Twisted String Actuators Research Articles

Enhancing Maximum Stroke of Twisted String Actuators by Adjusting Twisting Ratio

Enhancing Maximum Stroke of Twisted String Actuators by Adjusting Twisting Ratio

Conductive polymer composites-enable self-sensing twisted string actuators

Twisted string actuators (TSAs) are innovative linear soft actuators that can mimic natural muscle contraction. However, obtaining feedback on their stroke requires cumbersome external sensors that compromise their compliance. We addressed this by developing self-sensing strings using conductive polymer composites (CPCs). The CPC strings exhibit electrical resistance changes in response to strain, enabling stroke sensing by the strings themselves. We fabricated CPCs strings with varying concentrations of multi-walled carbon nanotubes (MWCNTs). Characterization revealed excellent conductivity, tensile strength exceeding 30 N, tunable strain sensitivity via MWCNTs concentration variation, as well as stable and repeatable strain-dependent resistance changes. Optimization via a high-strength core fiber enabled the CPCs strings to withstand over 6[Formula: see text]kg loading with enhanced stroke and minimal resistance variation. We achieved at least a 97.8% linear correlation between resistance change rate and contraction rate in twisting experiments. This research provides a self-contained stroke sensor compatible with high-load soft TSAs, overcoming limitations of external sensors. The simple yet effective sensing mechanism could spur adoption of TSA in robotics.

Direct model parameter identification of twisted string actuators using Nelder-Mead simplex method

A twisted string actuator (TSA) is a simple rotary-to-linear motion converter with a large transmission ratio. This paper presents a simple procedure for direct model parameters identification of TSAs, which accepts the model in initial ODE-based form, while the previous techniques required a complex reformulation of the model. Also, the identification process estimates all unknown or impossible-to-measure parameters directly (not in an arithmetic combination) in the original form of the mathematical model of the TSA, which is a benefit in comparison with common and classic adaptive parameter estimators. The proposed nonlinear identification procedure employs the Nelder–Mead simplex method to minimize the cost function as the core. Moreover, the identification results are verified in different working frequencies. The presented model parameter optimization procedure reduced the deviation between the mathematical model and the real TSA behavior for a set of optimum parameters up to [Formula: see text] in terms of the defined cost function. As an application for the mathematical model of the TSA with the identified parameters, a feedback linearization controller is designed for the position control of the actuator. The simulation and implementation of the controller prove the proper performance of the controller.

Shear stiffening gel-enabled twisted string for bio-inspired robot actuators

A rotary motor combined with fibrous string demonstrates excellent performance because it is powerful, lightweight, and prone to large strokes; however, the stiffness range and force-generating capability of twisted string transmission systems are limited. Here, we present a variable stiffness artificial muscle generated by impregnating shear stiffening gels (STGs) into a twisted string actuator (TSA). A high twisting speed produces a large impact force and causes shear stiffening of the STG, thereby improving the elasticity, stiffness, force capacity, and response time of the TSA. We show that at a twisting speed of 4186 rpm, the elasticity of an STG-TSA reached 30.92 N/mm, whereas at a low twisting speed of 200 rpm, it was only 10.51 N/mm. In addition, the STG-TSA exhibited a more prominent shear stiffening effect under a high stiffness load. Our work provides a promising approach for artificial muscles to coactivate with human muscles to effectively compensate for motion.

Model-based Performance Analysis of Twisted String Actuators with Comparison to Spooled Motor Tendon-driven Actuators

Model-based Performance Analysis of Twisted String Actuators with Comparison to Spooled Motor Tendon-driven Actuators

Twisted string actuation through a conduit: Undesirable behaviors and pre-twist effects

Twisted string actuation through a conduit enhances flexibility, one of the most important features of twisted string actuators (TSAs). It allows power transmission remotely along an arbitrary curved surface, such as the human body Exosuit, while avoiding interference with the natural movement of the wearer. However, TSAs on guided sliding surfaces or inside conduits have not been extensively investigated. This study experimentally investigates TSAs inside a conduit and its undesirable behaviors, namely, pullback and chatter and their causes. Furthermore, this paper proposes a pre-twist method to overcome undesirable behaviors by introducing a certain amount of advanced twists as an initial condition to compensate for any opposite directional twist. Also, investigated the relationship between the required amount of pre-twist and string parameters (radius, length, and stroke) and external conditions (deflection angle and external load). Finally, an online-required pre-twist estimation method is proposed to minimize the performance loss due to the present pre-twist. In addition, the feasibility of these approaches is validated through an experimental comparison study.

Electromechanical Properties of Silver-Plated Yarns and Their Relation to Yarn Construction Parameters.

For signal transmission and sensing in stretchable structures for human motion monitoring or proprioception of soft robots, textiles with electronically conductive yarns are a promising option. Many recent publications employ silver-plated yarns in knits, braids, wovens for strain or pressure sensing purposes as well as heating fabrics or twisted string actuators. Silver-plated yarns are available in a wide range of base materials, yarn counts and twists. These structural properties significantly influence the electrical and electromechanical behavior of such yarns. However, until now little research has been carried out on the yarns themselves. To close this research gap, several variations of a single yarn type are electromechanically characterized. Additionally, tensile tests with synchronous resistance measurements are performed. From these measurements, sensor metrics are derived and calculated to compare the different variants quantitatively.

Tension Control of Twisted String Actuators in Variation of Stiffness and Original Length of Strings

Although several studies have been conducted on the modeling and control of twisted string actuators (TSAs), most have been limited to position control; the studies on tension control are limited. This study proposes an indirect tension control method for TSAs. Through comprehensive loading/unloading experiments involving frequency richness and a wide range of tension inputs, the results showed that the conventional static model is no longer valid with a fixed stiffness and constant original length of the string. Therefore, the proposed method allows the stiffness and original length variation in the static tension model, which is then considered in the control by introducing an estimation method. Second, the proposed method indirectly controls string tension by controlling the rotation angle of the motor. The inverse calculation of the desired rotation angle of the motor to achieve the desired tension is equivalent to adaptively changing feedback gains with respect to the nonlinear varying gear ratio of the TSAs. The proposed estimation method simulated the actual string tension from the low- to high-frequency and from the low- to high-tension regions within a tolerable error range. Therefore, the proposed tension controller demonstrated superior regulating and tracking performance compared with the best-tuned direct proportional–integral–derivative feedback controller in a wide range of desired tensions and bandwidths.

Lightweight Soft Robotic Glove with Whole-Hand Finger Motion Tracking for Hand Rehabilitation in Virtual Reality.

Soft robotic gloves have attracted significant interest in hand rehabilitation in the past decade. However, current solutions are still heavy and lack finger-state monitoring and versatile treatment options. To address this, we present a lightweight soft robotic glove actuated by twisted string actuators (TSA) that provides whole-hand finger motion tracking. We have developed a virtual reality environment for hand rehabilitation training, allowing users to interact with various virtual objects. Fifteen small inertial measurement units are placed on the glove to predict finger joint angles and track whole-hand finger motion. We performed TSA experiments to identify design and control rules, by understanding how their response varies with input load and voltages. Grasping experiments were conducted to determine the grasping force and range of motion. Finally, we showcase an application of the rehabilitation glove in a Unity-based VR interface, which can actuate the operator's fingers to grasp different virtual objects.

Biomimetic Design of a Tendon-Driven Myoelectric Soft Hand Exoskeleton for Upper-Limb Rehabilitation.

Degenerative diseases and injuries that compromise hand movement reduce individual autonomy and tend to cause financial and psychological problems to their family nucleus. To mitigate these limitations, over the past decade, hand exoskeletons have been designed to rehabilitate or enhance impaired hand movements. Although promising, these devices still have limitations, such as weight and cost. Moreover, the movements performed are not kinematically compatible with the joints, thereby reducing the achievements of the rehabilitation process. This article presents the biomimetic design of a soft hand exoskeleton actuated using artificial tendons designed to achieve low weight, volume, and cost, and to improve kinematic compatibility with the joints, comfort, and the sensitivity of the hand by allowing direct contact between the hand palm and objects. We employed two twisted string actuators and Bowden cables to move the artificial tendons and perform the grasping and opening of the hand. With this configuration, the heavy part of the system was reallocated to a test bench, allowing for a lightweight set of just 232 g attached to the arm. The system was triggered by the myoelectric signals of the biceps captured from the user's skin to encourage the active participation of the user in the process. The device was evaluated by five healthy subjects who were asked to simulate a paralyzed hand, and manipulate different types of objects and perform grip strength. The results showed that the system was able to identify the intention of movement of the user with an accuracy of 90%, and the orthosis was able to enhance the ability of handling objects with gripping force up to 1.86 kgf.

Kinematic Modeling and Open-Loop Control of a Twisted String Actuator-Driven Soft Robotic Manipulator

Abstract Realizing high-performance soft robots is challenging because many existing soft or compliant actuators exhibit limitations like fabrication complexity, high power requirement, slow actuation, and low force generation. Due to their high-force output and power efficiency, compactness, and simplicity in fabrication, twisted string actuators (TSAs) have exhibited strong potential in mechatronic and robotic applications. However, they have had limited uses in soft robotics. Consequently, modeling and control of TSA-driven soft robots have not been sufficiently studied. This article presents the first study on the modeling and control of a TSA-driven soft robotic manipulator. A physics-based model was developed to predict the manipulator’s kinematic motion. An inverse model was derived to realize open-loop control. Models that describe the behavior of TSAs were utilized in a novel way to develop the proposed kinematic and inverse models of the soft robot. The proposed modeling and control approaches were experimentally verified to be effective. For example, the modeling and control errors of the bending angle were 1.60 deg (3.11%) and 2.11 deg (3.68%), respectively.

A TEC Cooling Soft Robot Driven by Twisted String Actuators.

Similar to biological muscles in nature, artificial muscles have unique advantages for driving bionic robots. However, there is still a large gap between the performance of existing artificial muscles and biological muscles. Twisted polymer actuators (TPAs) convert rotary motion from torsional to linear motion. TPAs are known for their high energy efficiency and large linear strain and stress outputs. A simple, lightweight, low-cost, self-sensing robot powered using a TPA and cooled using a thermoelectric cooler (TEC) was proposed in this study. Because TPA burns easily at high temperatures, traditional soft robots driven by TPAs have low movement frequencies. In this study, a temperature sensor and TEC were combined to develop a closed-loop temperature control system to ensure that the internal temperature of the robot was 5 °C to cool the TPAs quickly. The robot could move at a frequency of 1 Hz. Moreover, a self-sensing soft robot was proposed based on the TPA contraction length and resistance. When the motion frequency was 0.01 Hz, the TPA had good self-sensing ability and the root-mean-square error of the angle of the soft robot was less than 3.89% of the measurement amplitude. This study not only proposed a new cooling method for improving the motion frequency of soft robots but also verified the autokinetic performance of the TPAs.

Inverse Modeling for Component Selection of Twisted String Actuators

Twisted string actuators (TSAs) have been widely used in numerous mechatronic applications. However, existing literature selects the TSA's components (strings and motors) through ad hoc procedures. The selection of TSA components requires inversion of its mathematical models. This is difficult because many variables are coupled in such a way that prevents direct inversion. This article presents a novel systematic design framework and inversion algorithm for TSAs based on their required performance properties. First, a comprehensive formula to invert the kinetostatic and dynamic models of the TSA is presented. This inversion finds the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TSA-specific properties</i> given the desired performance properties that are <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">common to most actuators</i> . The solution is iteratively solved from a synthesis of existing models that account for string compliance, variable TSA radius, friction, the payload's inertia, and its linear velocity. Second, an algorithm recommends the most suitable motor and string pair from a custom-made database. Third, simulations and experiments evaluated the algorithm's performance under different conditions.

Anthropomorphic Twisted String-Actuated Soft Robotic Gripper With Tendon-Based Stiffening

Realizing high-performance soft robotic grippers is challenging because of the inherent limitations of the soft actuators and artificial muscles that drive them, including low force generation, small actuation range, and poor compactness to name a few. Despite advances in this area, realizing compact soft grippers, which exhibit high dexterity and force output, is still challenging. This article explores using twisted string actuators (TSAs) to drive a soft robotic gripper. TSAs have been widely used in numerous robotic applications, but their inclusion in soft robots has been limited. The proposed design of the gripper was inspired by the human hand, with four fingers and a thumb. Tunable stiffness was implemented in the fingers by using antagonistic TSAs. The fingers' bending angles, actuation speed, blocked force output, and stiffness tuning are experimentally characterized. The gripper achieves a score of 6 on the Kapandji test and recreate 31 of the 33 grasps of the Feix GRASP taxonomy. It exhibits a maximum grasping force of 72 N, which is almost 13 times its own weight. A comparison study reveals that the proposed gripper exhibits equivalent or superior performance compared to other similar soft grippers.

Overtwisting and Coiling Highly Enhance Strain Generation of Twisted String Actuators.

Twisted string actuators (TSAs) have exhibited great promise in robotic applications by generating high translational force with low input torque. To further facilitate their robotic applications, it is strongly desirable but challenging to enhance their consistent strain generation while maintaining compliance. Existing studies predominantly considered overtwisting and coiling after the regular twisting stage to be undesirable-nonuniform and unpredictable knots, entanglements, and coils formed to create an unstable and failure-prone structure. Overtwisting would work well for TSAs when uniform coils can be consistently formed. In this study, we realize uniform and consistent coil formation in overtwisted TSAs, which greatly increases their strain. Furthermore, we investigate methods for enabling uniform coil formation upon overtwisting the strings in a TSA and present a procedure to systematically "train" the strings. To the authors' best knowledge, this is the first study to experimentally investigate overtwisting for TSAs with different stiffnesses and realize consistent uniform coil formation. Ultrahigh molecular-weight polyethylene strings form the stiff TSAs, whereas compliant TSAs are realized with stretchable and conductive supercoiled polymer strings. The strain, force, velocity, and torque of each overtwisted TSA were studied. Overtwisting and coiling resulted in ∼70% strain in stiff TSAs and ∼60% strain in compliant TSAs. This is more than twice the strain achieved through regular twisting. Finally, the overtwisted TSA was successfully demonstrated in a robotic bicep.

Kinematic Modeling of a Twisted-String Actuated Soft Robotic Finger as Part of an Anthropomorphic Gripper

Twisted string actuators (TSAs) generate high tendon-based (muscle-like) linear actuation and forces and have wide operational bandwidth. For these properties, TSAs are well-suited for advanced robotic and mechatronic applications, though their inclusion in soft robots has been limited. We recently employed TSAs to drive an anthropomorphic soft gripper which successfully demonstrated dexterous grasping and manipulation. While the gripper showed superior qualitative performance, the lack of modeling and control strategies limited its realization in a fully autonomous system that could generalize well to new grasping behaviors. As a first step toward this objective, this paper presents modeling strategies for a monolithic soft silicone finger driven by a TSA. A physics-based kinematic model is developed to predict the bending and velocity kinematics of the finger as a function of the TSA's twisting angle. An average error of 2.06° was obtained for the kinematic bending model across different actuation behaviors and an average error of 2.95°/s was measured for the angular velocity model.

A Variable Stiffness Exosuit for Walking Assistance

Robotic exoskeleton takes an important role in walking assistance for subjects with lower extremity impairment. However, most of the existing robotic exoskeletons are bulky and complicated in the mechanical structure, placing a large load on the wearer. In this paper, a soft exosuit with twisted string actuators (TSAs) is designed for walking assistance. The analytic model of the TSA is derived to prove its characteristic of variable stiffness, benefited from which, flexible and compliant assistive torque can be generated to knee joints whilst walking. Furthermore, a human-robot coupling dynamic model is established, and an admittance control strategy is utilized to improve the trajectory tracking performance. Finally, simulations are conducted to verify the proposed robot system.

A Novel Magnetic Transmission for Powerful Miniature Surgical Robots

Untethered magnetically actuated robots present significant advantages for biomedical applications by allowing power to be delivered wirelessly to remote, miniature robots through flesh and bone. Nevertheless, generating enough usable force to interact with their environment remains a challenge: Most millimeter-size magnetic robots achieve forces of much less than 0.1 N, which limits their medical applications. Therefore, a compact, millimeter-scale transmission is needed to amplify the output force. A novel microtransmission system is presented, composed of a driving magnet suspended between two twisted string actuators. An analytical model of the transmission is formulated to predict its behavior under both fixed load and fixed displacement configurations. Experimental measurements are used to validate the predicted maximum achievable force, to quantify the transmission performance over numerous cycles, to determine the effect of different string materials, and to determine the impact of hysteresis and viscoelasticity. Finally, the transmission is integrated into a 3 mm diameter surgical gripper prototype to demonstrate its effectiveness. With only a modest 20 mT of applied magnetic field, the gripper generates 1.09 N gripping force—a factor of 35 improvement in mechanical advantage and a factor of 62 improvement in gripping force compared to a similar size gripper using direct magnetic actuation. This microtransmission for miniature magnetic robots will enable high-strength untethered robots for minimally invasive surgical applications.

A Spine Assistive Robot With a Routed Twisted String Actuator and a Flat-Back Alleviation Mechanism for Lumbar-Degenerative Flat Back

A lumbar-degenerative flat back is a condition caused by a decline in back muscle strength with aging. The symptoms of this condition include severe lower back pain and spinal disorders, which restrict people from performing activities of daily living (ADL). Recently, various wearable robots have been developed to assist the weakened muscles. However, despite their effectiveness, the wearables require either bulky and rigid structures (active wearables) or tend to constrain users’ motion (passive wearables). In addition, the complex biomechanics of the human spine have not been sufficiently investigated during the design process. To address these issues, we propose a human-inspired spine assistive robot with a routed twisted string actuator (RTSA, active element) and a flat-back alleviation mechanism (FAM, passive element). This innovative RTSA conforms to the complex human spine curvature while minimizing friction and assists the ADL with its unique prioritizing characteristics. The human spine-inspired FAM, on the other hand, was designed to prevent spinal disorder injury while performing ADL. The experimental results showed that the proposed system successfully reduced the electromyography signals while performing ADL. Furthermore, the spinal disorder injury during trunk motion could be prevented by reducing the lumbopelvic ratio of the users.

Design, characterisation and validation of a haptic interface based on twisted string actuation.

This paper presents the design and experimental characterisation of a wrist haptic interface based on a twisted string actuator. The interface is designed for controlled actuation of wrist flexion/extension and is capable of rendering torque feedback through a rotary handle driven by the twisted string actuator and spring-loaded cable mechanisms. The interface was characterised to obtain its static and dynamic haptic feedback rendering capabilities. Compliance in the spring and actuation mechanism makes the interface suitable for smooth rendering of haptic feedback of large magnitudes due to the high motion transmission ratio of the twisted strings. Haptic virtual wall rendering capabilities are demonstrated.