Magnetic compression anastomosis (MCA) offers a promising solution for minimally invasive anastomosis surgery. However, current MCA schemes lack safe, real-time localization and guidance for compression magnets, hindering surgeons' ability to control the compression magnets effectively in complex, unstructured endoluminal environments. To address these limitations, this paper introduces the MagsL-HUD endoscopic system, a novel solution that enables multi-magnetic six-degree-of-freedom (six-DoF) localization and head-up display (HUD) guidance within the endoscopic view (EV). Specifically, the system integrates a developed Endo-MagCap device with an orthogonal magnet configuration, along with a magnetic sensor array, to achieve real-time full-pose localization. An endoscopic camera model is incorporated for HUD visualization, enhancing intuitive interaction for surgeons' better-informed decisions. Eventually, the effectiveness of the MagsL-HUD endoscopic system is validated through laboratory experiments andex vivoanimal trials. The system demonstrates six-DoF tracking accuracy with average errors of 0.0070 m and 0.1437 rad, and 0.0071 m and 0.1721 rad in the designed trajectory cases for two compression magnets, respectively. Additionally,ex vivoporcine tests confirm the system's feasibility and applicability, successfully performing a stomach-colon MCA surgery with a final compression gap of approximately 0.00247 m. Further comparative studies demonstrate that the MagsL-HUD method has a compression success rate of 71.4$\%$versus 42.9$\%$of the non-HUD approaches in the designed tests. This work represents a significant step toward the clinical adoption of magnetic-assisted endoscopy for minimally invasive anastomosis surgeries, holding substantial practical significance for improving the safety and efficacy of MCA procedures in complex, unstructured endoluminal environments.

Endoscopic submucosal dissection (ESD) is a procedure targeted for early gastrointestinal cancer. Traction plays a crucial role in enhancing the efficiency of cutting lesions, thereby reducing procedural complexity and duration. From the perspective of traction devices, current non-magnetic ones hold shortcomings in complicating the workspace in directional tissue manipulation; Current magnetic traction devices cannot be prepared before the procedure, and require the withdrawal of endoscope in the midway to re-introduce the magnetic retractor to the lesion site. Towards these plights, this paper introduces a robotic flexible magnetic retractor designed for tissue manipulation during ESD. Precisely, the flexible prototype can be seamlessly inserted through the instrument channel of an endoscope to the lesion site without the need for endoscope withdrawal. Moreover, the introduction of robotic magnetic actuation enhances the agile control of magnetic retractors while alleviating the surgeon's workload in magnetic-retractor-assisted ESD. The experimental results validate the functionality and efficacy of the prototype magnetic retractor in magnetic traction-assisted ESD procedures. The retractor demonstrated its ability to provide adequate traction and accomplish clinical tasks. This innovative approach holds promise for enhancing the efficiency and outcomes of ESD procedures, offering a compelling alternative to traditional traction methods.

Magnetically actuated capsule endoscopic robots (MACERs) are becoming increasingly popular because they can reach deep diseased regions inside the body that are difficult or inaccessible to traditional endoscopes without the restriction of mechanical transmission medium. However, MACERs are highly nonlinear, hence achieving obstacle avoidance, safe, and stable target tracking control of MACERs remains a challenging research topic. Therefore, to satisfy the diagnosis and treatment needs of the deep diseased regions inside the body, this paper designs a MACER target tracking neural network control method with obstacle avoidance and noise-resistant capabilities. Firstly, the kinematics and obstacle avoidance model of the MACER are established, and then a moving target tracking control scheme of robot with joint motion constraints and obstacle avoidance capabilities is designed. Next, a noise-resistant neural network is designed to quickly solve the MACER’s control scheme, thereby achieving safe, obstacle avoidance, and stable target tracking control of the MACER. Finally, the effectiveness and practicability of the proposed method are checked by simulation analysis and experiment on MACER, and compared with the existing methods. The experimental results indicate that the neural network method proposed can effectively control the MACER to track the target motion along the gastric wall curve. Compared with existing methods, the designed method has stronger anti-noise interference ability, the convergence accuracy of the proposed method is improved by 1.3 times, and the computational burden is reduced by 26.7 times.

In robotic teleoperation systems, the effectiveness of teleoperation relies heavily on the operator performing control actions, underscoring the importance of master device design. Breaking away from the mechanical framework that relies on complex structures and restricts workspace, this paper adopts a new magnetic method and introduces a wireless magnetic master device (MMD) with an expandable, singularity-free workspace, designed to enhance maneuverability and operational reach. Specifically, the concept and development of the MMD for robotic teleoperation are presented, followed by an exploration of key technical aspects, including a six-degree-of-freedom (DoF) tracking approach using dual magnetic localization and controller design for the robotic arm using the MMD. Finally, the proposed method’s feasibility and accuracy are validated through magnetic localization and teleoperation control tests. Results indicate that the MMD achieves six-DoF localization with an average Euclidean localization error ofet= 0.0018 m and an average Geodesic distance error ofeR= 0.0604 rad within the central region of the workspace, and six-DoF manipulation (velocityet= 0.0062 m andeR=0.2091 rad in tests. Furthermore, the overall teleoperation control framework achieves tracking accuracy withet= 0.0085 m andeR= 0.1475 rad in robotic calligraphy task; achieves a broad scanning range of 0.2746 m along they-axis in robotic ultrasound scanning task; achieves a large-angle rotation of 9.15 rad in robotic clamp rotating task. Overall, this research advances master device design, aiming to inspire further innovation in master-follower teleoperation control for human-machine systems.

In minimally invasive surgery (MIS), the field of view (FOV) control is crucial. Autonomous endoscope robots have been developed to facilitate MIS procedures by enabling autonomous surgical target tracking, thus reducing the workload on surgeons. However, existing visual servoing-based target tracking methods for autonomous endoscopes often overlook the insecurity stemming from restricted workspace conditions. Instances, such as collisions between the endoscope robot’s tip and the patient’s chest or abdominal wall pose risks to patient tissue, while extensive motion of the endoscope shaft may damage incision port tissue. Addressing these security concerns, this article proposes a novel approach called virtual fixture-based restricted workspace constraint (RWSC) to reconstruct the endoscope robot’s movement range. A quadratic programming (QP) optimization framework is employed to govern the robot’s motion, ensuring autonomous target tracking while adhering to RWSCs. To solve the QP problem, we propose an adaptive zeroing neural network (ZNN) featuring a newly designed activation function (AF). This AF enhances the ZNN with predefined-time convergence and noise rejection capabilities, making it especially suitable for time-sensitive and noise-prone surgical applications. Theoretical analysis and experimental results demonstrate that our adaptive ZNN achieves shorter convergence times than existing neural dynamic-based QP solvers. Physical validations show the efficacy of the proposed RWSCs in limiting the workspace of the endoscope robot, while the FOV control strategy enables autonomous target tracking of flexible endoscopes under diverse constraints and objectives.

In response to torso-oriented magnetic localization tasks that require the system to have interactivity and flexibility with guaranteed accuracy, a novel bio-inspired magnetic sensor array configuration is proposed in this paper. Precisely, the ideas of the natural characteristics of octopus flexible tentacles and the "wrap" morphology are integrated into the design of the magnetic localization system based on the sensor array method. It is worth mentioning that such a design enhances the interactivity and flexibility of the localization system compared to the general planar sensor array strategy. Apart from the concept introduction, the geometry analysis of the proposed configuration is presented based on the constant curvature model. Besides, the magnetic localization algorithm for the system is presented by constructing a magnetic tracking optimization function. Eventually, the proposed concept and developed algorithm are examined in the sensor-array-simulation environment to manifest their effectiveness and applicability. The experimental results indicate that the octopus-inspired-configuration sensor array achieves a mean accuracy at a centimeter-level in our cases, and has better accuracy with a mean value of ē as 0.0178 m and ${\overline {SQR} _{ave{\text{ }}}}$ as 0.0883 for the center interest space compared to general planar configuration one. Moreover, the effect of the configuration error is analyzed. These results verify the feasibility and superiority of the proposed concept and hold significant practical significance in addressing the challenge associated with magnetic localization tasks toward the clinical application scenarios.

Manual rigid endoscopes have defects such as a low efficiency, difficult operation, and safety risks, and the antinoise interference ability, convergence speed, and control accuracy of the neural network control technology for the existing autonomous endoscopes are often ignored. Solving these problems is important for the stable operation of endoscopes. Therefore, a new adaptive fast convergent antinoise dual neural network (AFA-DNN) controller for the visual servo control of ten-degree of freedom flexible endoscope robots (FERs) with physical constraints is proposed in this work. First, the control scheme of the FERs is formulated as a quadratic programming problem, and then, an AFA-DNN visual servo controller is designed for the FERs. The adaptive gains of the controller can accelerate the convergence, improve the antinoise ability, and increase the convergence accuracy of the controller. Then, according to the Lyapunov theory, the fast convergence of the AFA-DNN in finite time is proven for both noise-free and noisy conditions. The experimental results indicate that the FER controlled by the proposed AFA-DNN can accurately track various trajectories and that the AFA-DNN has a better antinoise interference ability, higher convergence accuracy, and faster convergence speed than conventional methods. The convergence speed of the AFA-DNN is increased by a factor of 4.22 by using the adaptive gains. Experiments also indicate that the AFA-DNN remains well functioning under various noise disturbances (such as constant, periodic, linear, and Gaussian noise).

This paper is concerned with the issue of the kinematic model-based bending control for the magnetically actuated robotic endoscope and its application for automatic retroflexion. By the utilization of the Cosserat rod theory and the transformation in the magnetic tip of the endoscope, the comprehensive kinematic model of the magnetically-actuated robotic endoscope is established. Afterward, a magnetic control scheme for the bending motion is proposed by co-developing an error feedback PID control strategy and the model-based feedback approach. Moreover, as one unique kind of bending motion, retroflexion is taken into account, and the strategy aimed at the bid of compact space retroflexion is presented by virtue of the introduction of serial waypoints pursuing the position of the magnetic tip being close to the midline as possible. Eventually, the developed modeling and bending control scheme and the compact space retroflexion strategy are examined in a magnetically actuated robotic endoscope system to manifest the effectiveness and applicability of the theoretical approach. The experimental results indicate that the designed controller can drive the endoscope to bend to the desired pose and show a reduction of about 47.01% in the sweeping area and 79.25% in the last distance to midline achieved by conducting compact space retroflexion in comparison to “U” type one.

Characteristics of wireless manipulation based on permanent magnet coupling, including anchoring distance, panning torque, and translational force, are assessed in this paper. The study focuses on a typical scenario where a slave robot embedded with a small permanent magnet can be remotely controlled within a constrained area by a master large permanent magnet placed outside the environment at a certain distance from it. The key parameters (force and torque) acting on the slave robot are quantified and evaluated. In this article, several combinations of permanent magnets with various dimensions and configurations are studied using finite element methods. Based on the obtained results, we create a lookup table for each parameter, serving as a guideline to help interested researchers choose suitable magnetic combinations for their applications.

Generally, the infinity-norm joint-velocity minimization (INVM) of physically constrained kinematically redundant robots can be formulated as time-variant linear programming (TVLP) with equality and inequality constraints. Zeroing neural network (ZNN) is an effective neural method for solving equality-constrained TVLP. For inequality-constrained TVLP, however, existing ZNNs become incompetent due to the lack of relevant derivative information and the inability to handle inequality constraints. Currently, there is no capable ZNN in the literature that has achieved the INVM of redundant robots under joint limits. To fill this gap, a classical INVM scheme is first introduced in this article. Then, a new joint-limit handling technique is proposed and employed to convert the INVM scheme into a unified TVLP with full derivative information. By using a perturbed Fisher-Burmeister function, the TVLP is further converted into a nonlinear equation. These conversion techniques lay a foundation for the success of designing a capable ZNN. To solve the nonlinear equation and the TVLP, a novel continuous-time ZNN (CTZNN) is designed and its corresponding discrete-time ZNN (DTZNN) is established using an extrapolated backward differentiation formula. Theoretical analysis is rigorously conducted to prove the convergence of the neural approach. Numerical studies are performed by comparing the DTZNN solver and the state-of-the-art (SOTA) linear programming (LP) solvers. Comparative results show that the DTZNN consumes the least computing time and can be a powerful alternative to the SOTA solvers. The DTZNN and the INVM scheme are finally applied to control two kinematically redundant robots. Both simulative and experimental results show that the robots successfully accomplish user-specified path-tracking tasks, verifying the effectiveness and practicability of the proposed neural approach and the INVM scheme equipped with the new joint-limit handling technique.

To solve the problems of discomfort and potential colon perforations of patients that arise when standard colonoscopes are used for colonoscopy, an electromagnetically actuated soft-tethered colonoscope robot (EASCR) is here introduced. Owing to EASCRs’ highly nonlinear and complex application environments, the hybrid vision/magnetic-force tracking control for these types of robots remains a challenging research issue, and the lack of current constraints may also give rise to safety concerns. Therefore, a hybrid vision/magnetic-force fast convergent dual neural network (DNN) tracking controller for an EASCR with current constraints is developed to alleviate patient discomfort and ensure the safe and smooth progression of colonoscopy. First, EASCR motion/vision and electromagnetically actuated force nonlinear coupling models are established, and a quadratic programming visual servo-tracking control scheme with current constraints is designed. Second, a novel DNN solver for the nonlinear control scheme is developed, and its convergence in finite time is strictly proved. The results of simulations and experiments indicate that the designed control method can well control EASCRs with current constraints to achieve tracking tasks, and it has a stronger anti-disturbance ability, faster convergence, and higher convergence accuracy than existing methods.

This paper presents a long-range magnetic actuated and guided endoscope for uniport video-assisted thoracic surgery (VATS). In VATS, the incision is quite narrow and part of the chest wall may be very thick. So, the magnetic endoscope system is required to produce sufficient attractive force at a considerable distance with a compact dimension. In this paper, a magnetic endoscope system is developed to meet the aforementioned clinical demands. In the system, both the internal and external units consist of two cylindrical magnets at both ends and a semi-cylindrical magnet in the middle. Coupled with the magnetic field from the external unit, the internal endoscope can achieve anchoring, tilting, panning, and translating to provide the desired view for the surgeon. The rotation of the endoscope is dynamically modeled by combining magnetic theory and coordinate transformation. The prototype is made with a boundary box of 10×14×56 mm, which can be inserted through the narrow incision in VATS. In the experiment, the developed models of anchoring, tilting, and panning were verified. The magnet configuration in the system can achieve a static anchoring distance of 95 mm and exhibits enhancement in attractive force compared with other designs.

The use of magnetic fields and field gradients to move magnetic material and devices within the human body has a surprisingly long history. Over the past two decades, there has been renewed interest in this area with the growth of magnetic medical microrobots. In this article, we focus on the state-of-the-art and future directions for magnetically actuated medical robots from anin vivoperspective. We initially review the history and relevant physics followed by a discussion on the limitedin vivoresearch efforts that investigate magnetically guided devices. Our focus is on magnetically guided tethered probes, untethered devices (microrobots and nanorobots), and magnetic navigation systems that have been or could be utilizedin vivoto provide increased control and safety for the physician and patient.

After years of development, various swarms of robots have been proposed for many complicated tasks, such as forming patterns, cooperative locomotion, and adapting to different environments. However, controlling microrobotic swarms is still a challenging task owing to the lacking of integrated devices on the small-scale agents, and actuation of multiple microrobotic swarms to different targets under the same global input will be even more difficult. In this work, we present a swarm of nickel nanorods and its diverse locomotion velocity compared with Fe3O4nanoparticle swarms is implemented for actuating the two swarms to different targets under the same customized oscillating magnetic field. The effects of the magnetic anisotropy of agents on the macroscopic swarm behaviour are analysed theoretically. To prove the strategy, the speeds of the two swarms were characterized through experiments, and demonstrations were conducted to show the capability of driving the two swarms to different locations in the same environment. Furthermore, parallel locomotion of the two swarms towards opposite directions was also achieved on a tilted substrate. This work has proved the feasibility of simultaneously actuating two swarms to diverse targets and promoted fundamental understandings of microrobotic swarms.

Colorectal cancer incidence has been steadily rising worldwide. Magnetic colonoscopes provide new approaches to conduct colon inspection and treatment. This paper presents a novel electromagnetically actuated soft-tethered colonoscope to achieve precise and stable orientation control. An inflated balloon is designed to eliminate the unpredictable disturbance of the floating tether. A 2OR Pseudo-Rigid-Body (PRB) model of the soft tether is developed to analyze the relationship between the tether deflection and applied force and torque. A closed-loop control framework is constructed with visual position feedback. Experiments are first conducted to validate the assumption of the PRB model and the efficacy of the magnetic field model. Then, trajectory tracking tasks and disturbance rejection tests are performed to validate the feasibility of the proposed solution and closed-loop control. Results show that the colonoscope can stably and accurately orient to the desired orientation with an absolute mean position error of less than 0.5 mm and an average velocity of 3.5 mm/s. The distal tip can quickly re-stabilize to the desired orientation even when a large disturbance exists.

Crawling through various terrains has been a long research interest. In recent years, quite a number of soft crawling robots have been developed. However, locomoting in an elastic, humid, and slippery environment remains a challenge. In nature, gastropods, such as snails, live in humid environment and could crawl through all kinds of surface conditions by using wet adhesion. In the wet adhesive locomotion, the mucus is crucial in adhering the gastropod while allowing forward motion. Previously, we presented one snail-like soft robot that mimics the gastropods. In this work, we propose a second version and present a theoretical model of the mucus simulant. In addition, the dynamic model of the soft robot’s wet adhesive locomotion is developed for the first time. Results show that the speed of the current version is 5 times than that of the previous one through the optimization of design. Also shown by the results that the mucus helps to speed up the robot by at least 2.7 times.

In this paper, we proposed an autonomous robotic flexible endoscope system for the laparoscopic bariatric surgery (LBS). This system comprises a UR5 robot and a flexible endoscope equipped with a novel continuum joint, named reinforced double helix continuum mechanism. Compared with the simple helix structure, the compressional and torsional stiffness of the proposed joint are improved significantly. To automate the robotic flexible endoscope, image-based visual servoing technique is employed. A deep learning algorithm named TernausNet-16 is improved and incorporated into the control framework to detect surgical instruments inside the camera view. The experimental studies verified the effectiveness and feasibility of the robotic flexible endoscope system for the visual serviong control scheme assisted by deep learning methods.

A flexible endoscope introduces more dexterity to the image capturing in endoscopic surgery. However, manual control or automatic control based on instrument tracking does not handle the misorientation between the endoscopic video and the surgeon. We propose an automatic flexible endoscope control method that tracks the surgeon's head with respect to the object in the surgical scene. The robotic flexible endoscope is actuated so that it captures the surgical scene from the same perspective as the surgeon. The surgeon wears a head-mounted display to observe the endoscopic video. The frustum of the flexible endoscope is rendered as an augmented reality overlay to provide surgical guidance. We developed the prototype, FlexiVision, integrating a 6-DOF robotic flexible endoscope based on the da Vinci Research Kit and Microsoft HoloLens. We evaluated the proposed automatic control method via a lesion observation task, and evaluated the AR surgical guidance in a lesion targeting task. The multi-user study results demonstrated that, for both tasks, FlexiVision significantly reduced the completion time (by 59% and 58%), number of errors (by 75% and 95%) and subjective task load level. With FlexiVision, the flexible endoscope could act as the surgeon's eyes teleported into the abdominal cavity of the patient.

This article designs and analyzes a recurrent neural network (RNN) for the visual servoing of a flexible surgical endoscope. The flexible surgical endoscope is based on a commercially available UR5 robot with a flexible endoscope attached as an end-effector. Most of the existing visual servo control frameworks of the robotic endoscopes or robot arms have not considered either the physical limits of the robot or the remote center of motion (RCM) constraints (i.e., the fulcrum effect). To tackle this issue, this article first conducts the kinematic modeling of the flexible robotic endoscope to achieve automation by visual servo control. The kinematic modeling results in a quadratic programming (QP) framework with physical limits and RCM constraints involved, making the UR5 robot applicable to surgical field. To solve the QP problem and accomplish the visual task, an RNN activated by a sign-bi-power activation function (AF) is proposed. The motivation of using the sign-bi-power AF is to enable the RNN to exhibit an accelerated finite-time convergence, which is more preferred in time-critical applications. Theoretically, the finite-time convergence of the RNN is rigorously proved using the Lyapunov theory. Compared with the previous AFs applied to the RNN, theoretical analysis shows that the RNN activated by the sign-bi-power AF delivers an accelerated convergence speed. Comparative validations are performed, showing that the proposed finite-time convergent neural network is effective to achieve visual servoing of the flexible endoscope with physical limits and RCM constraints handled simultaneously.

This paper presents a novel magnetic anchored and steered camera robot intended for minimally invasive surgery (MIS), particularly for single port access (SPA) surgery. The design aims to achieve both compactness and a planar pan/tilt workspace (instead of hemispheric) to lower robot footprint in vertical space. Robot comprises two 6mm×6mm diametrically magnetized internal permanent magnets (IPMs) fixed at either ends of a small cylindrical capsule, with camera module and a 45°mirror capped inside capsule. As such, camera view orientation can be steered in 2-DOF across range of 180° tilt and 360° panning, all within a planar workspace close to surface of anchor. Using only two small IPMs for all necessary functions (anchoring, translation along intra-abdominal surface, and steering) reduces bulk and length of robot. The robot is investigated first by finite element methods. Theoretical models for both tilting and panning were then built based on FEM results. The models are evaluated and verified by checking its predictions in benchtop experiments. Ex vivo evaluations was also utilized to prove feasibility of device in environment similar to human anatomy. Overall, the camera robot prototype is compact (4cm length; 7mm diameter), lightweight (3.6g), motor-free, and allow view orientation control (tilting and panning) in a planar workspace. Minimal footprint in vertical space is ideal for many MIS applications, where vertical space is extremely limited.

Microrobots are considered as promising tools for biomedical applications. However, the imaging of them becomes challenges in order to be further applied on in vivo environments. Here we report the magnetic navigation of a paramagnetic nanoparticle-based swarm using ultrasound images. The swarm can be generated using simple rotating magnetic fields, resulting in a region containing particles with a high area density. Ultrasound images of the swarm shows a periodic changing of imaging contrast. The reason for such dynamic contrast has been analyzed and experimental results are presented. Moreover, this swarm exhibits enhanced ultrasound imaging in comparison to that formed by individual nanoparticles with a low area density, and the relationship between imaging contrast and area density is testified. Furthermore, the microrobotic swarm can be navigated near a solid surface at different velocities, and the imaging contrast show negligible changes. This method allows us to localize and navigate a microrobotic swarm with enhanced ultrasound imaging indicating a promising approach for imaging of microrobots.

Navigation through tubular environment is fundamental in tasks such as pipeline inspection, gastrointestinal tract inspection, etc. Conventional pipeline inspection robots are mostly made by rigid materials and could not well adapt to the large size variation of the environment. Soft robots provide an additional solution for inspection of pipelines, especially with significant size variation. In this work, we present a soft robot for pipeline inspection, which consists of an earthworm-like soft robot and a Central Pattern Generator (CPG)-based control system. An analytical model is developed to predict the maximum pipe diameter that the robot could adapt to. For the current prototype, the robot could adapt to size change of three times. Experimental results show that this robot could navigate through pipelines with sharp turnings and with large diameter change.

Minimally invasive surgery (MIS) has seen substantial development in recent decades. In MIS, particularly in laparoendoscopic single site (LESS) surgery, the surgical site is always crowded. One potential solution is the magnetic anchored and guidance system (MAGS), which liberates instruments from constraint of the accessing port. Current MAGS are all made by rigid components, which relies on articulated joints to maneuver inside the surgical cavity. Moreover, fabricating and assembling the MAGS are difficult due to the small size of the components. In this work, we present the design, modeling, fabrication and testing of a novel soft MAGS endoscope system. The system includes the external controller and the internal unit, which contains a soft body, two magnets and a replaceable wireless camera. It is compact, safe, lightweight and easy to make. Experimental results show that the system could offer stable maneuvering both in lab settings and in porcine model.

In this paper, a concentric wire-driven mechanism (CWM) is presented. The CWM comprises of two nested wire-driven mechanisms (WDM). Each WDM contains a flexible backbone and a set of wires. The backbone bending is controlled by pulling the wires. The stiffness of the outer WDM is controllable and dominants that of the overlapped section. Therefore, in the overlapped section the inner WDM conforms to the shape of the outer WDM and the tip of the outer WDM serves as the base of the distal separate section of the inner WDM. Compared with conventional flexible mechanisms, i.e., tendon/wire/cable-driven mechanism and concentric tube mechanism, the CWM has a much wider workspace. This advantage is demonstrated by simulations based on kinematic modeling. A prototype is developed and the preliminary experimental results validate the design concept.

Endoscopic submucosal dissection (ESD) is an effective and less invasive treatment for early gastric and colorectal cancers. Nevertheless, performing ESD through a flexible endoscope is technically challenging due to the limited controllability of the endoscopic instruments. Therefore, a surgical robotic system with high dexterity and better ergonomics is much needed. A master-slave dual-arm robot with customizing workspace for ESD is proposed for this study. The design is such that the procedure is completed without the need for changing the instrument. Our robot is mainly driven by tendon-sheath (TS) mechanism. Modeling and use of a controller for elongation compensation of tendon due to friction to increase position control accuracy are presented. Experiment shows that the controller greatly enhances the controllability of the robot. We have demonstrated that the design of the robot arm allows it to lift up to 48 g, which is sufficient for ESD. Six subjects, including three endoscopists and upper gastrointestinal surgeons, were invited to evaluate the system in an ex vivo experiment. Experienced surgeons were able to complete a dissection within 30 min. We have demonstrated a prototype robot that can facilitate the ESD procedure with bimanual tissue dissection. The system is competent to remove a lesion area precisely. Further studies are needed to evaluate the system in vivo.

In this paper, a novel constrained tendon-driven serpentine manipulator (CTSM) suited for minimally invasive surgery is presented. It comprises of a flexible backbone, a set of controlling tendons and a constraint. In the CTSM not only the curvature of the bending section can be controlled but also the length. Specifically, the curvature is controlled by the tendons, and the length is controlled by a constraint tube, which is translational and is concentric with the flexible backbone. The kinematic model of the CTSM is developed based on the piecewise constant curvature assumption. Analysis shows that by introducing the translational constraint both the workspace and dexterity of the manipulator are improved. The stiffer the constraint the larger the workspace expansion and the smaller the dexterity enhancement. A prototype is developed and the experimental results validate the design idea and analysis.