Robot-Assisted Retraction for Transoral Surgery

Abstract

Tissue retraction is an important task in head and neck surgery to leave space for surgical operations. Because the contact between the retractor and soft tissue is not trivial to model, the retraction operation has not been well addressed by robots in modern robot-assisted surgery. We propose a human-robot collaboration approach to assist the retraction for transoral surgery. The surgeons only need to roughly place the retractors into the oral cavity and specify the recommended retraction force. Robot manipulators will automatically retract the tissues in a safe way. In order to keep the touching force safe, we employ a force-sensing system at the distal end of the retractor. By analyzing the real-time force sensor data, we propose a control strategy which combines active retraction angle compensation and passive torque compensation to adjust the retractor, further reducing potential slippage during the retraction. The proposed method ensures the retraction is adaptive to unknown perturbations of the human anatomy. Our system requires no extra recognition or calibration of the surgical scene or the human tissue models. The approach is validated with two robot manipulators and force-sensing retractors on a physical head phantom as well as a cadaveric experiment. We show that the robots stably retract the mouth under various configurations, where the relative error of the stable retraction force does not exceed 11.8%.