Needle Grasp and Entry Port Selection for Automatic Execution of Suturing Tasks in Robotic Minimally Invasive Surgery

This paper presents algorithms for selection of needle grasp and for selection of entry ports of robotic instruments, for autonomous robotic execution of the minimally invasive surgical suturing task. A critical issue for automatic execution of surgical tasks, such as suturing, is the choice of needle grasp for the robotic system. Inappropriate needle grasp increases operating time requiring multiple regrasps to complete the desired task. In robotic minimally invasive surgery, the entry port that the surgical robot goes through into the patient's body has a significant role on the performance of the robot. Improper entry port affects the robot's dexterity, manipulability and reachability. The proposed methods use manipulability, dexterity and torque metrics for needle grasp selection, and employ needle grasp robustness and target location robustness metrics for port selection. The results of a case study simulation in thoracoscopic surgery is also presented to demonstrate the proposed methods. This paper is motivated by the problem of automating low-level surgical tasks in robotic surgery, such as, suturing, retraction, dissection, and providing exposure. Specifically, this paper focuses on needle grasp and entry port selection for automating robotic surgical suturing. Selection of an appropriate way of grasping a needle is critical for successfully and robustly completing autonomous suturing. To the best authors' knowledge, there are no earlier studies in the literature which focus on the needle grasp selection problem. The proposed approach determines how to grasp the needle by optimizing the surgical system's manipulation performance. The existing approaches in the literature for selecting entry ports for the robotic surgical tools only consider the teleoperated robotic minimally invasive surgery, in which the surgeons directly control the robotic instruments. However, automated performance of suturing introduces additional challenges due to uncertainties in needle localization and grasping. This paper proposes two new performance metrics on selecting port locations from the perspective of autonomously performing surgical suturing, without direct involvement of the human user. This paper also presents preliminary experiments which demonstrate the effectiveness of the proposed methods.