Wearable and Implantable Soft Robots

Soft robotics presents innovative solutions across different scales. The flexibility and mechanical characteristics of soft robots make them particularly appealing for wearable and implantable applications. The scale and level of invasiveness required for soft robots depend on the extent of human interaction. This review provides a comprehensive overview of wearable and implantable soft robots, including applications in rehabilitation, assistance, organ simulation, surgical tools, and therapy. We discuss challenges such as the complexity of fabrication processes, the integration of responsive materials, and the need for robust control strategies, while focusing on advances in materials, actuation and sensing mechanisms, and fabrication techniques. Finally, we discuss the future outlook, highlighting key challenges and proposing potential solutions.

YoMo: Yoshimura Continuum Manipulator for MR Environment

Origami robots have garnered attention due to their versatile deformation and potential applications, particularly for medical applications. In this article, we propose a Yoshimura continuum manipulator (YoMo) that can achieve accurate control of the tip position for the magnetic resonance (MR) environment. The YoMo made of a single piece of paper is cable-actuated to generate the bending and shortening deformation. The paper-based YoMo attached to an arc frame can readily function under different orientations in the MR environment. The design and fabrication of YoMo were formulated according to the Yoshimura folding pattern. The kinematics model based on constant curvature assumption was derived as a benchmark method to predict the tip position of the YoMo. The Koopman operator theory was applied to describe the relationship between the tip position and the length change under different orientations. The linear quadratic regulator integrated into the Koopman-based model (K-LQR) was adopted to achieve the trajectory tracking. Comprehensive experiments were carried out to examine the proposed YoMo, its modeling and control methods. The performance of the YoMo including stiffness and workspace was characterized via a customized test setup. The Koopman-based method demonstrates the superiority over the constant curvature-based model to predict the tip position. The K-LQR control method was examined with different trajectories, and the impact of the orientation, speed, and different trajectories were taken into consideration. The results demonstrate the YoMo is capable of achieving trajectory tracking with satisfied accuracy, indicating its potential for medical applications in the MR environment.

Automatic Path-Planning Techniques for Minimally Invasive Stereotactic Neurosurgical Procedures-A Systematic Review

This review systematically examines the recent research from the past decade on diverse path-planning algorithms tailored for stereotactic neurosurgery applications. Our comprehensive investigation involved a thorough search of scholarly papers from Google Scholar, PubMed, IEEE Xplore, and Scopus, utilizing stringent inclusion and exclusion criteria. The screening and selection process was meticulously conducted by a multidisciplinary team comprising three medical students, robotic experts with specialized knowledge in path-planning techniques and medical robotics, and a board-certified neurosurgeon. Each selected paper was reviewed in detail, and the findings were synthesized and reported in this review. The paper is organized around three different types of intervention tools: straight needles, steerable needles, and concentric tube robots. We provide an in-depth analysis of various path-planning algorithms applicable to both single and multi-target scenarios. Multi-target planning techniques are only discussed for straight tools as there is no published work on multi-target planning for steerable needles and concentric tube robots. Additionally, we discuss the imaging modalities employed, the critical anatomical structures considered during path planning, and the current status of research regarding its translation to clinical human studies. To the best of our knowledge and as a conclusion from this systematic review, this is the first review paper published in the last decade that reports various path-planning techniques for different types of tools for minimally invasive neurosurgical applications. Furthermore, this review outlines future trends and identifies existing technology gaps within the field. By highlighting these aspects, we aim to provide a comprehensive overview that can guide future research and development in path planning for stereotactic neurosurgery, ultimately contributing to the advancement of safer and more effective neurosurgical procedures.

Design and Research of the Grasping Force Feedback Mechanism of Flexible Surgical Robots

BACKGROUND

Robot-assisted microsurgery (RAMS) is gradually becoming the preferred method for some delicate surgical procedures. However, the lack of haptic feedback reduces the safety of the surgery. Surgeons are unable to feel the grasping force between surgical instruments and the patient's tissues, which can easily lead to grasping failure or tissue damage.

METHODS

This paper proposes a tendon-driven grasping force feedback mechanism, consisting of a follower hand and a leader hand, to address the lack of grasping force feedback in flexible surgical robots. Considering the friction in the tendon transmission process, a grasping force estimation model is established for the follower hand. The admittance control model is designed for force/position control of the leader hand.

RESULTS

Through experimental validation, it has been confirmed that the grasping force sensing range of the follower hand is 0.5-5 N, with a sensing accuracy of 0.3 N. The leader hand is capable of providing feedback forces in the range of 0-5 N, with a static force accuracy of 0.1 N.

CONCLUSIONS

The designed mechanism and control strategy can provide the grasping force feedback function. Future work will focus on improving force feedback performance.

TRIAL REGISTRATION

This research has no clinical trials.

Thermally Drawn-Based Microtubule Soft Continuum Robot for Cardiovascular Intervention

Cardiovascular disease is becoming the leading cause of human mortality. In order to address this, flexible continuum robots have emerged as a promising solution for miniaturizing and automating vascular interventional equipment for diagnosing and treating cardiovascular diseases. However, existing continuum robots used for vascular intervention face challenges such as large cross-sectional sizes, inadequate driving force, and lack of navigation control, preventing them from accessing cerebral blood vessels or capillaries for medical procedures. Additionally, the complex manufacturing process and high cost of soft continuum robots hinder their widespread clinical application. In this study, we propose a thermally drawn-based microtubule soft continuum robot that overcomes these limitations. The proposed robot has cross-sectional dimensions several orders of magnitude smaller than the smallest commercially available conduits, and it can be manufactured without any length restrictions. By utilizing a driving strategy based on liquid kinetic energy advancement and external magnetic field for steering, the robot can easily navigate within blood vessels and accurately reach the site of the lesion. This innovation holds the potential to achieve controlled navigation of the robot throughout the entire blood vessel, enabling in situ diagnosis and treatment of cardiovascular diseases.

Actuation mechanism of a nanoscale drilling rig based on nested carbon nanotubes

With the increasing emphasis on health and the continuous improvement of medical standards, more and more micro/nano devices are being used in the medical field. However, the existing micro/nano devices cannot effectively solve various problems encountered in medical processes and achieve specific therapeutic effects. Based on this, this article designs a new type of nanoscale drilling rig. The nanoscale drilling rig is composed of double-layer nested carbon nanotubes with multiple electrodes, and is powered by an external power source, making it easy to perform long-term surgery in the human body. Through coding strategies, we can adjust the surface charge density and distribution of the nanoscale drilling rig, thereby controlling its periodical rotation and achieving precise medical treatment. In addition, in order to control the length of the nanoscale drill bit, meet the treatment needs of different parts of the human body, and reduce damage to the human body, we have designed a structure of ion electric double layers so that the drill bit can be fixed in different positions, reducing the risk of treatment to a certain extent. This drilling rig enriches the functions of micro/nano devices, which is beneficial for the development of the medical industry.

Shape Sensing and Kinematic Control of a Cable-Driven Continuum Robot Based on Stretchable Capacitive Sensors

A Cable-Driven Continuum Robot (CDCR) that consists of a set of identical Cable-Driven Continuum Joint Modules (CDCJMs) is proposed in this paper. The CDCJMs merely produce 2-DOF bending motions by controlling driving cable lengths. In each CDCJM, a pattern-based flexible backbone is employed as a passive compliant joint to generate 2-DOF bending deflections, which can be characterized by two joint variables, i.e., the bending direction angle and the bending angle. However, as the bending deflection is determined by not only the lengths of the driving cables but also the gravity and payload, it will be inaccurate to compute the two joint variables with its kinematic model. In this work, two stretchable capacitive sensors are employed to measure the bending shape of the flexible backbone so as to accurately determine the two joint variables. Compared with FBG-based and vision-based shape-sensing methods, the proposed method with stretchable capacitive sensors has the advantages of high sensitivity to the bending deflection of the backbone, ease of implementation, and cost effectiveness. The initial location of a stretchable sensor is generally defined by its two endpoint positions on the surface of the backbone without bending. A generic shape-sensing model, i.e., the relationship between the sensor reading and the two joint variables, is formulated based on the 2-DOF bending deflection of the backbone. To further improve the accuracy of the shape-sensing model, a calibration method is proposed to compensate for the location errors of stretchable sensors. Based on the calibrated shape-sensing model, a sliding-mode-based closed-loop control method is implemented for the CDCR. In order to verify the effectiveness of the proposed closed-loop control method, the trajectory tracking accuracy experiments of the CDCR are conducted based on a circle trajectory, in which the radius of the circle is 55mm. The average tracking errors of the CDCR measured by the Qualisys motion capture system under the open-loop and the closed-loop control are 49.23 and 8.40mm, respectively, which is reduced by 82.94%.

Model-based trajectory tracking of a compliant continuum robot

Introduction: Compliant mechanisms, especially continuum robots, are becoming integral to advancements in minimally invasive surgery due to their ability to autonomously navigate natural pathways, significantly reducing collision severity. A major challenge lies in developing an effective control strategy to accurately reflect their behavior for enhanced operational precision. Methods: This study examines the trajectory tracking capabilities of a tendon-driven continuum robot at its tip. We introduce a novel feedforward control methodology that leverages a mathematical model based on Cosserat rod theory. To mitigate the computational challenges inherent in such models, we implement an implicit time discretization strategy. This approach simplifies the governing equations into space-domain ordinary differential equations, facilitating real-time computational efficiency. The control strategy is devised to enable the robot tip to follow a dynamically prescribed trajectory in two dimensions. Results: The efficacy of the proposed control method was validated through experimental tests on six different demand trajectories, with a motion capture system employed to assess positional accuracy. The findings indicate that the robot can track trajectories with an accuracy within 9.5%, showcasing consistent repeatability across different runs. Discussion: The results from this study mark a significant step towards establishing an efficient and precise control methodology for compliant continuum robots. The demonstrated accuracy and repeatability of the control approach significantly enhance the potential of these robots in minimally invasive surgical applications, paving the way for further research and development in this field.

Adaptive Online Learning and Robust 3-D Shape Servoing of Continuum and Soft Robots in Unstructured Environments

In this article, we present a novel and generic data-driven method to servo-control the 3-D shape of continuum and soft robots based on proprioceptive sensing feedback. Developments of 3-D shape perception and control technologies are crucial for continuum and soft robots to perform tasks autonomously in surgical interventions. However, owing to the nonlinear properties of continuum robots, one main difficulty lies in the modeling of them, especially for soft robots with variable stiffness. To address this problem, we propose a versatile learning-based adaptive shape controller by leveraging proprioception of 3-D configuration from fiber Bragg grating (FBG) sensors, which can online estimate the unknown model of continuum robot against unexpected disturbances and exhibit an adaptive behavior to the unmodeled system without priori data exploration. Based on a new composite adaptation algorithm, the asymptotic convergences of the closed-loop system with learning parameters have been proven by Lyapunov theory. To validate the proposed method, we present a comprehensive experimental study using two continuum and soft robots both integrated with multicore FBGs, including a robotic-assisted colonoscope and multisection extensible soft manipulators. The results demonstrate the feasibility, adaptability, and superiority of our controller in various unstructured environments, as well as phantom experiments.

A mechanics-based model for a tendon-driven active needle navigating inside a multiple-layer tissue

Percutaneous minimally invasive procedures such brachytherapy and biopsy require a flexible active needle for precise movement inside tissue and accurate placement at target positions for higher success rates for diagnosis and treatment, respectively. In a previous work, we presented a tendon-driven active needle to navigate inside tissue. This work presents a new model to predict the deflection of the tendon-driven needle while steering in a multiple-layer soft tissue. A multi-layer phantom tissue with different localized stiffness was developed for needle insertion tests followed by indentation tests to identify its mechanical properties. Using a robot that inserts and actively bends the tendon-driven needle inside the soft tissue while simultaneously tracking the needle through ultrasound imaging, various experiments were conducted for model validation. The proposed model was verified by comparing the simulation results to the empirical data. The results demonstrated the accuracy of the model in predicting the tendon-driven needle deflection in multiple-layer (different stiffness) soft tissue.

Multifunctional flexible magnetic drive gripper for target manipulation in complex constrained environments

Soft actuators capable of remote-controlled guidance and manipulation within complex constrained spaces hold great promise in various fields, especially in medical fields such as minimally invasive surgery. However, most current magnetic drive soft actuators only have the functions of position control and guidance, and it is still challenging to achieve more flexible operations on different targets within constrained spaces. Herein, we propose a multifunctional flexible magnetic drive gripper that can be steered within complex constrained spaces and operate on targets of various shapes. On the one hand, changing the internal pressure of the magnetic gripper can achieve functions such as suction or injection of liquid and transportation of targets with smooth surfaces. On the other hand, with the help of slit structures in the constrained environment, by simply changing the position and orientation of the permanent magnet in the external environment, the magnetic gripper can be controlled to clamp and release targets of linear, flaked, and polyhedral shapes. The full flexibility and multifunctionality of the magnetic gripper suggest new possibilities for precise remote control and object transportation in constrained spaces, so it could serve as a direct contact operation tool for hazardous drugs in enclosed spaces or a surgical tool in human body cavities.

Adaptive fuzzy control for tendon-sheath actuated bending-tip system with unknown friction for robotic flexible endoscope

Introduction

The tendon-sheath actuated bending-tip system (TAB) has been widely applied to long-distance transmission scenes due to its high maneuverability, safety, and compliance, such as in exoskeleton robots, rescue robots, and surgical robots design. Due to the suitability of operation in a narrow or tortuous environment, TAB has demonstrated great application potential in the area of minimally invasive surgery. However, TAB involves highly non-linear behavior due to hysteresis, creepage, and non-linear friction existing on the tendon routing, which is an enormous challenge for accurate control.

Methods

Considering the difficulties in the precise modeling of non-linearity friction, this paper proposes a novel fuzzy control scheme for the Euler-Lagrange dynamics model of TAB for achieving tracking performance and providing accurate friction compensation. Finally, the asymptotic stability of the closed-loop system is proved theoretically and the effectiveness of the controller is verified by numerical simulation carried out in MATLAB/Simulink.

Results

The desired angle can be reached quickly within 3 s by adopting the proposed controller without overshoot or oscillation in Tracking Experiment, demonstrating the regulation performance of the proposed control scheme. The proposed method still achieves the desired trajectory rapidly and accurately without steady-state errors in Varying-friction Experiment. The angle errors generated by external disturbances are < 1 deg under the proposed controller, which returns to zero in 2 s in Anti-disturbance Experiment. In contrast, comparative controllers take more time to be steady and are accompanied by oscillating and residual errors in all experiments.

Discussion

The proposed method is model-free control and has no strict requirement for the dynamics model and friction model. It is proved that advanced tracking performance and real-time response can be guaranteed under the presence of unknown bounded non-linear friction and time-varying non-linear dynamics.

Modeling and experimental analysis of wire-driven continuum surgical robot

A new configuration of continuum surgical robot is proposed, whose skeleton is composed of inner and outer layers. The outer layer is composed of miniature rotating modules connected in series and connected by orthogonal hinges, which can ensure the ability to resist unconventional torsion without losing the degree of freedom. The inner layer is a central support column with superelasticity. When bending, its superelasticity can make the overall configuration biased toward constant curvature bending, which is convenient for motion control and according to the new configuration, this paper establishes the kinematics model of the robot. Finally, the motion control experiment of the continuum robot is carried out. After the experiment, the average positioning error of the robot is 2.674 mm, and the average repetitive positioning error is 2.625 mm. Both are less than 2 % of the robot length, verifying the accuracy of the model.

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.

Review of robotic surgery platforms and end effectors

In the last 50 years, the number of companies producing automated devices for surgical operations has grown extensively. The population started to be more confident about the technology capabilities. The first patents related to surgical robotics are expiring and this knowledge is becoming a common base for the development of future surgical robotics. The review describes some of the most popular companies manufacturing surgical robots. The list of the company does not pretend to be exhaustive but wishes to give an overview of the sector. Due to space constraints, only a limited selction of companies is reported. Most of the companies described are born in America or Europe. Advantages and limitations of each product firm are described. A special focus is given to the end effectors; their shape and dexterity are crucial for the positive outcome of the surgical operations. New robots are developed every year, and existing robots are allowed to perform a wider range of procedures. Robotic technologies improve the abilities of surgeons in the domains of urology, gynecology, neurology, spine surgery, orthopedic reconstruction (knee, shoulder), hair restoration, oral surgery, thoracic surgery, laparoscopic surgery, and endoscopy.

A Model to Predict Deflection of an Active Tendon-Driven Notched Needle Inside Soft Tissue

The last decade has witnessed major progress in the field of minimally invasive and robotic-assisted surgeries. Needle insertion, a minimally invasive technique, has proven its efficacy in procedures such as brachytherapy, ablation, drug delivery, and biopsy. Manual needle steering inside tissue is a challenging task due to complex needle-tissue interactions, needle and tissue movement, lack of actuation and control, as well as poor sensing and visualization. Recently, active tendon-driven notched needles, and robotic manipulation systems have been proposed to assist surgeons to guide the needles in desired trajectories toward target positions. This work introduces a new deflection model for the active tendon-driven notched needle steering inside soft tissue for intention to use in model-based robotic control. The model is developed to predict needle deflection in a single-layer tissue. To validate the proposed deflection model, five sets of needle insertion experiments with a bevel-tipped active needle into single-layer phantom tissues were performed. A real-time robot-assisted ultrasound tracking method was used to track the needle tip during needle insertion. It was shown that the model predicts needle deflection with an average error of 0.58 ± 0.14 mm for the bevel-tipped active needle insertion into a single-layer phantom tissue.

Pioneering healthcare with soft robotic devices: A review

Recent advancements in soft robotics have been emerging as an exciting paradigm in engineering due to their inherent compliance, safe human interaction, and ease of adaptation with wearable electronics. Soft robotic devices have the potential to provide innovative solutions and expand the horizons of possibilities for biomedical applications by bringing robots closer to natural creatures. In this review, we survey several promising soft robot technologies, including flexible fluidic actuators, shape memory alloys, cable-driven mechanisms, magnetically driven mechanisms, and soft sensors. Selected applications of soft robotic devices as medical devices are discussed, such as surgical intervention, soft implants, rehabilitation and assistive devices, soft robotic exosuits, and prosthetics. We focus on how soft robotics can improve the effectiveness, safety and patient experience for each use case, and highlight current research and clinical challenges, such as biocompatibility, long-term stability, and durability. Finally, we discuss potential directions and approaches to address these challenges for soft robotic devices to move toward real clinical translations in the future.

A Novel Extensible Continuum Robot with Growing Motion Capability Inspired by Plant Growth for Path-Following in Transoral Laryngeal Surgery

This article presents a novel extensible continuum robot (ECR) with growing motion capability for improved flexible access in transoral laryngeal procedures. The robot uses an extensible continuum joint with a staggered V-shaped notched structure as the backbone, driven by the pushing and pulling of superelastic Nitinol rods. The notched structure is optimized to achieve a wide range of extension/contraction and bending motion for the continuum joint. The successive and uniform deflection of the notches provides the continuum joint with excellent constant curvature bending characteristics. The bidirectional rod-driven approach expands the robot's extension capabilities with both pushing and pulling operations, and the superelasticity of the driving rods preserves the robot's bending performance. The ECR significantly increases motion dexterity and reachability through its variable length, which facilitates collision-free access to deep lesions by following the anatomy. To further exploit the advantages of the ECR in path-following for flexible access, a growing motion approach inspired by the plant growth process has been proposed to minimize the path deviation error. Characterization experiments are conducted to verify the performances of the proposed ECR. The extension ratio achieves up to 225.92%, and the average distal positioning error and hysteresis error values are 2.87% and 0.51% within the ±120° bending range. Compared with the typical continuum robot with a fixed length, the path-following deviation of this robot is reduced by more than 58.30%, effectively reducing the risk of collision during access. Phantom experiments validate the feasibility of the proposed concept in flexible access procedures.

Bioinspired handheld time-share driven robot with expandable DoFs

Handheld robots offer accessible solutions with a short learning curve to enhance operator capabilities. However, their controllable degree-of-freedoms are limited due to scarce space for actuators. Inspired by muscle movements stimulated by nerves, we report a handheld time-share driven robot. It comprises several motion modules, all powered by a single motor. Shape memory alloy (SMA) wires, acting as "nerves", connect to motion modules, enabling the selection of the activated module. The robot contains a 202-gram motor base and a 0.8 cm diameter manipulator comprised of sequentially linked bending modules (BM). The manipulator can be tailored in length and integrated with various instruments in situ, facilitating non-invasive access and high-dexterous operation at remote surgical sites. The applicability was demonstrated in clinical scenarios, where a surgeon held the robot to conduct transluminal experiments on a human stomach model and an ex vivo porcine stomach. The time-share driven mechanism offers a pragmatic approach to build a multi-degree-of-freedom robot for broader applications.

Design Optimization of a Hybrid-Driven Soft Surgical Robot with Biomimetic Constraints

The current study investigated the geometry optimization of a hybrid-driven (based on the combination of air pressure and tendon tension) soft robot for use in robot-assisted intra-bronchial intervention. Soft robots, made from compliant materials, have gained popularity for use in surgical interventions due to their dexterity and safety. The current study aimed to design a catheter-like soft robot with an improved performance by minimizing radial expansion during inflation and increasing the force exerted on targeted tissues through geometry optimization. To do so, a finite element analysis (FEA) was employed to optimize the soft robot's geometry, considering a multi-objective goal function that incorporated factors such as chamber pressures, tendon tensions, and the cross-sectional area. To accomplish this, a cylindrical soft robot with three air chambers, three tendons, and a central working channel was considered. Then, the dimensions of the soft robot, including the length of the air chambers, the diameter of the air chambers, and the offsets of the air chambers and tendon routes, were optimized to minimize the goal function in an in-plane bending scenario. To accurately simulate the behavior of the soft robot, Ecoflex 00-50 samples were tested based on ISO 7743, and a hyperplastic model was fitted on the compression test data. The FEA simulations were performed using the response surface optimization (RSO) module in ANSYS software, which iteratively explored the design space based on defined objectives and constraints. Using RSO, 45 points of experiments were generated based on the geometrical and loading constraints. During the simulations, tendon force was applied to the tip of the soft robot, while simultaneously, air pressure was applied inside the chamber. Following the optimization of the geometry, a prototype of the soft robot with the optimized values was fabricated and tested in a phantom model, mimicking simulated surgical conditions. The decreased actuation effort and radial expansion of the soft robot resulting from the optimization process have the potential to increase the performance of the manipulator. This advancement led to improved control over the soft robot while additionally minimizing unnecessary cross-sectional expansion. The study demonstrates the effectiveness of the optimization methodology for refining the soft robot's design and highlights its potential for enhancing surgical interventions.

Nonlinear dynamic modeling and model-based AI-driven control of a magnetoactive soft continuum robot in a fluidic environment

In recent years, magnetoactive soft continuum robots (MSCRs) with multimodal locomotion capabilities have emerged for various biomedical applications. Developments in nonlinear dynamic models and effective control methods for MSCRs are deemed vital not only to gain a better understanding of their coupled magneto-mechanical behavior but also to accurately steer the MSCRs inside the human body. This study presents a novel dynamic model and model-based AI-driven control method to guide an MSCR in a fluidic environment. The MSCR is fully exposed to fluid flows at different rates to simulate the biofluidic environment within the body. A novel nonlinear dynamic model considering the effect of damping and drag force attributed to fluidic flows is first developed to accurately and efficiently predict the response of the MSCR under varying magnetic and mechanical loading. Fairly accurate correlations were observed between the theoretical responses based on the developed magneto-viscoelastic model and the experimental data for various scenarios. A novel model-based control algorithm based on a fractional-order sliding surface and deep reinforcement learning algorithm (DRL-FOSMC) is subsequently developed to accurately steer the magnetoactive soft robot on predefined trajectories considering varying fluid flow rates. A fractional-order sliding surface and a compensator, trained using the deep deterministic policy gradient algorithm, are designed to mitigate the amount of chattering and enhance the tracking performance of the closed-loop system. The stability proof of the developed control algorithm is also presented. A hardware-in-the-loop experimental framework has been designed to assess the effectiveness of the proposed control algorithm through various case studies. The performance of the proposed DRL-FOSMC algorithm is rigorously assessed and found to be superior when compared with other control 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.

Compound continuum manipulator for surgery: Efficient static-based kinematics

BACKGROUND

The combination of various continuum manipulators is a potential solution to break the bottleneck of continuum manipulators. However, continuum manipulators dissatisfy the constant curvature assumption due to the influence of joints.

METHODS

In this paper, a mechanics-based kinematic model of the compound continuum manipulator is proposed, which indicates that the curvature is non-constant. The static model of the manipulator is established, and the relationship of the bending angles is obtained. An efficient static-based Inverse Kinematic Algorithm using Polynomial Curve (IKAPC) of the manipulator is proposed. The polynomial curve is used to fit the end trajectory of the first manipulator.

RESULTS

The simulation results show that the IKAPC is 354 times faster than the Levenberg-Marquardt algorithm. The experimental results show that the mechanics-based model improves the position accuracy by 3.75 times over the constant curvature method.

CONCLUSION

This paper is critical for solving the inverse kinematics of the compound continuum manipulator.

A Novel Spatial Position Prediction Navigation System Makes Surgery More Accurate

During intravascular interventional surgery, the 3D surgical navigation system can provide doctors with 3D spatial information of the vascular lumen, reducing the impact of missing dimension caused by digital subtraction angiography (DSA) guidance and further improving the success rate of surgeries. Nevertheless, this task often comes with the challenge of complex registration problems due to vessel deformation caused by respiratory motion and high requirements for the surgical environment because of the dependence on external electromagnetic sensors. This article proposes a novel 3D spatial predictive positioning navigation (SPPN) technique to predict the real-time tip position of surgical instruments. In the first stage, we propose a trajectory prediction algorithm integrated with instrumental morphological constraints to generate the initial trajectory. Then, a novel hybrid physical model is designed to estimate the trajectory's energy and mechanics. In the second stage, a point cloud clustering algorithm applies multi-information fusion to generate the maximum probability endpoint cloud. Then, an energy-weighted probability density function is introduced using statistical analysis to achieve the prediction of the 3D spatial location of instrument endpoints. Extensive experiments are conducted on 3D-printed human artery and vein models based on a high-precision electromagnetic tracking system. Experimental results demonstrate the outstanding performance of our method, reaching 98.2% of the achievement ratio and less than 3 mm of the average positioning accuracy. This work is the first 3D surgical navigation algorithm that entirely relies on vascular interventional robot sensors, effectively improving the accuracy of interventional surgery and making it more accessible for primary surgeons.

Magnetic Continuum Robot with Intraoperative Magnetic Moment Programming

Magnetic continuum robots (MCRs), which are free of complicated structural designs for transmission, can be miniaturized and are therefore widely used in the medical field. However, the deformation shapes of different segments, including deflection directions and curvatures, are difficult to control simultaneously under an external programmable magnetic field. This is because the latest MCRs have designs with an invariable magnetic moment combination or profile of one or more actuating units. Therefore, the limited dexterity of the deformation shape causes the existing MCRs to collide readily with their surroundings or makes them unable to approach difficult-to-reach regions. These prolonged collisions are unnecessary or even hazardous, especially for catheters or similar medical devices. In this study, a novel magnetic moment intraoperatively programmable continuum robot (MMPCR) is introduced. By applying the proposed magnetic moment programming method, the MMPCR can deform under three modalities, that is, J, C, and S shapes. Additionally, the deflection directions and curvatures of different segments in the MMPCR can be modulated as desired. Furthermore, the magnetic moment programming and MMPCR kinematics are modeled, numerically simulated, and experimentally validated. The experimental results exhibit a mean deflection angle error of 3.3° and correspond well with simulation results. Comparisons between navigation capacities of the MMPCR and MCR demonstrate that the MMPCR has a higher capacity for dexterous deformation.

Spreadable Magnetic Soft Robots with On-Demand Hardening

Magnetically actuated mobile robots demonstrate attractive advantages in various medical applications due to their wireless and programmable executions with tiny sizes. Confronted with complex application scenarios, however, it requires more flexible and adaptive deployment and utilization methods to fully exploit the functionalities brought by magnetic robots. Herein, we report a design and utilization strategy of magnetic soft robots using a mixture of magnetic particles and non-Newtonian fluidic soft materials to produce programmable, hardened, adhesive, reconfigurable soft robots. For deployment, their ultrasoft structure and adhesion enable them to be spread on various surfaces, achieving magnetic actuation empowerment. The reported technology can potentially improve the functionality of robotic end-effectors and functional surfaces. Experimental results demonstrate that the proposed robots could help to grasp and actuate objects 300 times heavier than their weight. Furthermore, it is the first time we have enhanced the stiffness of mechanical structures for these soft materials by on-demand programmable hardening, enabling the robots to maximize force outputs. These findings offer a promising path to understanding, designing, and leveraging magnetic robots for more powerful applications.

Three-degrees-of-freedom orientation manipulation of small untethered robots with a single anisotropic soft magnet

Magnetic actuation has been well exploited for untethered manipulation and locomotion of small-scale robots in complex environments such as intracorporeal lumens. Most existing magnetic actuation systems employ a permanent magnet onboard the robot. However, only 2-DoF orientation of the permanent-magnet robot can be controlled since no torque can be generated about its axis of magnetic moment, which limits the dexterity of manipulation. Here, we propose a new magnetic actuation method using a single soft magnet with an anisotropic geometry (e.g., triaxial ellipsoids) for full 3-DoF orientation manipulation. The fundamental actuation principle of anisotropic magnetization and 3-DoF torque generation are analytically modeled and experimentally validated. The hierarchical orientation stability about three principal axes is investigated, based on which we propose and validate a multi-step open-loop control strategy to alternatingly manipulate the direction of the longest axis of the soft magnet and the rotation about it for dexterous 3-DoF orientation manipulation.

Flexible endoscopic instrument for diagnosis and treatment of early gastric cancer

Gastric cancer is a common cancer endangering human life and health worldwide. Early detection and diagnosis of gastric cancer that is normally performed by flexible endoscope can significantly improve the survival rate of patients. However, current endoscopic instruments have some problems, such as limitation of degrees of freedom (DOFs) and lack of surgical triangulation. Meanwhile, the lack of an intraoperative technique for the real-time evaluation of early gastric cancer is also a serious problem. To solve these problems, we have developed a dual-bending flexible endoscopic instrument for the diagnosis and treatment of early gastric cancer. This instrument has a compact structure with a maximum outer diameter of 3 mm and an insertion length of 1220 mm. It has 5 DOFs with a dual-bending function, which can form a surgical operation triangulation to easily perform the endoscopic procedure. Apart from the surgical forceps, the end of the instrument can be equipped with different endoscopic devices to meet the needs of diagnosis and treatment, such as endomicroscopic probes, electrosurgical knives, and laser ablation optical fibers. It is verified that the instrument can carry these devices to complete corresponding tasks, demonstrating the great potential of this instrument in clinical applications.

A Concentric Tube Steerable Drilling Robot for Minimally Invasive Spinal Fixation of Osteoporotic Vertebrae

Spinal fixation with rigid pedicle screws have shown to be an effective treatment for many patients. However, this surgical option has been proved to be insufficient and will eventually fail for patients experiencing osteoporosis. This failure is mainly attributed to the lack of dexterity in the existing rigid drilling instruments and the complex anatomy of vertebrae, forcing surgeons to implant rigid pedicle screws within the osteoporotic regions of anatomy. To address this problem, in this article, we present the design, fabrication, and evaluation of a unique flexible yet structurally strong concentric tube steerable drilling robot (CT-SDR). The CT-SDR is capable of drilling smooth and accurate curved trajectories through hard tissues without experiencing buckling and failure; thus enabling the use of novel flexible pedicle screws for the next generation of spinal fixation procedures. Particularly, by decoupling the control of bending and insertion degrees of freedom (DoF) of the CT-SDR, we present a robotic system that (i) is intuitive to steer as it does not require an on-the-fly control algorithm for the bending DoF, and (ii) is able to address the contradictory requirements of structural stiffness and dexterity of a flexible robot interacting with the hard tissue. The robust and repeatable performance of the proposed CT-SDR have been experimentally evaluated by conducting various drilling procedures on simulated bone materials and animal bone samples. Experimental results indicate drilling times as low as 35 seconds for curved trajectories with 41 mm length and remarkable steering accuracy with a maximum 2% deviation error.

A multifunctional soft robot for cardiac interventions

In minimally invasive endovascular procedures, surgeons rely on catheters with low dexterity and high aspect ratios to reach an anatomical target. However, the environment inside the beating heart presents a combination of challenges unique to few anatomic locations, making it difficult for interventional tools to maneuver dexterously and apply substantial forces on an intracardiac target. We demonstrate a millimeter-scale soft robotic platform that can deploy and self-stabilize at the entrance to the heart, and guide existing interventional tools toward a target site. In two exemplar intracardiac procedures within the right atrium, the robotic platform provides enough dexterity to reach multiple anatomical targets, enough stability to maintain constant contact on motile targets, and enough mechanical leverage to generate newton-level forces. Because the device addresses ongoing challenges in minimally invasive intracardiac intervention, it may enable the further development of catheter-based interventions.

A Kinetostatic Model for Concentric Push-Pull Robots

Concentric push-pull robots (CPPR) operate through the mechanical interactions of concentrically nested, laser-cut tubes with offset stiffness centers. The distal tips of the tubes are attached to each other, and relative displacement of the tube bases generates bending in the CPPR. Previous CPPR kinematic models assumed two tubes, planar shapes, no torsion, and no external loads. In this paper, we develop a new, more general CPPR model accounting for any number of tubes, describing their variable-curvature 3D shape when actuated, including the effects of torsion and external loads. To accomplish this, we employ a modified Kirchhoff rod model for each tube (with offset stiffness center) and embed the constraints of concentricity. We use an energy method to determine robot shape as a function of actuation and external loading. We experimentally validate this kinetostatic model on prototype CPPRs with two tubes and three tubes and non-constant laser-cut patterns that create variable curvature and stiffness. Experimental results agree with the model, paving the way for use of this model in design optimization, planning, and control of CPPRs.

Kirchhoff rod-based three-dimensional dynamical model and real-time simulation for medical-magnetic guidewires

BACKGROUND AND OBJECTIVE

Magnetic guidewire, fabricated from hard-magnetic soft composites, has recently emerged as an appropriate candidate for magnetic actuation systems to perform intravascular surgical navigation, owing to its elastic, magnetically steerable properties and good interphase with biological tissues. A suitable and efficient mathematical model for the magnetic guidewire is essential in the system to execute remote manipulation and active control.

METHODS

This paper presents a real-time Kirchhoff rod-based dynamical modeling approach, the magneto-elastic rod model, to simulate magnetic guidewire, which provides accurate simulations for two- and three-dimensional dynamic deflections induced by external magnetic fields and obtains deformed guidewire shapes in quasi-static status.

RESULTS

The proposed model is capable of describing the intrinsic principles of elastic body actuation by torques generated from the hard-magnetic soft matrix. The effectiveness of the developed model is validated, and the real-time simulation application is conducted via the semi-implicit numerical integration method.

CONCLUSIONS

It has been shown that the presented dynamical model captures large nonlinear deformations and transient responses of the magnetic guidewire in an imitated human blood environment, which could offer robust support for the construction of a simulated magnetically driven surgical system.

A variable stiffness manipulator with multifunctional channels for endoscopic submucosal dissection

PURPOSE

Endoscopic submucosal dissection (ESD) has become the main treatment for early esophageal and gastric cancers, but the insufficient stiffness and large diameter of current devices increase the difficulty in operation. To address the above problems, this study proposes a variable stiffness manipulator with multifunctional channels for ESD.

METHODS

The proposed manipulator has a diameter of just 10 mm and highly integrates a CCD camera, two optical fibers, two channels for instruments, and one channel for water and gas. Additionally, a compact wire-driven variable stiffness mechanism is also integrated. The drive system of the manipulator is designed, and the kinematics and workspace are analyzed. The variable stiffness and practical application performance of the robotic system are tested.

RESULTS

The motion tests verify that the manipulator has sufficient workspace and motion accuracy. The variable stiffness tests show that the manipulator achieves 3.55 times of stiffness variation instantly. Further insertion tests and operation test demonstrates that the robotic system is safe and can satisfy the needs in motion, stiffness, channels, image, illumination, and injection.

CONCLUSION

The manipulator proposed in this study highly integrates six functional channels and a variable stiffness mechanism in a 10 mm diameter. After kinematic analysis and testing, the performance and application prospect of the manipulator are verified. The proposed manipulator can promote the stability and accuracy of ESD operation.

Reduced order modeling and model order reduction for continuum manipulators: an overview

Soft robot's natural dynamics calls for the development of tailored modeling techniques for control. However, the high-dimensional configuration space of the geometrically exact modeling approaches for soft robots, i.e., Cosserat rod and Finite Element Methods (FEM), has been identified as a key obstacle in controller design. To address this challenge, Reduced Order Modeling (ROM), i.e., the approximation of the full-order models, and Model Order Reduction (MOR), i.e., reducing the state space dimension of a high fidelity FEM-based model, are enjoying extensive research. Although both techniques serve a similar purpose and their terms have been used interchangeably in the literature, they are different in their assumptions and implementation. This review paper provides the first in-depth survey of ROM and MOR techniques in the continuum and soft robotics landscape to aid Soft Robotics researchers in selecting computationally efficient models for their specific tasks.

Bioinspiration and Biomimetic Art in Robotic Grippers

The autonomous manipulation of objects by robotic grippers has made significant strides in enhancing both human daily life and various industries. Within a brief span, a multitude of research endeavours and gripper designs have emerged, drawing inspiration primarily from biological mechanisms. It is within this context that our study takes centre stage, with the aim of conducting a meticulous review of bioinspired grippers. This exploration involved a nuanced classification framework encompassing a range of parameters, including operating principles, material compositions, actuation methods, design intricacies, fabrication techniques, and the multifaceted applications into which these grippers seamlessly integrate. Our comprehensive investigation unveiled gripper designs that brim with a depth of intricacy, rendering them indispensable across a spectrum of real-world scenarios. These bioinspired grippers with a predominant emphasis on animal-inspired solutions have become pivotal tools that not only mirror nature's genius but also significantly enrich various domains through their versatility.

Design and Experimental Validation of a 3D-Printed Embedded-Sensing Continuum Robot for Neurosurgery

A minimally-invasive manipulator characterized by hyper-redundant kinematics and embedded sensing modules is presented in this work. The bending angles (tilt and pan) of the robot tip are controlled through tendon-driven actuation; the transmission of the actuation forces to the tip is based on a Bowden-cable solution integrating some channels for optical fibers. The viability of the real-time measurement of the feedback control variables, through optoelectronic acquisition, is evaluated for automated bending of the flexible endoscope and trajectory tracking of the tip angles. Indeed, unlike conventional catheters and cannulae adopted in neurosurgery, the proposed robot can extend the actuation and control of snake-like kinematic chains with embedded sensing solutions, enabling real-time measurement, robust and accurate control of curvature, and tip bending of continuum robots for the manipulation of cannulae and microsurgical instruments in neurosurgical procedures. A prototype of the manipulator with a length of 43 mm and a diameter of 5.5 mm has been realized via 3D printing. Moreover, a multiple regression model has been estimated through a novel experimental setup to predict the tip angles from measured outputs of the optoelectronic modules. The sensing and control performance has also been evaluated during tasks involving tip rotations.

A stiffness-tunable soft actuator inspired by helix for medical applications

PURPOSE

This paper introduces the stiffness-tunable soft actuator (STSA), a novel device that combines a silicone body with a thermoplastic resin structure (TPRS). The STSA's design allows for the variable stiffness of soft robots, significantly increasing their potential for use in medical scenarios such as minimally invasive surgeries (MIS). By adjusting the stiffness of the STSA, it is possible to enhance the robot's dexterity and adaptability, making it a promising tool for performing complex tasks in narrow and delicate spaces.

METHODS

The stiffness of the STSA can be modulated by altering the temperature of the TPRS, which has been inspired by the helix and is integrated into the soft actuator to achieve a broad range of stiffness modulation while maintaining flexibility. The STSA has been designed with both diagnostic and therapeutic functions in mind, with the hollow area of the TPRS serving as an instrument channel for delivering surgical instruments. Additionally, the STSA features three uniformly arranged pipelines for actuation by air or tendon, and can be expanded with more functional chambers for endoscopy, illumination, water injection, and other purposes.

RESULTS

Experimental results show that the STSA can achieve a maximum 30-fold stiffness tuning, providing a significant improvement in load capacity and stability when compared to pure soft actuators (PSAs). Of particular importance, the STSA is capable of achieving stiffness modulation below 45 °C, thereby ensuring a safe entry into the human body and creating an environment conducive to the normal operation of surgical instruments such as endoscope.

CONCLUSION

The experimental findings indicate that the soft actuator with TPRS can achieve a broad range of stiffness modulation while retaining flexibility. Moreover, the STSA can be designed to have a diameter of 8-10 mm, which satisfies the diameter requirements of a bronchoscope. Furthermore, the STSA has the potential to be utilized for clamping and ablation in a laparoscopic scenario, thereby demonstrating its potential for clinical use. Overall, these results suggest that the STSA has significant promise for use in medical applications, particularly in the context of minimally invasive surgeries.

Plug & play origami modules with all-purpose deformation modes

Three basic deformation modes of an object (bending, twisting, and contraction/extension) along with their various combinations and delicate controls lead to diverse locomotion. As a result, seeking mechanisms to achieve simple to complex deformation modes in a controllable manner is a focal point in related engineering fields. Here, a pneumatic-driven, origami-based deformation unit that offers all-purpose deformation modes, namely, three decoupled basic motion types and four combinations of these three basic types, with seven distinct motion modes in total through one origami module, was created and precisely controlled through various pressurization schemes. These all-purpose origami-based modules can be readily assembled as needed, even during operation, which enables plug-and-play characteristics. These origami modules with all-purpose deformation modes offer unprecedented opportunities for soft robots in performing complex tasks, which were successfully demonstrated in this work.

Artificial intelligence meets medical robotics

Artificial intelligence (AI) applications in medical robots are bringing a new era to medicine. Advanced medical robots can perform diagnostic and surgical procedures, aid rehabilitation, and provide symbiotic prosthetics to replace limbs. The technology used in these devices, including computer vision, medical image analysis, haptics, navigation, precise manipulation, and machine learning (ML) , could allow autonomous robots to carry out diagnostic imaging, remote surgery, surgical subtasks, or even entire surgical procedures. Moreover, AI in rehabilitation devices and advanced prosthetics can provide individualized support, as well as improved functionality and mobility (see the figure). The combination of extraordinary advances in robotics, medicine, materials science, and computing could bring safer, more efficient, and more widely available patient care in the future. -Gemma K. Alderton.

Robotic endoscope with double-balloon and double-bend tube for colonoscopy

The insertion of conventional colonoscopes can sometimes cause patients to experience pain during the procedure owing to the stretching of the mesentery. In this study, a prototype of a robotic colonoscope with a double-balloon and double-bend tube based on the conventional double-balloon endoscope was developed to simplify insertion and prevent the overstretching of the colon. Both the outer and inner tubes were confirmed to be free from interference from wires and sheaths. Additionally, all functions such as tip bending, inflation and deflation of the balloons, and actuator-driven pulling and pushing of the inner tube were operated properly. During the insertion test, the device could be reached the cecum of a colon model in approximately 442 s when operated by a non-medical operator. In addition, the device did not overstretch the colon model, thereby suggesting that the insertion mechanism can follow the shape of the colon model. As a result, the developed mechanism has the potential to navigate through a highly-bent colon without overstretching.

Design and Fabrication of a Fiber Bragg Grating Shape Sensor for Shape Reconstruction of a Continuum Manipulator

Continuum dexterous manipulators (CDMs) are suitable for performing tasks in a constrained environment due to their high dexterity and maneuverability. Despite the inherent advantages of CDMs in minimally invasive surgery, real-time control of CDMs' shape during nonconstant curvature bending is still challenging. This study presents a novel approach for the design and fabrication of a large deflection fiber Bragg grating (FBG) shape sensor embedded within the lumens inside the walls of a CDM with a large instrument channel. The shape sensor consisted of two fibers, each with three FBG nodes. A shape-sensing model was introduced to reconstruct the centerline of the CDM based on FBG wavelengths. Different experiments, including shape sensor tests and CDM shape reconstruction tests, were conducted to assess the overall accuracy of the shape-sensing. The FBG sensor evaluation results revealed the linear curvature-wavelength relationship with the large curvature detection of 0.045 mm and a high wavelength shift of up to 5.50 nm at a 90° bending angle in both the bending directions. The CDM's shape reconstruction experiments in a free environment demonstrated the shape-tracking accuracy of 0.216 ± 0.126 mm for positive/negative deflections. Also, the CDM shape reconstruction error for three cases of bending with obstacles was observed to be 0.436 ± 0.370 mm for the proximal case, 0.485 ± 0.418 mm for the middle case, and 0.312 ± 0.261 mm for the distal case. This study indicates the adequate performance of the FBG sensor and the effectiveness of the model for tracking the shape of the large-deflection CDM with nonconstant-curvature bending for minimally invasive orthopedic applications.

Navigation with minimal occupation volume for teleoperated snake-like surgical robots: MOVE

Master-Slave control is a common mode of operation for surgical robots as it ensures that surgeons are always in control and responsible for the procedure. Most teleoperated surgical systems use low degree-of-freedom (DOF) instruments, thus facilitating direct mapping of manipulator position to the instrument pose and tip location (tip-to-tip mapping). However, with the introduction of continuum and snake-like robots with much higher DOF supported by their inherent redundant architecture for navigating through curved anatomical pathways, there is a need for developing effective kinematic methods that can actuate all the joints in a controlled fashion. This paper introduces the concept of navigation with Minimal Occupation VolumE (MOVE), a teleoperation method that extends the concept of follow-the-leader navigation. It defines the path taken by the head while using all the available space surrounding the robot constrained by individual joint limits. The method was developed for the i ² Snake robot and validated with detailed simulation and control experiments. The results validate key performance indices such as path following, body weights, path weights, fault tolerance and conservative motion. The MOVE solver can run in real-time on a standard computer at frequencies greater than 1 kHz.

Toward Continuum Robot Tentacles for Lung Interventions: Exploring Folding Support Disks

Toward the future goal of creating a lung surgery system featuring multiple tentacle-like robots, we present a new folding concept for continuum robots that enables them to squeeze through openings smaller than the robot's nominal diameter (e.g., the narrow space between adjacent ribs). This is facilitated by making the disks along the robot's backbone foldable. We also demonstrate that such a robot can feature not only straight, but also curved tendon routing paths, thereby achieving a diverse family of conformations. We find that the foldable robot performs comparably, from a kinematic perspective, to an identical non-folding continuum robot at varying deployment lengths. This work paves the way for future applications with a continuum robot that can fold and fit through smaller openings, with the potential to reduce invasiveness during surgical tasks.

A Millimeter-Scale Soft Robot for Tissue Biopsy Procedures

While interest in soft robotics as surgical tools has grown due to their inherently safe interactions with the body, their feasibility is limited in the amount of force that can be transmitted during procedures. This is especially apparent in minimally invasive procedures where millimeter-scale devices are necessary for reaching the desired surgical site, such as in interventional bronchoscopy. To leverage the benefits of soft robotics in minimally invasive surgery, a soft robot with integrated tip steering, stabilization, and needle deployment capabilities is proposed for lung tissue biopsy procedures. Design, fabrication, and modeling of the force transmission of this soft robotic platform allows for integration into a system with a diameter of 3.5 mm. Characterizations of the soft robot are performed to analyze bending angle, force transmission, and expansion during needle deployment. In-vitro experiments of both the needle deployment mechanism and fully integrated soft robot validate the proposed workflow and capabilities in a simulated surgical setting.

Unified Robot and Inertial Sensor Self-Calibration

Robots and inertial measurement units (IMUs) are typically calibrated independently. IMUs are placed in purpose-built, expensive automated test rigs. Robot poses are typically measured using highly accurate (and thus expensive) tracking systems. In this paper, we present a quick, easy, and inexpensive new approach to calibrate both simultaneously, simply by attaching the IMU anywhere on the robot's end effector and moving the robot continuously through space. Our approach provides a fast and inexpensive alternative to both robot and IMU calibration, without any external measurement systems. We accomplish this using continuous-time batch estimation, providing statistically optimal solutions. Under Gaussian assumptions, we show that this becomes a nonlinear least squares problem and analyze the structure of the associated Jacobian. Our methods are validated both numerically and experimentally and compared to standard individual robot and IMU calibration methods.

Hyperelastic Modeling and Validation of Hybrid-Actuated Soft Robot with Pressure-Stiffening

Soft robots have gained popularity, especially in intraluminal applications, because their soft bodies make them safer for surgical interventions than flexures with rigid backbones. This study investigates a pressure-regulating stiffness tendon-driven soft robot and provides a continuum mechanics model for it towards using that in adaptive stiffness applications. To this end, first, a central single-chamber pneumatic and tri-tendon-driven soft robot was designed and fabricated. Afterward, the classic Cosserat's rod model was adopted and augmented with the hyperelastic material model. The model was then formulated as a boundary-value problem and was solved using the shooting method. To identify the pressure-stiffening effect, a parameter-identification problem was formulated to identify the relationship between the flexural rigidity of the soft robot and internal pressure. The flexural rigidity of the robot at various pressures was optimized to match theoretical deformation and experiments. The theoretical findings of arbitrary pressures were then compared with the experiment for validation. The internal chamber pressure was in the range of 0 to 40 kPa and the tendon tensions were in the range of 0 to 3 N. The theoretical and experimental findings were in fair agreement for tip displacement with a maximum error of 6.40% of the flexure's length.

A Mixed-Reality-Based Unknown Space Navigation Method of a Flexible Manipulator

A hyper-redundant flexible manipulator is characterized by high degree(s) of freedom (DoF), flexibility, and environmental adaptability. It has been used for missions in complex and unknown spaces, such as debris rescue and pipeline inspection, where the manipulator is not intelligent enough to face complex situations. Therefore, human intervention is required to assist in decision-making and control. In this paper, we designed an interactive navigation method based on mixed reality (MR) of a hyper-redundant flexible manipulator in an unknown space. A novel teleoperation system frame is put forward. An MR-based interface was developed to provide a virtual model of the remote workspace and virtual interactive interface, allowing the operator to observe the real-time situation from a third perspective and issue commands to the manipulator. As for environmental modeling, a simultaneous localization and mapping (SLAM) algorithm based on an RGB-D camera is applied. Additionally, a path-finding and obstacle avoidance method based on artificial potential field (APF) is introduced to ensure that the manipulator can move automatically under the artificial command in the remote space without collision. The results of the simulations and experiments validate that the system exhibits good real-time performance, accuracy, security, and user-friendliness.

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.

Modeling of and Experimenting with Concentric Tube Robots: Considering Clearance, Friction and Torsion

Concentric tube robots (CTRs) are a promising prospect for minimally invasive surgery due to their inherent compliance and ability to navigate in constrained environments. Existing mechanics-based kinematic models typically neglect friction, clearance, and torsion between each pair of contacting tubes, leading to large positioning errors in medical applications. In this paper, an improved kinematic modeling method is developed. The effect of clearance on tip position during concentric tube assembly is compensated by the database method. The new kinematic model is mechanic-based, and the impact of friction moment and torsion on tubes is considered. Integrating the infinitesimal torsion of the concentric tube robots eliminates the errors caused by the interaction force between the tubes. A prototype is built, and several experiments with kinematic models are designed. The results indicate that the error of tube rotations is less than 2 mm. The maximum error of the feeding experiment does not exceed 0.4 mm. The error of the new modeling method is lower than that of the previous kinematic model. This paper has substantial implications for the high-precision and real-time control of concentric tube robots.

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.