design, realization, and testing of our system are presented. RESULTS: The responses of the system in comparison with the dynamics model is similar vis-à-vis the same input commands. Any error in the position tracking is reduced by the cascaded controller. Phase-portrait analysis of the system showed that the system is stable. The reaction force estimation is validated against load cell measurements. The safety mechanism in the events of excessive reaction forces while interacting with vasculature is demonstrated. CONCLUSION AND SIGNIFICANCE: Our system is a step toward intelligent robots that can assist surgeons during endovascular procedures by monitoring and alerting the surgeons regarding detrimental parameters. It arrests any unintended excursions of the surgical tools or surgeon's actions. This will also eliminate the need for surgeons to be in radiation environment.