Design and Modelling of Continuum Robot for Endoscopic Submucosal Dissection Surgery With Lifting Force Estimation.

BACKGROUND: Endoscopic submucosal dissection (ESD) is an effective treatment for early-stage gastrointestinal cancers. However, traditional surgical instruments lack accuracy and force-sensing. METHODS: A new type of continuum robot for ESD is designed. An accurate static model of the proposed continuum robot is established, considering cases where the robot bends into C-shapes and S-shapes. A force estimation method based on an accurate static model is proposed. Then, the accuracy of the static model and force estimation is verified through experiments. Finally, an ex-organ experiment is carried out. RESULTS: The average position error of the proposed static model is 0.72 mm, accounting for 2.57% of the total robot length. The average error of force estimation is 19.53 mN. By gripping and cutting ex-porcine gastric mucosa, the robot's functionality is validated. CONCLUSION: This paper contributes to precise control and safe interaction of continuum robots.

Design and Motion Control of Master-Slave Control Endotracheal Intubation Robot.

BACKGROUND: Master-slave remote control technology allows patients to be treated promptly during transport and also reduces the risk of contagious infections. Endotracheal intubation, guided by endoscopy and a master-slave system, enables doctors to perform the procedure efficiently and accurately. METHODS: In this paper, we present the development of a master-slave controlled endotracheal intubation robot (EIR). It is based on operation incremental mapping, a weighted recursive average filtering method to reduce vibration, and a virtual fixture designed to reduce mishandling in minimally invasive surgery. RESULTS: Simulation analysis of the master-slave control demonstrates that the weighted recursive average filtering method effectively reduces vibration, while the virtual fixture assists in confining the operator's movement within a delimited area. Experimental validation confirms the validity of the robot's structural design and control method. CONCLUSIONS: The developed robot successfully achieves the necessary motion for endotracheal intubation surgery through master-slave control.

A Naturally Inspired Extrusion-Based Microfluidic Approach for Manufacturing Tailorable Magnetic Soft Continuum Microrobotic Devices.

Soft materials play a crucial role in small-scale robotic applications by closely mimicking the complex motion and morphing behavior of organisms. However, conventional fabrication methods face challenges in creating highly integrated small-scale soft devices. In this study, microfluidics is leveraged to precisely control reaction-diffusion (RD) processes to generate multifunctional and compartmentalized calcium-cross-linkable alginate-based microfibers. Under RD conditions, sophisticated alginate-based fibers are produced for magnetic soft continuum robotics applications with customizable features, such as geometry (compact or hollow), degree of cross-linking, and the precise localization of magnetic nanoparticles (inside the core, surrounding the fiber, or on one side). This fine control allows for tuning the stiffness and magnetic responsiveness of the microfibers. Additionally, chemically cleavable regions within the fibers enable disassembly into smaller robotic units or roll-up structures under a rotating magnetic field. These findings demonstrate the versatility of microfluidics in processing highly integrated small-scale devices.

A Survey of Needle Steering Approaches in Minimally Invasive Surgery.

In virtue of a curved insertion path inside tissues, needle steering techniques have revealed the potential with the assistance of medical robots and images. The superiority of this technique has been preliminarily verified with several maneuvers: target realignment, obstacle circumvention, and multi-target access. However, the momentum of needle steering approaches in the past decade leads to an open question-"How to choose an applicable needle steering approach for a specific clinical application?" This survey discusses this question in terms of design choices and clinical considerations, respectively. In view of design choices, this survey proposes a hierarchical taxonomy of current needle steering approaches. Needle steering approaches of different manipulations and designs are classified to systematically review the design choices and their influences on clinical treatments. In view of clinical consideration, this survey discusses the steerability and acceptability of the current needle steering approaches. On this basis, the pros and cons of the current needle steering approaches are weighed and their suitable applications are summarized. At last, this survey concluded with an outlook of the needle steering techniques, including the potential clinical applications and future developments in mechanical design.

Continuum Robots and Magnetic Soft Robots: From Models to Interdisciplinary Challenges for Medical Applications.

This article explores the challenges of continuum and magnetic soft robotics for medical applications, extending from model development to an interdisciplinary perspective. First, we established a unified model framework based on algebra and geometry. The research progress and challenges in principle models, data-driven, and hybrid modeling were then analyzed in depth. Simultaneously, a numerical analysis framework for the principle model was constructed. Furthermore, we expanded the model framework to encompass interdisciplinary research and conducted a comprehensive analysis, including an in-depth case study. Current challenges and the need to address meta-problems were identified through discussion. Overall, this review provides a novel perspective on understanding the challenges and complexities of continuum and magnetic soft robotics in medical applications, paving the way for interdisciplinary researchers to assimilate knowledge in this domain rapidly.

Adaptive recursive sliding mode based trajectory tracking control for cable-driven continuum robots.

To improve the transient response, accuracy and robustness of trajectory tracking control for cable-driven continuum robots (CDCRs), a recursive integral terminal sliding mode control combined with an adaptive disturbance observer (ADO-RITSMC) is proposed. The recursive integral terminal sliding mode control (RITSMC) guarantees fast transient response and high tracking accuracy with a fast zero convergence of the tracking error without chattering. To attenuate the effect of uncertain dynamics, an adaptive disturbance observer (ADO) is constructed to derive uncertain dynamics. Particularly, an improved grey wolf optimizer (IGWO) is merged into the ADO to enhance the estimating accuracy of uncertain dynamic factors. Simulation and experiment results demonstrate the superiority of the ADO-RITSMC in enabling fast transient response, high accuracy and strong robustness of trajectory tracking control.

Sensing of Continuum Robots: A Review.

The field of continuum robotics is rapidly developing. The development of new kinematic structures, locomotion principles and control strategies is driving the development of new types of sensors and sensing methodologies. The sensing in continuum robots can be divided into shape perception and environment perception. The environment perception is focusing on sensing the interactions between the robot and environment. These sensors are often embedded on an outer layer of the robots, so the interactions can be detected. The shape perception is sensing the robot's shape using various principles. There are three main groups of sensors that use the properties of electricity, magnetism and optics to measure the shape of the continuum robots. The sensors based on measuring the properties of electricity are often based on measuring the electrical resistance or capacitance of the flexible sensor. Sensors based on magnetism use properties of permanent magnets or coils that are attached to the robot. Their magnetic field, flux or other properties are then tracked, and shape reconstruction can be performed. The last group of sensors is mostly based on leveraging the properties of traveling light through optical fibers. There are multiple objectives of this work. Objective number one is to clearly categorize the sensors and make a clear distinction between them. Objective number two is to determine the trend and progress of the sensors used in continuum robotics. And finally, the third objective is to define the challenges that the researchers are currently facing. The challenges of sensing the shape or the interaction with the environment of continuum robots are currently in the miniaturization of existing sensors and the development of novel sensing methods.

Deep CNN-Based Static Modeling of Soft Robots Utilizing Absolute Nodal Coordinate Formulation.

Soft continuum robots, inspired by the adaptability and agility of natural soft-bodied organisms like octopuses and elephant trunks, present a frontier in robotics research. However, exploiting their full potential necessitates precise modeling and control for specific motion and manipulation tasks. This study introduces an innovative approach using Deep Convolutional Neural Networks (CNN) for the inverse quasi-static modeling of these robots within the Absolute Nodal Coordinate Formulation (ANCF) framework. The ANCF effectively represents the complex non-linear behavior of soft continuum robots, while the CNN-based models are optimized for computational efficiency and precision. This combination is crucial for addressing the complex inverse statics problems associated with ANCF-modeled robots. Extensive numerical experiments were conducted to assess the performance of these Deep CNN-based models, demonstrating their suitability for real-time simulation and control in statics modeling. Additionally, this study includes a detailed cross-validation experiment to identify the most effective model architecture, taking into account factors such as the number of layers, activation functions, and unit configurations. The results highlight the significant benefits of integrating Deep CNN with ANCF models, paving the way for advanced statics modeling in soft continuum robotics.

A Pre-Grasping Motion Planning Method Based on Improved Artificial Potential Field for Continuum Robots.

Secure and reliable active debris removal methods are crucial for maintaining the stability of the space environment. Continuum robots, with their hyper-redundant degrees of freedom, offer the ability to capture targets of varying sizes and shapes through whole-arm grasping, making them well-suited for active debris removal missions. This paper proposes a pre-grasping motion planning method for continuum robots based on an improved artificial potential field to restrict the movement area of the grasping target and prevent its escape during the pre-grasping phase. The analysis of the grasping workspace ensures that the target is within the workspace when starting the pre-grasping motion planning by dividing the continuum robot into delivery and grasping segments. An improved artificial potential field is proposed to guide the continuum robot in surrounding the target and creating a grasping area. Specifically, the improved artificial potential field consists of a spatial rotating potential field, an attractive potential field incorporating position and posture potential fields, and a repulsive potential field. The simulation results demonstrate the effectiveness of the proposed method. A comparison of motion planning results between methods that disregard and consider the posture potential field shows that the inclusion of the posture potential field improves the performance of pre-grasping motion planning for spatial targets, achieving a success rate of up to 97.8%.

Soft Pneumatic Muscles: Revolutionizing Human Assistive Devices with Geometric Design and Intelligent Control.

Soft robotics, a recent advancement in robotics systems, distinguishes itself by utilizing soft and flexible materials like silicon rubber, prioritizing safety during human interaction, and excelling in handling complex or delicate objects. Soft pneumatic actuators, a prevalent type of soft robot, are the focus of this paper. A new geometrical parameter for soft artificial pneumatic muscles is introduced, enabling the prediction of actuation behavior using analytical models based on specific design parameters. The study investigated the impact of the chamber pitch parameter and actuation conditions on the deformation direction and internal stress of three tested soft pneumatic muscle (SPM) models. Simulation involved the modeling of hyperelastic materials using finite element analysis. Additionally, an artificial neural network (ANN) was employed to predict pressure values in three chambers at desired Cartesian positions. The trained ANN model demonstrated exceptional performance. It achieved high accuracy with training, validation, and testing residuals of 99.58%, 99.89%, and 99.79%, respectively. During the validation simulations and neural network results, the maximum errors in the x, y, and z coordinates were found to be 9.3%, 7.83%, and 8.8%, respectively. These results highlight the successful performance and efficacy of the trained ANN model in accurately predicting pressure values for the desired positions in the soft pneumatic muscles.

A Fast Soft Continuum Catheter Robot Manufacturing Strategy Based on Heterogeneous Modular Magnetic Units.

Developing small-scale continuum catheter robots with inherent soft bodies and high adaptability to different environments holds great promise for biomedical engineering applications. However, current reports indicate that these robots meet challenges when it comes to quick and flexible fabrication with simpler processing components. Herein, we report a millimeter-scale magnetic-polymer-based modular continuum catheter robot (MMCCR) that is capable of performing multifarious bending through a fast and general modular fabrication strategy. By preprogramming the magnetization directions of two types of simple magnetic units, the assembled MMCCR with three discrete magnetic sections could be transformed from a single curvature pose with a large tender angle to a multicurvature S shape in the applied magnetic field. Through static and dynamic deformation analyses for MMCCRs, high adaptability to varied confined spaces can be predicted. By employing a bronchial tree phantom, the proposed MMCCRs demonstrated their capability to adaptively access different channels, even those with challenging geometries that require large bending angles and unique S-shaped contours. The proposed MMCCRs and the fabrication strategy shine new light on the design and development of magnetic continuum robots with versatile deformation styles, which would further enrich broad potential applications in biomedical engineering.

Continuum Robots: From Conventional to Customized Performance Indicators.

Continuum robots have often been compared with rigid-link designs through conventional performance metrics (e.g., precision and Jacobian-based indicators). However, these metrics were developed to suit rigid-link robots and are tuned to capture specific facets of performance, in which continuum robots do not excel. Furthermore, conventional metrics either fail to capture the key advantages of continuum designs, such as their capability to operate in complex environments thanks to their slender shape and flexibility, or see them as detrimental (e.g., compliance). Previous work has rarely addressed this issue, and never in a systematic way. Therefore, this paper discusses the facets of a continuum robot performance that cannot be characterized by existing indicator and aims at defining a tailored framework of geometrical specifications and kinetostatic indicators. The proposed framework combines the geometric requirements dictated by the target environment and a methodology to obtain bioinspired reference metrics from a biological equivalent of the continuum robot (e.g., a snake, a tentacle, or a trunk). A numerical example is then reported for a swimming snake robot use case.

Robust Global stabilization of aerial continuum manipulation systems via hybrid feedback.

In this paper, the control problem of aerial continuum manipulation systems (ACMSs) is considered. This study introduces a new platform for ACMSs in which a quadrotor is equipped with a tendon-bent concentric tube continuum robot. The decoupled dynamic modeling of ACMSs is utilized to derive the proposed feedback control law. The control design process is split into two distinct control loops. In the first loop, a terminal synergetic controller is presented to control the continuum robot's tip to track the desired trajectory. In the second loop, an improved synergetic controller is introduced to control the position and velocity of the quadrotor, which ensures asymptotic stability of the origin of the error dynamic. Moreover, in this loop a hybrid feedback law is designed to operate with the improved synergetic controller, which overcomes topological obstructions and globally stabilizes the attitude of the quadrotor. Furthermore, the stability of the resultant closed-loop system is verified utilizing the Lyapunov stability theorem. The efficiency and advantages of the proposed controller are verified by a comparative analysis in simulations.

Dexterity enhancement of continuum robot for natural orifice transluminal endoscopic surgery in the dual-manipulator collaborative space.

BACKGROUND: Suturing and knotting in Natural Orifice Transluminal Endoscopic Surgery (NOTES) requires the robot not only to be able to work with multiple manipulators but also to have a high degree of dexterity. However, little attention has been paid to the design and enhancement of dexterity in multi-manipulated robots. METHODS: In this paper, the dexterity of a new dual-manipulator collaborative continuum robot in collaborative space is analyzed and enhanced. A kinematic model of the continuum robot was developed. The dexterity function of the robot is evaluated based on the concepts of the low-Degree-of-Freedom Jacobian matrix. Then an Adaptive Parameter Gray Wolf Coupled Cuckoo Optimization Algorithm with faster convergence and higher accuracy is innovatively proposed to optimize the objective function. Finally, experiments demonstrate that the dexterity of the optimized continuum robot is enhanced. RESULTS: The optimization results show that the optimized dexterity is 24.91% better than the initial state. CONCLUSION: Through the work of this paper, the robot for NOTES can perform suturing and knot more dexterously, which has significant implications for the treatment of digestive tract diseases.

Use of semi-synthetic data for catheter segmentation improvement.

In the era of data-driven machine learning algorithms, data is the new oil. For the most optimal results, datasets should be large, heterogeneous and, crucially, correctly labeled. However, data collection and labeling are time-consuming and labor-intensive processes. In the field of medical device segmentation, present during minimally invasive surgery, this leads to a lack of informative data. Motivated by this drawback, we developed an algorithm generating semi-synthetic images based on real ones. The concept of this algorithm is to place a randomly shaped catheter in an empty heart cavity, where the shape of the catheter is generated by forward kinematics of continuum robots. Having implemented the proposed algorithm, we generated new images of heart cavities with various artificial catheters. We compared the results of deep neural networks trained purely on real datasets with respect to networks trained on both real and semi-synthetic datasets, highlighting that semi-synthetic data improves catheter segmentation accuracy. A modified U-Net trained on combined datasets performed the segmentation with a Dice similarity coefficient of 92.6 ± 2.2%, while the same model trained only on real images achieved a Dice similarity coefficient of 86.5 ± 3.6%. Therefore, using semi-synthetic data allows for the decrease of accuracy spread, improves model generalization, reduces subjectivity, shortens the labeling routine, increases the number of samples, and improves the heterogeneity.

Modular Morphing Lattices for Large-Scale Underwater Continuum Robotic Structures.

In this study, we present a method to construct meter-scale deformable structures for underwater robotic applications by discretely assembling mechanical metamaterials. We address the challenge of scaling up nature-like deformable structures while remaining structurally efficient by combining rigid and compliant facets to form custom unit cells that assemble into lattices. The unit cells generate controlled local anisotropies that architect the global deformation of the robotic structure. The resulting flexibility allows better unsteady flow control that enables highly efficient propulsion and optimized force profile manipulations. We demonstrate the utility of this approach in two models. The first is a morphing beam snake-like robot that can generate thrust at specific anguilliform swimming parameters. The second is a morphing surface hydrofoil that, when compared with a rigid wing at the same angles of attack (AoAs), can increase the lift coefficient up to 0.6. In addition, in lower AoAs, the L∕D ratio improves by 5 times, whereas in higher angles it improves by 1.25 times. The resulting hydrodynamic performance demonstrates the potential to achieve accessible, scalable, and simple to design and assemble morphing structures for more efficient and effective future ocean exploration and exploitation.

Design and kinematics of a tube-shaped multidirectional bending robotic device using slackened SMA wires for transurethral ureterolithotripsy.

PURPOSE: The complex and elaborate structure of the urinary system presents surgeons with difficulty in using a ureteroscope with a fixed optical fiber to reach the targeted calculus. To address this challenge, a robotic device is required to control the direction of laser irradiation position independently in ureteroscopes. METHOD: A continuum robotic device was designed and fabricated. The device is constructed with three slackened shape memory alloy (SMA) wires to control the laser irradiation position of the optical fiber combined with the view of the camera on the tip of the ureteroscope. Kinematics analysis and experimental evaluation reveal the capability of the device. RESULTS: The structure of the device is the same as a single-joint continuum robot. This device is unique because of the tiny diameter of 1.1 mm which can be used inside the ureteroscope through a Ø1.2 mm inner channel into the kidney for transurethral ureterolithotripsy. Kinematic analysis revealed the relationship among space coordinates, angles of bending, and direction and SMA wires length. The maximum bending angle was around 25° when the current value was 350 mA on a single SMA wire. The device could achieve multi-directional bending by allocating the values of current on SMA wires, separately. CONCLUSION: This device offers a major advancement in small size and dexterity in medical robotics. Combined with a proper control system, this device could simplify the operation and improve the efficiency of the transurethral ureterolithotripsy.

Continuum robots for endoscopic sinus surgery: Recent advances, challenges, and prospects.

PURPOSE: Endoscopic sinus surgery (ESS) has been recognized as an effective treatment modality for paranasal sinus diseases. Over the past decade, continuum robots (CRs) for ESS have been studied, but there are still some challenges. This paper presents a review on the scientific studies of CRs for ESS. METHODS: Based on the analysis of the anatomical structure of the paranasal sinus, the requirements of CRs for ESS are discussed. Recent studies on rigid robots, handheld flexible robots, and CRs for ESS are presented. Surgical path planning, navigation, and control are also included. RESULTS: Concentric tube CRs and cable-driven CRs have great potential for applications in ESS. The CRs incorporated with multiple replaceable arms with different functions are preferable in ESS. CONCLUSION: Further study on navigation and control is required to improve the performance of CRs for ESS.

Hybrid Tendon and Ball Chain Continuum Robots for Enhanced Dexterity in Medical Interventions.

A hybrid continuum robot design is introduced that combines a proximal tendon-actuated section with a distal telescoping section comprised of permanent-magnet spheres actuated using an external magnet. While, individually, each section can approach a point in its workspace from one or at most several orientations, the two-section combination possesses a dexterous workspace. The paper describes kinematic modeling of the hybrid design and provides a description of the dexterous workspace. We present experimental validation which shows that a simplified kinematic model produces tip position mean and maximum errors of 3% and 7% of total robot length, respectively.

QPSO-MPC based tracking algorithm for cable-driven continuum robots.

Cable-driven continuum robots (CDCRs) can flexibly travel through narrow space for complex workspace tasks. However, it is challenging to design the trajectory tracking algorithm for CDCRs due to their nonlinear dynamic behaviors and cable hysteresis characteristics. In this contribution, a model predictive control (MPC) tracking algorithm based on quantum particle swarm optimization (QPSO) is designed for CDCRs to realize effective trajectory tracking under constraints. In order to make kinematic analysis of a CDCR, the forward and inverse mapping among actuation space, joint space and work space is analyzed by using the piecewise constant curvature method and the homogeneous coordinate transformation. To improve the performance of conventional MPC for complex tracking tasks, QPSO is adopted in the rolling optimization of MPC for its global optimization performance, robustness and fast convergence. Both simulation and operational experiment results demonstrate that the designed QPSO-MPC presents high control stability and trajectory tracking precision. Compared with MPC and particle swarm optimization (PSO) based MPC, the tracking error of QPSO-MPC is reduced by at least 43 and 24%, respectively.