Optimization-Based Constrained Trajectory Generation for Robot-Assisted Stitching in Endonasal Surgery

• Published in: Robotics (Basel) Vol. 10; no. 1; p. 27
• Main Authors: Colan, Jacinto, Nakanishi, Jun, Aoyama, Tadayoshi, Hasegawa, Yasuhisa
• Format: Journal Article
• Language: English
• Published: MDPI AG 01.02.2021
• Subjects: endoscopic endonasal surgery; optimization-based trajectory generation; remote center of motion; robot-assisted suturing; stitching
• ISSN: 2218-6581; 2218-6581
• DOI: 10.3390/robotics10010027

The reduced workspace in endonasal endoscopic surgery (EES) hinders the execution of complex surgical tasks such as suturing. Typically, surgeons need to manipulate non-dexterous long surgical instruments with an endoscopic view that makes it difficult to estimate the distances and angles required for precise suturing motion. Recently, robot-assisted surgical systems have been used in laparoscopic surgery with promising results. Although robotic systems can provide enhanced dexterity, robot-assisted suturing is still highly challenging. In this paper, we propose a robot-assisted stitching method based on an online optimization-based trajectory generation for curved needle stitching and a constrained motion planning framework to ensure safe surgical instrument motion. The needle trajectory is generated online by using a sequential convex optimization algorithm subject to stitching kinematic constraints. The constrained motion planner is designed to reduce surrounding damages to the nasal cavity by setting a remote center of motion over the nostril. A dual concurrent inverse kinematics (IK) solver is proposed to achieve convergence of the solution and optimal time execution, in which two constrained IK methods are performed simultaneously; a task-priority based IK and a nonlinear optimization-based IK. We evaluate the performance of the proposed method in a stitching experiment with our surgical robotic system in a robot-assisted mode and an autonomous mode in comparison to the use of a conventional surgical tool. Our results demonstrate a noticeable improvement in the stitching success ratio in the robot-assisted mode and the shortest completion time for the autonomous mode. In addition, the force interaction with the tissue was highly reduced when using the robotic system.