Enabling Robotic Capsule Endoscopy Through Effective in-Body Capsule Localization

A critical problem for wireless capsule endoscopy is to be able to correlate a received image with a location, in order to more precisely locate a pathological condition (such as a lesion, or a tumor) inside the gastrointestinal tract and guide a potential subsequent surgical intervention. We treat the problem of determining the location and orientation parameters of a wireless capsule endoscope inside the human gastrointestinal tract through magnetic techniques. Considering the emerging trend in wireless capsule endoscopy towards remotely maneuverable robotic devices (also known as robotic capsule endoscopy), solving the problem of fast, accurate localization of the capsule becomes even more critical. It is also vital that the performance of different localization algorithms be characterized effectively in a repeatable manner in a controlled environment. Towards this goal, we present a design for a novel cyber-physical system to characterize the magnetic localization performance in robotic capsule endoscopy. We present some sample results for localization performance. The results indicate that highly accurate in-body localization of the capsule (with approximately 3.1 mm localization and 2.2° orientation error) is possible.

A Computational Approach for Internal Tendon Routing Channels in a Tendon-Driven Continuum Joint

Tendon-driven continuum soft robots are currently applied in research and are given a promising perspective for future applications. For the routing of the tendons from the actuator to the point where the loading is demanded, two routing possibilities exist in the literature: internal routing of the tendons with the help of structurally embedded Bowden sheaths and external tendon routing where the tendon is not in contact with the soft structure. The application of the latter is a clear disadvantage for applications due to the high risk of interference with the tendon, for example, causing the tendon to break. The first option on the other hand introduces high friction forces into the tendon transmission and affects the elastic characteristic of the continuum and therefore the desired workspace of the system. This article overcomes the aforementioned problems by integrating tendon routings within tendon channels eroded from the continuum structure by a model-based design method. The channels within the continuum structure are computed a priori such that the tendons do not interact with the continuum while moving through its workspace. Overall, a new model-based method for tendon channel design is introduced and a corresponding manufacturing process is established. A continuum joint module prototype is designed to enable roll-pitch-yaw motions with a large accessible workspace. The capabilities of the system are measured in experiments using an external camera for the range of motion. Moreover, walking experiments on the ANYmal robot from ETHZ are presented.

Registration, Path Planning and Shape Reconstruction for Soft Tools in Robot-Assisted Intraluminal Procedures: A Review

BACKGROUND

Robot and navigation systems can relieve surgeon's difficulties in delicate and safe operation in tortuous lumens in traditional intraluminal procedures (IP). This paper aims to review the three key components of these systems: registration, path planning and shape reconstruction and highlight their limitations and future perspectives.

METHODS

An electronic search for relevant studies was performed in Web of Science and Google scholar databases until 2024.

RESULTS

As for 2D-3D registration in IP, we focused on analysing feature extraction. For path planning, this paper proposed a new classification method and focused on selection of planning space and the establishment of path cost. Regarding shape reconstruction, the pros and cons of existing methods are analysed and methods based on fibre optic sensors and electromagnetic (EM) tracking are focused on.

CONCLUSION

These three technologies in IP have made great progress, but there are still challenges that require further research.

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.

Cosserat Rod-Based Tendon Friction Modeling, Simulation, and Experiments for Tendon-Driven Continuum Robots

Traditional tendon-driven continuum robot (TDCR) models based on Cosserat rod theory often assume that tendon tension is a continuous wrench along the backbone. However, this assumption overlooks critical factors, including the discrete arrangement of disks, the segmented configuration of tensioned tendons, and the friction between tendons and guide holes. Additionally, tendon forces are not continuous but discrete, concentrated wrenches, with the frictional force magnitude and direction varying based on the TDCR's bending configuration. We propose a TDCR modeling method that integrates Cosserat rod theory with a finite element approach to address these limitations. We construct a Cosserat rod model for the robot's backbone, discretize the tendon geometry using the finite element method (FEM), and incorporate friction modeling between tendons and guide holes. Furthermore, we introduce an algorithm to determine the direction of friction forces, enhancing modeling accuracy. This approach results in a more realistic and comprehensive mathematical representation of TDCR behavior. Numerical simulations under various tendon-routing scenarios are conducted and compared with classical TDCR models. The results indicate that our friction-inclusive model improves accuracy, yielding an average configuration deviation of only 0.3% across different tendon routings. Experimental validation further confirms the model's accuracy and robustness.

Snake-Like Robot Workspace Solving Method Based on Improved Monte Carlo Method

The method is applicable for solving the obstacle avoidance workspace of a snake-like robot working on high-voltage transmission cables, based on an improved Monte Carlo method, to address the issues of uneven distribution of scattered points, difficulty in extracting point cloud boundaries, and insufficient accuracy in traditional Monte Carlo methods. The proposed method first generates a seed workspace for the snake-like robot using traditional Monte Carlo method and then envelops the seed workspace with a cube and divides it into several smaller cubes that contain points in the workspace equally. Next, Gaussian distribution probability density function is used to extend and sample the seed workspace of the robot, generating the workspace of the snake-like robot. Finally, the α - shape algorithm is used to extract the point cloud boundaries of the snake-like robot workspace and calculate its volume, accurately determining the workspace. Simulation experiments comparing the reconstructed surface obtained from the α - shape algorithm with the point cloud of the snake-like robot workspace show high accuracy.

Instant variable stiffness in cardiovascular catheters based on fiber jamming

Variable stiffness (VS) has revolutionized miniature surgical instruments, including cardiovascular catheters for minimally invasive surgeries (MISs), enabling advanced capabilities in stiffness modulation and multi-curvature bending. However, existing VS catheters with phase-changing materials are slow in softening and stiffening rates (≈90 s), which can lead to substantial increase in surgery duration. To address the slow stiffness change, we propose a VS catheter based on fiber jamming (FJ) that achieves instant stiffness changes (≤300 ms), enabling seamless catheter operations without delays. Moreover, our catheter, incorporating hundreds of ultrathin fibers into a slender 2.3-mm catheter body, achieves up to 6.5-fold stiffness changes. With adequate stiffness change, our two-segment catheter achieves complex bending profiles within seconds. In addition, the FJ-based design does not require electric currents or heating inside the human body, minimizing patient risks. This FJ-based VS catheter, with instantaneous response, adequate stiffness change, and enhanced safety, can potentially establish benchmarks in MIS, allowing medical practitioners to effectively address formidable diseases.

State of the Art and Development Trend of Laparoscopic Surgical Robot and Master Manipulator

BACKGROUND

In recent years, laparoscopic surgical robots have rapidly developed. However, most focus on the overall robotic systems, with few summaries on the laparoscopic surgical robots and the master manipulators.

METHODS

This paper provides a summary and analysis of typical laparoscopic surgical robots, including the strengths and limitations of existing laparoscopic surgical robots. Additionally, the master manipulators are analysed and summarised from four aspects: structural design and optimization, time-varying delays, tremor suppression and force feedback. Further classification and summary are made based on the different methods used in each study.

RESULTS

Laparoscopic surgical robots and the master manipulators still have some limitations. Therefore, the development trends of the laparoscopic surgical robots and the master manipulators are discussed from four aspects: structural materials, remote surgery, intelligence and human-machine interaction.

CONCLUSION

With the continuous advancement of technology, laparoscopic surgical robots will play an increasingly important role in the field of surgery.

Towards Design and Development of an MRI Conditional Robot to Enable Curvilinear Transperineal Prostate Biopsy

BACKGROUND

In-bore MRI prostate biopsy offers improved visualisation and detection of significant prostate cancer; however, it is not widely practiced in cancer diagnosis due to its associated costs.

METHODS

This work introduces the first prototype towards a 7-degrees-of-freedom (DOF) MRI-conditional piezoelectrically actuated robotic system for transperineal prostate biopsy. The robot enables needle insertions in the desired trajectories. Kinematic and static models of the active needle as well as automated control of the robot are presented.

RESULTS

It is shown that the controller can force the needle to realize the reference sine and triangular bending angles with an accuracy of 1.78 and 1.88°, respectively, in air. The trajectory tracking capability of the system in free space is shown with an RMS error of 0.86 mm and a standard deviation of 0.36 mm.

CONCLUSIONS

The robot's capability to steer the needle towards target inside a phantom and extract a sample was evaluated.

Closing the Loop on Concentric Tube Robot Design: A Case Study on Micro-Laryngeal Surgery

Concentric tube robots (CTRs) are well-suited to address the unique challenges of minimally invasive surgical procedures due to their small size and ability to navigate highly constrained environments. However, uncertainties in the manufacturing process can lead to challenges in the transition from simulated designs to physical robots. In this work, we propose an end-to-end design workflow for CTRs that considers the often-overlooked impact of manufacturing uncertainty, focusing on two primary sources - tube curvature and diameter. This comprehensive approach incorporates a two-step design optimization and an uncertainty-based selection of manufacturing tolerances. Simulation results highlight the substantial influence of manufacturing uncertainties, particularly tube curvature, on the physical robot's performance. By integrating these uncertainties into the design process, we can effectively bridge the gap between simulation and real-world performance. Two hardware experiments validate the proposed CTR design workflow. The first experiment confirms that the performance of the physical robot lies within the simulated probability distribution from the optimization, while the second experiment demonstrates the feasibility of the overall system for use in micro-laryngeal surgical tasks. This work not only contributes to a more comprehensive understanding of CTR design by addressing manufacturing uncertainties, but also creates a new framework for robust design, as illustrated in the context of micro-laryngeal surgery.

SAM: Semi-Active Mechanism for Extensible Continuum Manipulator and Real-Time Hysteresis Compensation Control Algorithm

BACKGROUND

Cable-driven continuum manipulators (CDCMs) enable scar-free procedures but face limitations in workspace and control accuracy due to hysteresis.

METHODS

We introduce an extensible CDCM with a semi-active mechanism (SAM) and develop a real-time hysteresis compensation control algorithm using a temporal convolution network (TCN) based on data collected from fiducial markers and RGBD sensing.

RESULTS

Performance validation shows the proposed controller significantly reduces hysteresis by up to 69.5% in random trajectory tracking test and approximately 26% in the box pointing task.

CONCLUSION

The SAM mechanism enables access to various lesions without damaging surrounding tissues. The proposed controller with TCN-based compensation effectively predicts hysteresis behaviour and minimises position and joint angle errors in real-time, which has the potential to enhance surgical task performance.

Development of a Variable-Pitch Flexible-Screw-Driven Continuum Robot (FSDCR) with Motion Decoupling Capability

Tendon-driven continuum robots suffer from crosstalk of driving forces between sections, typically resulting in motion coupling between sections, which affects their motion accuracy and complicates the control strategies. To address these issues, this article proposes a mechanically designed variable-pitch flexible-screw-driven continuum robot (FSDCR) that enables motion decoupling between sections. The continuum section of the FSDCR comprises a series of orthogonally arranged vertebrae and is driven by customized variable-pitch flexible screws. The variable-pitch flexible screws apply driving forces and constraints to several threaded vertebrae in the continuum section, improving positioning accuracy and loading capacity. The flexible screws effectively balance the driving force and torque within one section through antagonistic torsional actuation, thereby achieving motion decoupling between sections. Characterization experiments have been conducted to compare the motion accuracy and load capacity of the variable-pitch FSDCR with those of the constant-pitch FSDCR. The results demonstrate that the variable-pitch FSDCR exhibits improved positioning accuracy, minimizing an average error of 0.79 mm (0.60% relative to its total length), which is 82.09% lower than that of the constant-pitch FSDCR. The load capacity of the variable-pitch FSDCR is enhanced by up to 129.09% compared with the constant-pitch FSDCR. Experiments on the motion decoupling performance of the FSDCR show that the maximum motion coupling error is 0.32 mm (0.24% relative to the section length). Additionally, the motion coupling error is minimally influenced by the rotational speed of the screw. Finally, a three-section FSDCR is constructed, and its load capacity and motion flexibility are demonstrated.

Double-spiral as a bio-inspired functional element in engineering design

Spiral, one of the most well-known functional patterns in nature that can be observed in structures such as the proboscis of lepidoptera and snail shells or as vortices forming in flowing fluids, has long served as a source of inspiration for humans in the creation of numerous spiral-based designs. Double-spiral is a design derived from spirals, which has been previously presented and utilized as a compliant joint. Advantageous properties of double-spirals, such as easily adjustable design, multiple degrees of freedom, reversible extensibility, and tunable deformability make them promising candidates for the development of mechanically intelligent structures that exhibit unique behavior and reach desired functions, such as soft grippers, continuum manipulators, energy-dissipative structures, and foldable metamaterials. In this article, we first develop the Double-Spiral Design software to facilitate the design and modeling of double-spirals. We then design and manufacture five different spiral-based structures using three-dimensional (3D) printing, including (1) a freeform passive gripper, (2) a highly extensible enveloping gripper, (3) a mechanical interlocking structure, (4) an adaptive energy-dissipative structure, and (5) a compliant planar joint. Through practical experimentation, we test the functionality of the developed structures and showcase the potential of double-spirals for being used in various technical applications. This study represents a significant step towards a better understanding of double-spirals and demonstrates their broad but unexplored potential in engineering design.

Submillimeter fiber robots capable of decoupled macro-micro motion for endoluminal manipulation

Endoluminal and endocavitary intervention via natural orifices of the body is an emerging trend in medicine, further underpinning the future of early intervention and precision surgery. This motivates the development of small continuum robots to navigate freely in confined and tortuous environment. The trade-off between a large range of motion and high precision with concomitant actuation cross-talk poses a major challenge. Here, we present a submillimeter-scale fiber robot (~1 mm) capable of decoupled macro and micro manipulations for intervention and operation. The thin optical fibers, working both as mechanical tendons and light waveguides, can be pulled/pushed to actuate the macro tendon-driven continuum robot and transmit light to actuate the liquid crystal elastomer-based micro built-in light-driven parallel robot. The combination of the decoupled macro and micro motions can accomplish accurate cross-scale motion from several millimeters down to tens of micrometers. In vivo animal studies are performed to demonstrate its positioning accuracy of precise micro operations in endoluminal or endocavitary intervention.

Numerical study of effective parameters on deformation and coalescence of ferrofluid droplets under uniform magnetic field

This research examines different numerical techniques for modeling ferrofluids in a non-magnetic liquid subjected to homogeneous and steady magnetic field. It particularly compares the conservative level set method with the Volume of Fluid (VOF) and Simple Coupled Level Set and Volume of Fluid (SCLSVOF) methods. By comparing these methods with experimental data, we established the superiority of the utilized method in this study. Several case studies were conducted to evaluate how a homogeneous magnetic actuation affects ferrofluid dynamics, considering parameters such as initial droplet size, surface tension coefficient, and magnetic susceptibility. Additionally, the study explored the coalescence of two falling ferrofluid droplets under the combined effects of an external magnetic field and gravity. The conservative level set method was shown to be extendable to three-dimensional environments, unlike the standard level set method. The novelty of this work lies in demonstrating that the conservative level set method is particularly effective for ferrofluids, accurately capturing their complex dynamics. The main novelty of this article lies in demonstrating the precision of Conservative Level Set Method while utilizing a reduced number of equations compared to other works. This reduction in complexity enhances the method's efficiency without compromising precision, making it especially suited for applications requiring both speed and accuracy, such as model-based control systems.

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.

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.

Closed-Loop Control of a Tendon-Driven Active Needle for Tip Tracking at Desired Bending Angle for High-Dose-Rate Prostate Brachytherapy

Prostate cancer is the second most common malignancy in American men. High-dose-rate brachytherapy is a popular treatment technique in which a large, localized radiation dose is used to kill cancer. Utilization of curvilinear catheter implantation inside the prostate gland to provide access channels to host the radiation source has shown superiority in terms of improved dosimetric constraints compared to straight needles. To this aim, we have introduced an active needle to curve inside the prostate conformal to the patient's specific anatomical relationship for improved dose distribution to the prostate and reduced toxicity to the organs at risk (OARs). This work presents closed-loop control of our tendon-driven active needle in water medium and air using the position feedback of the tip obtained in real time from an ultrasound (US) or an electromagnetic (EM) tracking sensor, respectively. The active needle consists of a compliant flexure section to realize bending in two directions via actuation of two internal tendons. Tracking errors using US and EM tracker are estimated and compared. Results show that the bending angle of the active needle could be controlled using position feedback of the US or the EM tracking system with a bending angle error of less than 1.00 degree, when delay is disregarded. It is concluded that the actuation system and controller, presented in this work, are able to realize a desired bending angle at the active needle tip with reasonable accuracy paving the path for tip tracking and manipulation control evaluations in a prostate brachytherapy.

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%.

Quasi-static Path Planning for Continuum Robots By Sampling on Implicit Manifold

Continuum robots (CR) offer excellent dexterity and compliance in contrast to rigid-link robots, making them suitable for navigating through, and interacting with, confined environments. However, the study of path planning for CRs while considering external elastic contact is limited. The challenge lies in the fact that CRs can have multiple possible configurations when in contact, rendering the forward kinematics not well-defined, and characterizing the set of feasible robot configurations is non-trivial. In this paper, we propose to perform quasi-static path planning on an implicit manifold. We model elastic obstacles as external potential fields and formulate the robot statics in the potential field as the extremal trajectory of an optimal control problem. We show that the set of stable robot configurations is a smooth manifold diffeomorphic to a submanifold embedded in the product space of the CR actuation and base internal wrench. We then propose to perform path planning on this manifold using AtlasRRT*, a sampling-based planner dedicated to planning on implicit manifolds. Simulations in different operation scenarios were conducted and the results show that the proposed planner outperforms Euclidean space planners in terms of success rate and computational efficiency.

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.

Unified Shape and External Load State Estimation for Continuum Robots

Continuum robots navigate narrow, winding passageways while safely and compliantly interacting with their environments. Sensing the robot's shape under these conditions is often done indirectly, using a few coarsely distributed (e.g. strain or position) sensors combined with the robot's mechanics-based model. More recently, given high-fidelity shape data, external interaction loads along the robot have been estimated by solving an inverse problem on the mechanics model of the robot. In this paper, we argue that since shape and force are fundamentally coupled, they should be estimated simultaneously in a statistically principled approach. We accomplish this by applying continuous-time batch estimation directly to the arclength domain. A general continuum robot model serves as a statistical prior which is fused with discrete, noisy measurements taken along the robot's backbone. The result is a continuous posterior containing both shape and load functions of arclength, as well as their uncertainties. We first test the approach with a Cosserat rod, i.e. the underlying modeling framework that is the basis for a variety of continuum robots. We verify our approach numerically using distributed loads with various sensor combinations. Next, we experimentally validate shape and external load errors for highly concentrated force distributions (point loads). Finally, we apply the approach to a tendon-actuated continuum robot demonstrating applicability to more complex actuated robots.

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.