Endoscopic endonasal surgery (EES) is a minimally invasive technique for removal of pituitary adenomas or cysts at the skull base. This approach can reduce the invasiveness and recovery time compared to traditional open surgery techniques. However, it represents challenges to surgeons because of the constrained workspace imposed by the nasal cavity and the lack of dexterity with conventional surgical instruments. While robotic surgical systems have been previously proposed for EES, issues concerned with proper interface design still remain. In this paper, we present a cooperative, compact, and versatile bimanual human-robot interface aimed to provide intuitive and safe operation in robot-assisted EES. The proposed interface is attached to a robot arm and holds a multi-degree-of-freedom (DOF) articulated forceps. In order to design the required functionalities in EES, we consider a simplified surgical task scenario, with four basic instrument operations such as positioning, insertion, manipulation, and extraction. The proposed cooperative strategy is based on the combination of force based robot control for tool positioning, a virtual remote-center-of-motion (VRCM) during insertion/extraction tasks, and the use of a serial-link interface for precise and simultaneous control of the position and the orientation of the forceps tip. Virtual workspace constraints and motion scaling are added to provide safe and smooth control of our robotic surgical system. We evaluate the performance and usability of our system considering reachability, object manipulability, and surgical dexterity in an anatomically realistic human head phantom compared to the use of conventional surgical instruments. The results demonstrate that the proposed system can improve the precision, smoothness and safety of the forceps operation during an EES.

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.

Robot-assisted minimally invasive surgery (RMIS) has been shown to be effective in improving surgeon capabilities, providing magnified 3D vision, highly dexterous surgical tools, and intuitive human-robot interfaces for high-precision tool motion control. Robotic surgical tools (RST) are a critical component that defines the performance of an RMIS system. Current RSTs still represent a high cost, with few commercially available options, which limits general access and research on RMIS. We aim to take advantage of recent progress in biocompatible 3D printing and contribute to the development of RMIS technologies, presenting an open platform for low-cost, biocompatible, and customizable RSTs. The proposed design concept consists of a 3-DOF end-effector with a decoupled wrist mechanism, a tool interface module, and a tool drive unit. We validated our end-effector design using Finite Element Analysis (FEA) to confirm that stress generated by high grip forces is maintained below the material yield stress. Validation experiments showed that the proposed RST could provide up to 10N grip forces and up to 3N pulling forces. The proposed control framework exhibited a mean absolute positioning tracking error of approximately 0.1 rad. Finally, we also demonstrated the use of the proposed RST in two surgical training tasks: pick-andplace and stitching. The designs and software control framework are open-access and freely available for customization and fast development at https://github.com/jcolan/OpenRST.

Laparoscopic surgery (LS) is a minimally invasive technique that offers many advantages over traditional open surgery: it reduces trauma, scarring, and shortens recovery time. However, an important limitation is the loss of tactile sensations. Although some progress has been made in robotic-assisted minimally invasive surgery (RMIS) setups, RMIS is still not widely accessible. This review aims to identify which tactile display technologies have been proposed and experimentally validated for the restoration of tactile sensations during conventional laparoscopic surgical tasks. We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We identified relevant articles published over the past 10 years through a search on Web of science, Scopus, IEEE Xplore Digital, and PubMed repositories. A total of 143 articles met the inclusion criteria and 24 were included in the final review. From the reviewed articles, we classified the proposed tactile displays into two categories based on the use of skin contact: (i) skin tactile displays, which include vibrotactile, skin-indentation, and grip-feedback devices, and (ii) non-contact tactile displays based on visualization tools. This survey aims to contribute to further research in the area of tactile displays for laparoscopic surgery by providing a better understanding of the current state of the art and identifying the remaining challenges.

Minimally invasive surgery has undergone significant advancements in recent years, transforming various surgical procedures by minimizing patient trauma, postoperative pain, and recovery time. However, the use of robotic systems in minimally invasive surgery introduces significant challenges related to the control of the robot’s motion and the accuracy of its movements. In particular, the inverse kinematics (IK) problem is critical for robot-assisted minimally invasive surgery (RMIS), where satisfying the remote center of motion (RCM) constraint is essential to prevent tissue damage at the incision point. Several IK strategies have been proposed for RMIS, including classical inverse Jacobian IK and optimization-based approaches. However, these methods have limitations and perform differently depending on the kinematic configuration. To address these challenges, we propose a novel concurrent IK framework that combines the strengths of both approaches and explicitly incorporates RCM constraints and joint limits into the optimization process. In this paper, we present the design and implementation of concurrent inverse kinematics solvers, as well as experimental validation in both simulation and real-world scenarios. Concurrent IK solvers outperform single-method solvers, achieving a 100% solve rate and reducing the IK solving time by up to 85% for an endoscope positioning task and 37% for a tool pose control task. In particular, the combination of an iterative inverse Jacobian method with a hierarchical quadratic programming method showed the highest average solve rate and lowest computation time in real-world experiments. Our results demonstrate that concurrent IK solving provides a novel and effective solution to the constrained IK problem in RMIS applications.