Search Results (46)

Structural heart interventions require precise navigation through tortuous and dynamic cardiac anatomies. However, current guide sheaths often lack sufficient maneuverability for positioning additional catheters. To address these limitations, this paper presents the design and evaluation of a robotic guide sheath with a dual-bendable, compressible tip. The sheath is capable of navigating complex cardiac anatomies for multiple valve interventions. The system consists of a soft continuum sheath tip driven by tendons, a laser-cut compact motorized actuation bed, and a joystick-controlled tendon actuation mechanism. A constant-curvature kinematic model maps actuation inputs to tip bending in 3D, while a custom software interface enables real-time control. Mechanical evaluation (tension, maximum bending, and contraction tests) demonstrated low actuation tension requirements (0.78 N), a wide bending range (from 80° to 90°), and promising tip compressibility (average 5 mm). Trajectory-following tests showed good accuracy, with an average error of 3.34 mm. Catheter guidance trials further validated the sheath’s ability to navigate to the right atrium and guide additional catheters effectively. This work presents a proof-of-concept robotic guide sheath with enhanced maneuverability and adaptability, establishing a foundation for future integration of sensing, automation, and clinical applications. Full article

Continuum robots have garnered significant attention for their high flexibility and adaptability to complex environments. However, achieving the same level of high-precision control as rigid robots remains a significant challenge. This paper introduces an innovative Multi-Segment Extendable Soft Manipulator (MSESM) that employs a pneumatic–tendon hybrid drive mechanism. The design, utilizing off-the-shelf industrial bellows and 3D-printed components, allows the manipulator to achieve an extension ratio of up to 156.85%. By adopting a differential stiffness design, its bending stiffness was increased by approximately 4–5 times, its axial stiffness was increased by approximately 10 times, and its torsional resistance was enhanced, preventing inter-segment coupling during motion. At the control level, this paper proposes a hybrid control method that integrates a Constant Curvature (CC) physical prior with a data-driven neural network. Experimental results show that in tracking rectangular, triangular, and circular trajectories, this hybrid method reduced the average tracking error by 60.43% compared to a purely neural network-based controller, with the error reduction for the rectangular trajectory reaching 74.19%. This research validates a practical and effective approach for creating soft manipulators that successfully merge high flexibility with high-precision control. Full article

This study presents a quasi-static optimization framework for the pressure-based control of a multi-segment soft continuum manipulator. The proposed method circumvents traditional curvature and length-based modeling by directly identifying the quasi-static input–output relationship between actuator pressures and the 6-DoF end-effector pose. Experimental data were collected using a high-frequency electromagnetic tracking system under monotonic pressurization to minimize hysteresis effects. Transfer functions were identified for each coordinate–actuator pair using the System Identification Toolbox in MATLAB, and optimal actuator pressures were computed analytically by solving a constrained quadratic program via a manual active-set method. The resulting control strategy achieved sub-millimeter positioning error while minimizing the number of actuators engaged. The approach is computationally efficient, sensor-minimal, and fully implementable in open-loop settings. Despite certain limitations due to sensor nonlinearity and actuator hysteresis, the method provides a robust foundation for feedforward control and the real-time deployment of soft robots in quasi-static tasks. Full article

Soft continuum robots are constructed from soft and compliant materials and can provide high flexibility and adaptability to various applications. They have theoretically infinite degrees of freedom (DOFs) and can generate highly nonlinear behaviors, which leads to challenges in accurately modeling and controlling their deformation, compliance, and behaviors. Inspired by animals, embodied intelligence utilizes physical bodies as an intelligent resource for information processing and task completion and offloads the computational cost of central control, which provides a unique approach to understanding and modeling soft robotics. In this study, we propose a theoretical framework to explain and guide distributed sensing enabled embodied intelligence for soft finger manipulation from a physics-based perspective. Specifically, we aim to provide a theoretical foundation to guide future sensor design and placement by addressing two key questions: (1) whether and why the state of a specific material point such as the tip trajectory of a soft finger can be predicted using distributed sensing, and, (2) how many sensors are sufficient for accurate prediction. These questions are critical for the design of soft and compliant robotic systems with embedded sensing for embodied intelligence. In addition to theoretical analysis, the study presents a feasible approach for real-time trajectory prediction through optimized sensor placement, with results validated through both simulation and experiment. The results showed that the tip trajectory of a soft finger can be predicted with a finite number of sensors with proper placement. While the proposed method is demonstrated in the context of soft finger manipulation, the framework is theoretically generalizable to other compliant soft robotic systems. Full article

Magnetic soft continuum robots (MSCRs) have broad application advantages in vascular intervention; however, current MSCRs still face challenges in navigating the narrower and tortuous structure of the cerebral vasculature. To address this challenge, we propose a tapered MSCR (T-MSCR), which is designed to facilitate smooth navigation through microvascular structures via its miniature tip. Specifically, to optimize its bending ability, we combine the Gray Wolf Optimizer (GWO) with the Euler–Bernoulli beam theory and introduce a Discrete GWO (DGWO) approach to optimize the distribution of magnetic particles within the T-MSCR. We then demonstrate the optimization process of the T-MSCR’s bending ability, comparing and analyzing its deflection angle and deformation characteristics, highlighting its capability to enter microvasculars. Furthermore, we demonstrate the magnetic steering and path selection capabilities of T-MSCR in a two-dimensional vascular model and its navigation performance in real-scale human vascular models. Finally, biocompatibility tests confirm that T-MSCR exhibits no toxicity to human cells, thereby laying a solid foundation for its clinical application. The proposed T-MSCR design and optimization are expected to provide a more efficient and feasible solution for future cerebrovascular interventions. Full article

Soft modular biomimetic robots, driven by flexible actuators, are extensively used in various fields due to their excellent flexibility, environmental adaptability, and isomorphism. However, existing flexible modules typically possess no more than two degrees of freedom for structural limitations. In this study, a three-degree-of-freedom biomimetic segment driven by water hydraulic artificial muscles (WHAMs) and supported by springs was proposed, achieving integrated and modular design. The continuum robot composed of this segment can execute earthworm-, snake-, and elephant trunk-biomimetic motion modes based on operational environmental constraints. During long-distance operational tasks, distinct segments of the continuum robot can adopt varying biomimetic configurations to meet specific requirements. The closed-loop control characteristic tests were conducted on a single segment to evaluate its motion characteristics. The isomorphic master controller was designed based on the motion range of a single segment, with the maximum bending angle deviation between the master controller and biomimetic segment not exceeding 4°, and the system demonstrating favorable stability. Full article

This paper comprehensively reviews the latest advances in hydrogel-based continuum soft robots. Hydrogels exhibit exceptional flexibility and adaptability compared to traditional robots reliant on rigid structures, making them ideal as biomimetic robotic skins and platforms for constructing highly accurate, real-time responsive sensory interfaces. The article systematically summarizes recent research developments across several key dimensions, including application domains, fabrication methods, actuator technologies, and sensing mechanisms. From an application perspective, developments span healthcare, manufacturing, and agriculture. Regarding fabrication techniques, the paper extensively explores crosslinking methods, additive manufacturing, microfluidics, and other related processes. Additionally, the article categorizes and thoroughly discusses various hydrogel-based actuators responsive to solute/solvent variations, pH, chemical reactions, temperature, light, magnetic fields, electric fields, hydraulic/electro-osmotic stimuli, and humidity. It also details the strategies for designing and implementing diverse sensors, including strain, pressure, humidity, conductive, magnetic, thermal, gas, optical, and multimodal sensors. Finally, the paper offers an in-depth discussion of the prospective applications of hydrogel-based continuum soft robots, particularly emphasizing their potential in medical and industrial fields. Concluding remarks include a forward-looking outlook highlighting future challenges and promising research directions. Full article

Inspired by the characteristics of living organisms with soft bodies and flexibility, continuum robots, which bend their robotic bodies and adapt to different shapes, have been widely introduced. Such robots can be used as manipulators to handle objects by wrapping themselves around them, and they are expected to have high grasping performance. However, their infinite degrees of freedom and soft structure make modeling and controlling difficult. In this study, we develop a tendon-driven continuum robot system with color-based posture sensing. The robot is driven by dividing the continuum body into two parts, enabling it to grasp objects by flexible motions. For posture sensing, each joint is painted in a different color, and the 3D coordinates of each joint are detected by a stereo camera for estimating the 3D shape of the robotic body. By taking a video of the robot in actuation and using image processing to detect joint positions, we succeeded in obtaining the posture of the entire robot in experiments. We also robustly demonstrate the grasping manipulation of an object using the redundant structure of the continuum body. Full article

Soft arms, characterized by their compliance and adaptability, have gained significant attention in applications ranging from industrial automation to biomedical fields. Modeling these systems presents unique challenges due to their high degrees of freedom, nonlinear behavior, and complex material properties. This review provides a comprehensive overview of three primary modeling approaches: numerical methods, analytical techniques, and data-driven models. Numerical methods, including finite element analysis and multi-body dynamics, offer precise but computationally expensive solutions for simulating soft arm behaviors. Analytical models, rooted in continuum mechanics and simplified assumptions, provide insights into the fundamental principles while balancing computational efficiency. Data-driven approaches, leveraging machine learning and artificial intelligence, open new avenues for adaptive and real-time modeling by bypassing explicit physical formulations. The strengths, limitations, and application scenarios of each approach are systematically analyzed, and future directions for integrating these methodologies are discussed. This review aims to guide researchers in selecting and developing effective modeling strategies for advancing the field of soft robotic arm design and control. Full article

Soft robots are gaining increasing attention in current robotics research due to their continuum structure. However, accurately recognizing and reproducing the shape of such continuum robots remains a challenge. In this paper, we propose a novel approach that combines contour extraction with camera reconstruction to obtain shape features. Neural networks are employed to model the relationship between motor inputs and the resulting shape output. A simulation environment is established to verify the shape estimation and shape control of the flexible continuum. The outcomes demonstrate that this approach effectively predicts and reproduces the shape of flexible continuum robots, providing a promising solution for continuum shape control. Full article

Continuous robots have attracted more and more attention from the robotics community due to their high degree of flexibility and pliability, and have shown great potential for application in a variety of fields. With the continuous progress of material science, control technology, and artificial intelligence, the performance and application range of soft robotics have been further expanded, in which the cable drive has the advantages of large workspace, high flexibility, etc. The cable-driven soft robotic arm serves as an ultra-redundant robot that can operate in cramped and confined environments. In this paper, a cable-driven soft robot based on soft continuums and a cross gimbal is presented. The kinematics of the cable-driven soft robot is modeled and the mapping relations of the kinematics are solved by the D–H method and piecewise constant curvature, and the relations between the cable length, joint angle, and pose are further derived. Finally, the motion space of the cable-driven soft robot in the three-dimensional coordinate system is obtained by MATLAB2021b, and the single-segment soft body is simulated and analyzed using ADAMS to compare the theoretical data with the actual data and verify the reliability of this structure and method. Full article

Continuum joints use structural elastic deformations to enable joint motion, and their intrinsic compliance and inherent mechanical robustness are envisioned for applications in which the robot, the human, and the environment need to be safe during interaction. In particular, the intrinsic compliance makes continuum joints a competitor to soft articulated joints, which require additional integrated spring elements. For soft articulated joints incorporating rigid and soft parts, natural motions have been investigated in robotics research to exploit this energy-efficient motion property for cyclic motions, e.g., locomotion. To the best of the author’s knowledge, there is no robotic system to date that utilizes the natural motion of a continuum joint under periodic excitation. In this paper, the resonant behavior of a tendon-driven continuum joint under periodic excitation of the torsional axis is experimentally investigated in a functional sense. In the experiments, periodic inputs are introduced on the joint side of a tendon driven continuum joint with four tendons. By modulating the pretension of the tendons, both the resonant frequency and the gain can be shifted, from 3 to 4.3 Hz and 2.8 to 1.4, respectively, in the present experimental setup. An application would be the rotation of a humanoid torso, where gait frequencies are synchronized with the resonant frequency of the continuum joint. Full article

Magnetic soft continuum robots (MSCRs) hold significant potential in fulfilling the requirements of vascular interventional robots, enabling safe access to difficult-to-reach areas with enhanced active maneuverability, shape morphing capabilities, and stiffness variability. Their primary advantage lies in their tether-less actuation mechanism that can safely adapt to complex vessel structures. Existing commercial MSCRs primarily employ a magnetic-pull strategy, which suffers from insufficient driving force and a single actuation strategy, limiting their clinical applicability. Inspired by the inchworm crawling locomotion gait, we herein present a novel MSCR that integrates a magnetic sinusoidal actuation mechanism with adjustable frequency and kirigami structures. The developed MSCRs consist of two permanent magnets connected by a micro-spring, which is coated with a silicone membrane featuring a specific notch array. This design enables bio-inspired crawling with controllable velocity and active maneuverability. An analytical model of the magnetic torque and finite element analysis (FEA) simulations of the MSCRs has been constructed. Additionally, the prototype has been validated through two-dimensional in-vitro tracking experiments with actuation frequencies ranging from 1 to 10 Hz. Its stride efficiency has also been verified in a three-dimensional (3D) coronary artery phantom. Diametrically magnetized spherical chain tip enhances active steerability. Kirigami skin is coated over the novel guidewire and catheter, not only providing proximal anchorage for improved stride efficiency but also serving similar function as a cutting balloon. Under the actuation of an external magnetic field, the proposed MSCRs demonstrate the ability to traverse bifurcations and tortuous paths, indicating their potential for dexterous flexibility in pathological vessels. Full article

Bio-inspired robots with elongated anatomy, like eels, are studied to discover anguilliform swimming principles and improve the robots’ locomotion accordingly. Soft continuum robots replicate animal–environment physics better than noncompliant, rigid, multi-body eel robots. In this study, a slender soft robot was designed and tested in an actual swimming experiment in a still-water tank. The robot employs soft pneumatic muscles laterally connected to a flexible backbone and activated with a rhythmic input. The position of seven markers mounted on the robot’s backbone was recorded using QualiSys^® Tracking Manager (QTM) 1.6.0.1. The system was modeled as a fully coupled fluid–solid interaction (FSI) system using COMSOL Multiphysics^® 6.1. Further data postprocessing and analysis were conducted, proposing a new mode decomposition algorithm using simulation data. Experiments show the success of swimming with a velocity of 28 mm/s and at a frequency of 0.9 Hz. The mode analysis allowed the modeling and explanation of the fluctuation. Results disclose the presence of traveling waves related to anguilliform waves obtained by the superposition of two main modes. The similarities of the results with natural anguilliform locomotion are discussed. It is concluded that soft robot undulation is ruled by dynamic modes induced by robot–environment interaction. Full article

Soft continuum robots, with their flexible and deformable structures, excel in tasks requiring delicate manipulation and navigation through complex environments. Accurate shape sensing is vital to enhance their performance, safety, and adaptability. Unlike rigid sensors, soft sensors conform to the robot’s flexible surfaces, ensuring consistent measurement of shape and motion. This paper introduces a new approach using soft e-textile resistive sensors, which integrate seamlessly with the robot’s structure. These sensors adjust their resistance in response to movements, capturing multidimensional force data. A deep Convolutional Neural Network (CNN) decodes the sensor signals, enabling precise shape estimation and control. Our findings indicate that soft e-textile sensors may surpass traditional rigid sensors in shape sensing and control, significantly improving the functionality of soft continuum robots in challenging applications. Full article