Stability of Active Constraints Enforcement in Sensitive Regions Defined by Point-Clouds for Robotic Surgical Procedures

Robotic minimally invasive surgery provides images from the intraoperative field including organs and sensitive anatomic structures whose protection from non-voluntary destruction is imperative. To assist the surgeon, control methods that discourage motions towards these sensitive areas are advocated in the related literature. In this work, an active constraint controller is proposed and is proved to guarantee that sensitive/forbidden areas defined by a point cloud are never violated by the tool tip while the closed loop system remains passive and its state bounded under the exertion of  a human guiding force. Experimental results are given utilizing  a KUKA LWR4+ kinesthetically guided in a virtual surgical environment.