Tendon-sheath Mechanism Research Articles

Modeling Backlash-like Hysteresis and Feedforward Control of Tendon-Sheath Mechanism Pair with Arbitrary Shape: Excluding Distal Sensory Input

Abstract The tendon-sheath mechanism (TSM) has garnered attention for its versatile applications in soft robotics, robotic hands, and surgical robots due to its adeptness in transmitting force through tortuous and narrow channels. However, precise control of the TSM is challenging due to its shape-dependent deformation and force generation, highlighting the need to address shape variations in dynamic environments where direct measurement is impractical. This paper introduces a novel methodology leveraging the concept of the equivalent circle in TSM to model its shape under varying conditions. The equivalent circle substitutes an arbitrarily shaped TSM with a circle, whose radius is derived from TSM's deformation and forces measured at the proximal end during calibration. This approach provides a concise and effective framework for understanding and analyzing the distinct characteristics of TSM. Additionally, a control strategy is proposed, utilizing the estimated equivalent circle to adapt to dynamic environments. Experimental results demonstrate promising performance without distal end sensory feedback, with mean percentage errors (MPE) of 0.78% and 2.33% for predicting cumulated curve angle and equivalent circle radius, respectively. Moreover, by utilizing the equivalent circle to calculate and feedforward deadband, effective control is achieved. The root mean square error (RMSE) reduced from 1.31 mm to an average of 0.19 mm in two feedforward experiments, representing an average reduction of 85.5%. These findings shed light on effective control strategies for TSM, offering valuable insights for robotics and surgical applications where TSM shape configurations are uncertain and subject to dynamic change.

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

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

Empirical modeling of hysteresis in a tendon–sheath mechanism on multi-segmented curves

Empirical modeling of hysteresis in a tendon–sheath mechanism on multi-segmented curves

Hysteresis Compensation of Tendon-Sheath Mechanism Using Nonlinear Programming Based on Preisach Model

Hysteresis Compensation of Tendon-Sheath Mechanism Using Nonlinear Programming Based on Preisach Model

Design and position-tracking control of a flexible joint based on the tendon-sheath mechanism

In this study, a flexible joint comprising active and passive driving modes was designed based on the tendon-sheath mechanism. Further, angle sensors and series elastomers (SE) were integrated inside the joint to produce a compact and flexible structure. First, a model of the flexible joint was established based on the involved stiffness relation, and this model was validated using the dSPACE system. Next, to respond to the low control accuracy and poor anti-interference ability of the flexible joints, a sliding-mode controller (SMC) was designed to facilitate the precise position control, as well as achieve improved robustness. However, the flexible joint was prone to considerable tremors when the overall system was subjected to a large load mass. Therefore, a fuzzy-modified adaptive SMC (FMASMC), which adaptively adjusts the SMC parameters, was designed based on the historical-state data of the system. This control method could suppress the trembling phenomenon of the system while improving its control accuracy. Finally, it was experimentally verified that the compliant joint could achieve the expected functions. Compared with the proportional–integral–derivative (PID) and SMC control algorithms, the FMASMC algorithm could effectively overcome the tremors of the compliant actuation system and improve its control accuracy; moreover, it is also suitable for controlling other compliant joints.

Early-stage modeling and analysis of continuum compliant structure for multi-DOF endoluminal forceps using pseudo-rigid-body model

Early detection and treatment of intraluminal diseases enable minimally invasive surgery and can lead to a high cure rate. Advanced devices with multiple degrees of freedom (DOFs) make narrow intraluminal procedures easier and safer. In a previous study, we developed a multi-DOF compliant endoluminal forceps with a tendon-sheath mechanism. The maximum bending stress of this design was reduced by changing the thickness of a compliant hinge in each segment, and the forceps achieved a wide range of motion. However, its deformed shapes with a non-constant curvature, due to a compliant inhomogeneous-thickness hinge structure, hinder fine manipulation in a narrow lumen. Here, we construct an accurate model of this compliant inhomogeneous-thickness hinge structure using pseudo-rigid-body model. In the proposed method, each compliant hinge is represented by a torsion spring and rotational joint, and the deformed shape is estimated from the bending angle caused by the tensile force. We derive the coefficient of dynamic friction by considering the friction between the wire and compliant joint based on a belt friction model. These novel calculations allow to consider individual differences in material properties and surface roughness. We experimentally confirm the feasibility of constructing a highly accurate model with a lower calculation cost than the finite element method. Our proposal seems suitable for developing dexterous forceps and other endoluminal devices, such as catheters, which mitigate operation errors and help approach lesions in narrow lumens.

Optimization Design Method of Tendon-Sheath Transmission Path Under Curvature Constraint

The application requirements of the tendon-sheath mechanism in the field of precision machinery are becoming increasingly extensive. However, the contact friction between the tendon and sheath seriously affects the transmission accuracy. In the case of unavoidable friction, optimizing the tendon transmission path to reduce tension loss and elastic deformation has become an important research direction. In this article, the influence law of the tendon transmission path on the tension and displacement transmission is obtained using the two parameters related to the curvature of the transmission path: total bending angle and equivalent tendon length. Then, based on the optimal control theory and minimum principle, the different transmission path solutions of the minimum tension loss, the minimum tendon deformation, and the coupling of tension and displacement are obtained; the numerical optimization method verifies the correctness of the proposed theory. Finally, an optimal design of a tendon-constrained synchronous rotation mechanism for the manipulator is carried out, and the linkage performance is greatly improved by optimizing the transmission path.

Separable Tendon-Driven Robotic Manipulator with a Long, Flexible, Passive Proximal Section.

This work tackles practical issues which arise when using a tendon-driven robotic manipulator (TDRM) with a long, flexible, passive proximal section in medical applications. Tendon-driven devices are preferred in medicine for their improved outcomes via minimally invasive procedures, but TDRMs come with unique challenges such as sterilization and reuse, simultaneous control of tendons, hysteresis in the tendon-sheath mechanism, and unmodeled effects of the proximal section shape. A separable TDRM which overcomes difficulties in actuation and sterilization is introduced, in which the body containing the electronics is reusable and the remainder is disposable. An open-loop redundant controller which resolves the redundancy in the kinematics is developed. Simple linear hysteresis compensation and re-tension compensation based on the physical properties of the device are proposed. The controller and compensation methods are evaluated on a testbed for a straight proximal section, a curved proximal section at various static angles, and a proximal section which dynamically changes angles; and overall, distal tip error was reduced.

Hysteresis Modeling and Compensation for Tendon-Sheath Mechanisms in Robot-Assisted Endoscopic Surgery Based on the Modified Bouc-Wen Model With Decoupled Model Parameters

The tendon-sheath mechanism (TSM) has been widely applied in flexible endoscopy (FE) and natural orifice transluminal endoscopic surgery (NOTES) owing to its advantages of remote force and displacement transmission, size reduction, compactness, and convenient implementation. However, the positioning accuracy of TSMs is highly restrained by the motion hysteresis due to the complex friction condition between the tendon and sheath. The hysteresis phenomenon has posed significant challenges for modeling and controlling TSMs. This paper proposes a modified Bouc-Wen-based mathematical model to characterize the asymmetric hysteresis loop with distinct inflection points. The model parameters are decoupled, facilitating identification and reducing computational costs. Moreover, the model has retained the Bouc-Wen model structure, allowing for efficient derivation of the feedforward compensator based on the inverse multiplicative structure. The compensator was derived and cascaded with the TSM system to suppress the hysteresis phenomenon. Totally 120 trials of experiments were conducted to validate the proposed model and the feedforward control scheme on the two TSMs with different accumulated curvatures of 180∘ and 360∘. The results indicated that the proposed method achieved a 25.5% and 43.9% lower estimation and compensation error than the classical Bouc-Wen model. Further, it is worth noting that the model parameter identification time consumption has been significantly reduced to 5.8ms. The proposed model and the feedforward compensator can effectively linearize the TSM system and further facilitate delicate operations in robot-assisted surgical procedures.

General compensation control method of flexible manipulator driven by tendon-sheath mechanism

Flexible manipulator has been widely used because of its flexibility. In addition, the tendon-sheath mechanism has the advantages of compact structure and strong flexibility, and it can be used as the driving transmission mode of the flexible manipulator. However, the nonlinear and hysteretic characteristics of the tendon-sheath mechanism directly affect the motion accuracy of the manipulator. Firstly, the kinematic and static models of the flexible manipulator are analyzed considering the influence of multi section coupling. In addition, the mechanical transmission process of the tendon-sheath mechanism is analyzed. On this basis, a general feedforward compensation method for the flexible manipulator is established. The proposed model-based compensation control method can be applied to all flexible manipulators, and it is of great significance to promote the practical application of the manipulator.

2.5-mm articulated endoluminal forceps using a compliant mechanism.

Gastrointestinal cancer can be treated using a flexible endoscope through a natural orifice. However, treatment instruments with limited degrees of freedom (DOFs) require a highly skilled operator. Articulated devices useful for endoluminal procedures, such as endoscopic submucosal dissection and biopsy, have been developed. These devices enable dexterous operation in a narrow lumen; however, they suffer from limitations such as large size and high cost. To overcome these limitations, we developed a 2.5-mm articulated forceps that can be inserted into a standard endoscope channel based on a compliant mechanism. The compliant mechanism allows the device to be compact and affordable, which is possible due to its monolithic structure. The proposed mechanism consists of two segments, 1-DOF grasping and 2-DOF bending, that are actuated by tendon-sheath mechanisms. A prototype was designed based on finite element analysis results. To confirm the effectiveness of the proposed mechanism, we fabricated the prototype using a 3D printer. A series of mechanical performance tests on the prototype revealed that it achieved the following specifications: (1) DOF: 1-DOF grasping + 2-DOF bending, (2) outer diameter: 2.5 mm, (3) length of the bending segment: 30 mm, and (4) range of motion: [Formula: see text] to [Formula: see text] (grasping) and [Formula: see text] to [Formula: see text] (bending). Finally, we performed a tissue manipulation test on an excised porcine colon and found that a piece of mucous membrane tissue was successfully resected using an electric knife while being lifted with the developed forceps. The results of the evaluation experiment demonstrated a positive feasibility of the proposed mechanism, which has a simpler structure compared to those of other conventional mechanisms; furthermore, it is potentially more cost-effective and is disposable. The mechanical design, prototype implementation, and evaluations are reported in this paper.

Recurrent Neural Network With Preisach Model for Configuration-Specific Hysteresis Modeling of Tendon-Sheath Mechanism

The tendon-sheath mechanism (TSM) is widely used for flexible surgical robots owing to its ability to transfer motion through complicated paths and small volumes. However, precise motion control of the robots is difficult owing to the nonlinear characteristics of the TSM due to hysteresis, friction, deformation, backlash, etc. The hysteretic behavior exhibits a certain tendency depending on the shape of the TSM. In this study, our goal is to derive a hysteresis model that applies to the arbitrary geometry of a single-curve TSM. A hysteresis model was formulated by combining the Preisach hysteresis model, which has the structure of a weighted sum, and a recurrent neural network (RNN). Hysteresis output data were experimentally gathered for several representative shapes of the TSM to train the model. During data preprocessing, the data in the section where the hysteresis characteristic was prominent was augmented. Hyperparameter tuning using the grid search method was conducted to improve the performance of the model. The results indicate that the proposed model successively learned the tendency of configuration-specific hysteresis and adapted to arbitrary shapes of a single-curve TSM, even with shapes that the model did not learn.

ViO-Com: Feed-Forward Compensation Using Vision-Based Optimization for High-Precision Surgical Manipulation

Tendon-sheath mechanisms offer a means for a flexible surgical robot to be operated efficiently in restricted environments, for example, the long and narrow paths inside human organs. However, nonlinear hysteresis interferes with the precise motion control of a flexible robot. Generally, the characteristics of hysteresis can change due to changes in cable-related effects and robot shapes, which increase the difficulty associated with achieving precise control of surgical robots. Although several methods have been proposed to solve this problem, most of these methods offer limited performance and are unstable in realistic situations. In this letter, we present a vision-based optimized feedforward compensation (ViO-Com) scheme for a cable-driven surgical robot that reduces hysteresis as a practical approach, regardless of any unmeasured hysteresis while maintaining stable motion. A CycleGAN and a Siamese CNN were used to estimate the actual joint angle of a surgical manipulator, and the Bouc–Wen model with optimized parameters was used for feed-forward compensation. The results obtained using a real surgical robot platform K-FLEX suggest that the performance of ViO-Com is superior to that of vision-based feedback compensation under various hysteresis condition, and its accuracy is improved by 67%.

Learning Fingertip Force to Grasp Deformable Objects for Soft Wearable Robotic Glove With TSM

Soft wearable robotic gloves based on tendon-sheath mechanism are widely developed for assisting people with a loss of hand mobility. For these robots, knowing the fingertip forces applied to deformable objects is crucial in successfully grasping them without causing excessive deformations. Existing studies presented methods to predict fingertip force applied to rigid objects only using information from the actuation system. However, forces applied to deformable objects are subject to non-linearity and hysteresis in relation to the objects' stiffness, which further complicates the problem. Therefore, this letter proposes a deep-learning model that can accurately estimate the fingertip forces applied to deformable objects using motor encoder values, motor current, and wire tension. Our model is based on an integrated system of Long Short-Term Memory models that 1) estimates stiffness of the grasped objects and 2) incorporates the estimated stiffness for predicting the fingertip forces. When evaluated using a TSM-based soft wearable robot, the proposed model recorded fingertip force estimation of 0.702 N RMSE, achieving 45% increase in accuracy compared to LSTM that does not consider the objects' stiffness. The applicability of our method was evaluated by estimating the fingertip forces applied to common daily items and performing real-time force control.

Neural Decoding for Target Detection Using Multi-View Methods

Tendon–sheath mechanism (TSM) has inherent advantages in the development of flexible robotic systems because of its simplicity, safety, flexibility, and ease of transmission. However, the control of TSM is challenging due to the presence of nonlinearities, namely friction, backlash-like hysteresis and the time-varying configuration of the TSM during its operations. Existing studies of TSM found in the literature only address tendon transmission under the assumption of fixed configuration and a complex inverse model of backlash is required. In order to flexibly use the system in a wider range of applications, the aforementioned nonlinear effects have to be characterized for the purpose of compensation. In this paper, we endeavor to address these issues by presenting a series of controller strategies, namely a feedforward control scheme under the assumption of known backlash-like hysteresis profile, and an adaptive control scheme to characterize the nonlinearities with unknown backlash hysteresis and uncertainties. The proposed control schemes do not require information of the tendon–sheath configurations, which is challenging to obtain in practice, in the compensation structures. In the absence of output position feedback, a simple direct inverse model-based feedforward has been used that efficiently reduce the tracking errors. The feedforward compensation does not require any complex algorithm for the inverse model. In the presence of output position feedback, a nonlinear adaptive controller has been developed to enhance the tracking performances of the TSM regardless of the random change in the tendon–sheath configurations during compensation. In addition, exact values of the model parameters are not required. They are estimated online during the operations. A dedicated experimental setup is introduced to validate the proposed control approaches. The results show that the proposed control schemes significantly improve the tracking performances for the TSM in the presence of uncertainties and time-varying configurations during the operations. There is a significant decrease of 0.0158 rad2 (before compensation) to smaller value of 0.0012 rad2 (use feedforward control) and 8.2815 × 10−5 rad2 (use nonlinear controller) after compensation.

Design, Fabrication, and Hysteresis Modeling of Soft Microtubule Artificial Muscle (SMAM) for Medical Applications

Robotic artificial muscles (RAMs) are promising power sources for medical fields such as surgical robotics. However, existing RAMs are challenged by scalability, material costs and fabrications. The nonlinear hysteresis in fluid-driven RAMs causes oscillations in open-loop systems. To circumvent these limitations, this letter introduces hydraulically soft microtubule artificial muscle (SMAM) that is low-cost and scalable, yet simple to fabricate. The SMAM, which only requires a flexible silicone microtube and a hollow micro-coil, is elongated or contracted under a fluid pressure. The SMAM presents an ideal candidate for flexible robotic systems such as endoscopic surgical robots. Experiments are conducted to characterize the SMAMs. Results show that the hysteresis profiles between the input syringe plunger position and output position are stable regardless of its configuration, as opposed to the highly variable responses for the tendon-sheath mechanisms. A new nonlinear model is developed to characterize the asymmetric hysteresis phenomena of the SMAM. Compared to the Bouc-Wen hysteresis models, the developed model presents a better capture of hysteresis. To demonstrate the muscle capability, a SMAMs-driven pulley and a flexible surgical arm are given. The new SMAM and its asymmetric hysteresis model are expected to provide a path for the development of rapidly efficient and low-cost soft actuators for use in flexible medical devices and surgical robotic systems.

Muscle-like contraction control of tendon-sheath artificial muscle

The development of artificial muscles has focused on a high energy–weight ratio and soft structures, however, little work has been done towards muscle-like contraction behaviors. This unfortunately leads to a lack of comfort and safety, which is especially important for robotic applications like orthotics and exoskeletons. In this paper, we propose a contraction control method for a tendon-sheath artificial muscle to contract and relax like biological muscles. In view of the nonlinear transmission characteristics of the tendon-sheath artificial muscle, a transmission model is established and its accuracy is verified through experiments. A muscle-like contraction control method is then proposed based on the transmission model and the Hill-type muscle model. Through this method, the contraction force of the tendon-sheath artificial muscle can be adjusted according to the output displacement and velocity of the tendon-sheath mechanism estimated by the transmission model. Isometric contraction and quick-release experiments are then conducted. The experimental results demonstrate that this control method allows the tendon-sheath artificial muscle to contract with specific muscle-like force–length and force–velocity properties.

A Sigmoid-Colon-Straightening Soft Actuator With Peristaltic Motion for Colonoscopy Insertion Assistance: Easycolon

A colonoscopy is the most typical method to inspect for colorectal cancer; however, inserting colonoscopes in nonfixed sites, such as the sigmoid colon, requires very skilled insertion techniques. Since the sigmoid colon is one of the most difficult nonfixed sites for insertion, straightening it is a major step in colonoscopy. Previous studies have proposed various methods to assist the colonoscopy insertion process, but there are still challenges that must be addressed in clinical environments. The goal of this study was to assist colonoscopy operators to straighten the sigmoid colon using peristaltic motions generated with a soft actuator mounted on a commercial colonoscope. The peristaltic motions of the proposed system were combined with expanding and extending behaviors, and the straightening strategy was defined based on the analysis of the sigmoid colon handling process of colonoscopy. The peristaltic motions of the soft actuator were implemented using two balloons and a tendon-sheath mechanism. The colon shortening speed was measured to be about 80 mm/min, which contributed to the straightening of the sigmoid colon, thereby helping significantly with the process of colonoscopy.

Dynamic modeling and system identification of internally actuated, small-sized continuum robots

Small-sized continuum robots (CRs) have shown promising applications in multiple fields, including minimally invasive surgeries. This paper contributes to the field by presenting dynamic modeling and system identification of internally actuated, small-sized CRs in which continuous interactions between the internal actuation mechanisms and the flexible backbones are considered. First, a dynamic model of a flexible backbone sheath is developed. Next, an equivalent discrete model is identified to simulate the dynamics of CRs with continuous interactions. Moreover, based on the existing friction models of passive tendon-sheath mechanisms, the friction model within the proposed discrete model is modified to better resemble the continuity of the interaction. A prismatic ablation catheter is then used as the benchmark for the experimental study, in which parameters for the handle, shaft, and the proposed discrete model for its bending section are considered unknown. The identified model estimates the catheter motion with a maximum error of 4.5 mm at the tip position, which represents 5.6% of the length of the bending section of our experimental catheter.

Learning-Based Fingertip Force Estimation for Soft Wearable Hand Robot With Tendon-Sheath Mechanism

Soft wearable hand robots with tendon-sheath mechanisms are being actively developed to assist people with lost hand mobility. For these robots, accurately estimating fingertip forces leads to successful object grasping. An approach can utilize information from actuators assuming quasi-static environments. However, non-linearity and hysteresis with regards to the dynamic changes of the tendon-sheath mechanism hinder accurate fingertip force estimation. This paper proposes a learning-based method to estimate fingertip forces by integrating dynamic information of motor encoders, wire tension, and sheath bending angles. The model is modified from Long Short-Term Memory by incorporating a residual term that governs the dynamic changes in sheath bending angles. Using a tendon-driven soft wearable hand robot, the proposed model obtained RMSE less than 0.44 N. It was further evaluated under criteria ranging from different object sizes, bending angle ranges, and forces. Finally, a repeatability test (0.46 N in RMSE), real-time applicability (125 Hz), and force control (12.7% in MAPE) were performed to verify the feasibility of the proposed method.