Flexible Endoscopic Robot Research Articles

Modeling and Compensation of Stiffness-Dependent Hysteresis for Stiffness-Tunable Tendon-Sheath Mechanism in Flexible Endoscopic Robots

Modeling and Compensation of Stiffness-Dependent Hysteresis for Stiffness-Tunable Tendon-Sheath Mechanism in Flexible Endoscopic Robots

An MRI-Conditional Flexible Endoscopic Robot with a Hydraulic Tendon-Driven Actuation System

This paper presents the conceptualization, mathematical modeling, and experimental validation of a magnetic resonance imaging (MRI)-conditional, flexible endoscopic robot for MRI-guided neurosurgery. The robotic assembly encompasses a straight rigid shaft, a tendon-driven steerable tip with two degrees of freedom, and a compact hybrid actuation system made of nonmagnetic modules. The robot’s small diameter, approximately 3 mm, allows for robot navigation through narrow cavities, such as nasal passages and the densely packed anatomy of the skull base. By filling the robot with deionized water, the MRI contrast of the robot can be improved, therefore enabling intra-operative tracking of the robot’s movement. In this paper, we present the design and fabrication process of the robotic system, kinematic analysis of the robot, and experimental studies to validate our model, characterize the robot, and test the feedback robot control. Furthermore, we demonstrate the MRI compatibility of the robot, along with the intra-operative tracking capability.

A miniature triaxial force sensor based on fiber Bragg gratings for flexible endoscopic robot

Contact force sensing is an important means to ensure the safe operation of surgical robots. This paper presents a miniature triaxial force sensor based on fiber Bragg grating (FBG) for detecting the interaction forces between the tip of flexible endoscopic surgical robots and tissue. The proposed sensor mainly consists of a force-sensitive flexure structure, a support body, and four FBG sensors. A composite hollow structure with a parallel helical slot and elliptical hinge has been utilized to design the force-sensitive flexure with an excellent linear measurement range. The four optical fibers arranged along the circumference of the flexure are configured as a tightly stretched status with their two points fixed. This configuration can improve sensitivity and avoid the drawbacks of FBG chirping and low repeatability. Finite element method-based simulation has been implemented to optimize the flexure’s structural parameters for balancing the force sensor’s axial and radial resolution. The prototyped sensor has been calibrated and achieves a high resolution of 0.77 mN and 0.79 mN for both lateral forces within −1 to 1 N and 1.25 mN for axial force within 0 to 2 N. Loading experiments have been conducted to validate the effectiveness of the proposed designs. The results show that the sensor can provide a high-accuracy measurement of three force components with an average RMS error of less than 3% in the total operating ranges. Such a result validates the feasibility of the designed sensor to measure the robot-tissue interaction forces.

Development of a flexible endoscopic robot with autonomous tracking control ability using machine vision and deep learning

Abstract. A flexible endoscopic robot is designed to solve the problem that it is difficult for auxiliary doctors to maintain a stable visual field in traditional endoscopic surgery. Based on geometric derivation, a motion control method under the constraint of the remote center motion (RCM) of the robot system is established, and a set of circular trajectories are planned for it. The RCM error of the robot during operation and the actual trajectory of the robot end in three-dimensional space are obtained through the motion capture system. The end of the robot is controlled by the heterogeneous primary–secondary teleoperation control algorithm based on position increments. Finally, the RTMDet deep learning object detection algorithm was selected to identify and locate surgical instruments through comparative experiments, and the autonomous tracking control was completed based on visual guidance. In the process of autonomous tracking, the RCM error was less than 1 mm, which met the actual surgical requirements.

Development of a Novel 4-DOF Flexible Endoscopic Robot Using Cable-Driven Multisegment Continuum Mechanisms

Abstract This paper presents the design, analysis, and development of a novel four degrees of freedom (4-DOF) endoscopic robot with cable-driven multisegment flexible continuum mechanisms. The endoscopic robot is mainly composed of the passive positioning arm, cable-pulley system, and 3-DOF flexible continuum mechanism. The forward and inverse kinematics of the endoscopic robot are derived based on the constant curvature assumption, and its working space, flexibility, and preoperative incision determination method are analyzed as well. Based on the hardware structure of the robot system, a control strategy and a control software are developed, and the continuum mechanism is kinematically calibrated to carry out the trajectory planning experiment and simulated surgery experiment. The experimental results show that the calibrated constant curvature model can be used for the motion control of the continuum mechanism, and the 4-DOF endoscopic robot can meet the visual field requirements of minimally invasive surgery.

Accelerated Dual Neural Network Controller for Visual Servoing of Flexible Endoscopic Robot With Tracking Error, Joint Motion, and RCM Constraints

Aiming at the requirements for endoscope in minimally invasive surgery, a dual neural network (DNN) controller is designed for a flexible endoscopic robot (FER) with 10 DOF. First, the FER's kinematics model with remote center of motion (RCM) constraints is established. Then, a quadratic programming control scheme involving the tracking error, joint motion, and RCM constraints of the FER is proposed. A DNN solver of the control scheme, which is activated by the sum of linear and sign-bi-power activation function with adjustable parameters (LSB-AF-AP), is designed, and its convergence rate (CR) and antinoise ability can be improved via adjusting the parameters of LSB-AF-AP. The DNN can converge rapidly in finite time and it is proved by utilizing the Lyapunov theory. Compared with the previous linear AFs applied to the DNN, theoretical analysis indicates that the DNN activated by the LSB-AF-AP has an accelerated CR. Meanwhile, it is proved that the solution obtained by using the designed DNN is the optimal solution of the control scheme. Finally, simulations using the ROS and Gazebo, and an experiment performed on a real FER are conducted. The simulative and experimental results verify that the control scheme can complete the target tracking task well, and the CR and antinoise ability of the algorithm can be further improved via adjusting the parameters of LSB-AF-AP.

Initial clinical experience with a novel flexible endoscopic robot for transanal surgery

BackgroundThe Flex® Robotic System (Medrobotics, Raynham, MA, USA) is the first miniaturised flexible endoscopic robot that aims to allow surgical manoeuvres beyond the area currently reached by transanal endoscopic microsurgery. The aim of this study is to evaluate our initial clinical experience with this novel tool.MethodsWe prospectively collected all consecutive cases of local excisions of rectal lesions performed with the Flex® Robotic System performed at the Department of Surgical Sciences of the University of Turin between October 2018 and December 2019. Indications were benign, or early rectal lesions judged unsuitable for endoscopic removal, within 20 cm of the anal verge. Debriefing meetings after each procedure allowed technology assessment leading to the modification, development, and implementation of tools according to the clinical experience. We analysed the data in terms of the safety and efficacy of treatment.ResultsBetween October 2018 and February 2020, 26 patients were treated. We performed a full-thickness excision in 14 patients and a submucosal dissection in 12. The median operating time was 115 min (range 45–360 min). In six patients (23.1%), we converted to standard transanal endoscopic operation (TEO®) (Karl Storz, Tuttlingen, Germany) to complete the procedure. The 30-day morbidity rate was 11.5% (3/26). Positive resection margins were detected in 4 (15.4%) patients. At a minimum follow-up of 12 months, 2 (7.7%) local recurrences were observed.ConclusionsThis first clinical series demonstrates that the Flex® Robotic System is a fascinating technology that deserves further development to increase surgical dexterity, thereby overcoming current technical limitations and improving clinical outcomes.

Flexible and Deployable Colon Support Structure for Endoluminal Interventions

When performing endoluminal surgery inside the colon using a flexible endoscopic robot, there is a problem of losing visualization and task space due to the collapsing of the surrounding wall. This happens mainly because of the intra-abdominal pressure and peristalsis of the colon. Although insufflation is commonly used for expanding the colon, it does not function when a full-thickness incision is created on the colon wall. To support the collapsing colon and ensure sufficient visualization and task space even with a hole, we developed a deployable colon support structure (CSS) that can be seamlessly adapted to the existing procedures. While the CSS is designed to be small and flexible enough to pass through an endoscopic channel that can be tortuous, it becomes sturdy enough to hold the collapsing/squeezing colon after being deployed. Also, the CSS is collapsible after task completion, for retraction through an endoscopic channel. Through the ex-vivo and in-vivo studies with a swine, we have successfully demonstrated the feasibility of supporting the colon wall during endoluminal interventions with the CSS. We confirmed that the CSS was easily deliverable and deployable and the created space was large enough to perform surgical tasks using robotic arms.

Effect of backlash hysteresis of surgical tool bending joints on task performance in teleoperated flexible endoscopic robot.

The tendon-sheath mechanism provides flexibility but degrades the task performance of the flexible endoscopic robot because of the inherent backlash hysteresis problem. Previous studies have only focused on reducing backlash hysteresis. The goal of this study is to identify the backlash hysteresis criteria of surgical tool bending joints to maintain efficient surgical performance. A test platform for a surgical tool has been developed that has initial backlash hysteresis under 5° and can adjust the backlash hysteresis intentionally. Performance variation has been investigated in three bench-top endoscopic tasks in which various backlash hysteresis conditions were intentionally adjusted. A clear drop-off in task performance has been observed when the backlash hysteresis of the bending joints was greater than 10° regardless of the type of task and link length. The backlash hysteresis of surgical tool bending joints should be reduced to at least 10° to maintain efficient performance in robotic endoscopic surgery.

Deep learning for haptic feedback of flexible endoscopic robot without prior knowledge on sheath configuration

Distal-end force information is usually missing in flexible endoscopic robots due to the difficulties of mounting miniature force sensors on their end-effectors. This hurdle creates big challenges in providing a sense of touch for the operating surgeons. Many existing studies have developed models to calculate the distal-end forces based on the measured proximal-end forces of Tendon-Sheath Mechanisms (TSMs), but these models assume known sheath bending configuration which is unknown during real-life surgeries. This paper presents a two-stage data-driven method that makes dynamic distal-end force prediction of a flexible endoscopic robot without this assumption. In stage one, a convolutional neural network is used to estimate the sheath cumulative bending angle based on the proximal-end force responses of the robot to a probing signal; in stage two, a combination of two long-short-term-memory models pre-trained for the bending angles nearest to the estimated angle (obtained in stage one) makes dynamic estimations of the distal-end force of the robot. The proposed approach overcomes the challenges due to unknown TSM configurations and can robustly identify the correct force hysteresis phases of TSMs. The force prediction is continuous, accurate, and has a mean RMSE of 0.1711 N. This method was validated on an actual flexible surgical robot. In addition, since the proposed approach provides an estimation of the current system cumulative bending angle, it can also be used to facilitate the mathematical modeling methods which require information on the cumulative bending angle.

Eye-in-Hand Visual Servoing of Concentric Tube Robots

This letter deals with the development of a vision-based controller for a continuum robot architecture. More precisely, the controlled robotic structure is based on three-tube concentric tube robot (CTR), an emerging paradigm to design accurate, miniaturized, and flexible endoscopic robots. This approach has grown considerably in the recent years finding applications in numerous surgical disciplines. In contrast to conventional robotic structures, CTR kinematics arise many challenges for an optimal control, such as friction, torsion, shear, and nonlinear constitutive behavior. In fact, in order to ensure efficient and reliable control, in addition to computing an analytical and complete kinematic model, it is also important to close the control loop. To do this, we developed an eye-in-hand visual servoing scheme using a millimeter-sized camera embedded at the robot's tip. Both the kinematic model and the visual servoing controller were successfully validated in simulation with visual servoing platform and using an experimental setup. The obtained results showed satisfactory performances for three-degrees of freedom positioning and path following tasks with adaptive gain control.

軟性内視鏡ロボットに搭載可能な小型ハプティック鉗子ロボットの開発

In recent years, natural orifice transluminal endoscopic surgery (NOTES) using a flexible endoscope is focused on to reduce burden of patients. Since NOTES is difficult for surgeons, flexible endoscopic robots also have been studied and developed. However, conventional robots for NOTES cannot transmit force sensation adequately. The lack of force sensation causes undesired injury. In this paper, a novel haptic forceps robot for NOTES is developed, and force sensation is transmitted by implementing four-channel bilateral control.

Motion compensated controller for a tendon-sheath-driven flexible endoscopic robot

A tendon-sheath system (TSS) has the advantages of being relatively compact in size, flexible and low cost, and therefore is favoured in building flexible endoscopic robots to pass through long and tortuous human lumen. TSS, however, is prone to nonlinear behaviors such as backlash, hysteresis and direction dependent properties. A compensation technique is required to improve its positioning performance. Tension and elongation models of TSS are analyzed. A feedforward motion compensation controller is designed to compensate the asymmetric backlash behavior of the TSS in real time. Motion tracking experiments were conducted on a TSS driven two DOFs continuum manipulator. The results showed that using the proposed compensation methods, tracking error can be reduced by 74%. The proposed compensation method is useful for controlling flexible continuum robots, which are anticipated to have emerging roles in assisting surgeons to perform the increasingly technically challenging endoscopic procedures. Copyright © 2016 John Wiley & Sons, Ltd.