Towards A Generic In Vivo In Situ Camera Lens Cleaning Module for Laparoscopic Surgery This paper proposes a generic cleaning module to address lens fogging and soiling problems for insertable robotic cameras in laparoscopic surgery. The proposed lens cleaning module features minimal intraoperative interruption for surgeons to maintain clear visual field. The technical challenges for developing such a compact modular design involve confining the wiping mechanism within small space, yet delivering sufficient energy for the lens cleaning task. Inspired by thermoactivated phase transformation of shape memory alloy, we develop an effective mesoscale actuation mechanism to overcome the design challenges. A prototype is designed and manufactured for performance evaluation. The design effectiveness was verified by experiments.

Development of a Novel Handeye Coordination Algorithm for Robot Assisted Minimally Invasive Surgery * The minimally invasive surgical robot greatly improved surgical OR efficiency, and surgeon manipulates the surgical instruments through masterslave control under the guidance of laparoscope vision. As a mapping of the surgeonu0027s handeye coordination, the coordination between surgical instruments and laparoscope has an important impact on the surgical efficiency and the ergonomics. In this paper, a novel handeye coordination algorithm is proposed for the robot assisted minimally invasive surgery (RMIS). Firstly, a novel cascadecalibration (CC) algorithm structure is proposed to determine the pose relationship between the robot laparoscope arm coordinate system and the robot instruments arm coordinate system. A handeye coordination algorithm is also proposed, which provides accurate masterslave control and improves the surgical operation room (OR) efficiency. We validate the proposed algorithm through two experiments with our minimally invasive surgical robot system. Our experiments demonstrate that the proposed method is competitively effective to induce the handeye coordination for the RMIS.