Soft Robotics

Magnetic soft continuum robots (MSCRs) offer the possibility for wireless manipulation, compliant shape-forming, and miniaturization to the milli- and submillimeter scales. This presents them as an attractive choice in the development of robotic guidewires and catheters for endovascular applications. However, few approaches have considered strategies for geometric modification to enhance navigation and therapeutic delivery. These aspects are of high relevance for applications such as intra-arterial chemotherapeutic delivery. Here, we present an octopus tentacle-inspired MSCR with a monolithic material composition, tapered geometry of ≤ 2 mm, and integrated microchannels. We consider the suitability of a discrete elastic modeling approach alongside finite element based and material point method (MPM) simulations for capturing the deflection behavior of the tapered design under magnetic actuation. The MPM demonstrates the greatest accuracy, with root mean square errors in tip angle between 2.74° and 5.28°. For higher taper designs, experimental results highlight improved deflection under low magnetic field strengths (<5 mT) and an improved workspace at high actuation angles (up to 320°). We subsequently utilize tapered designs with a 0.66 mm distal tip diameter and embedded axial and lateral microchannel networks for localized drug simulant delivery in a neurovascular tumor phantom. We demonstrate significant improvements in localized drug delivery along specific vascular pathways in comparison to systemic intra-arterial delivery.

This article proposes a bioinspired soft coil-wrap gripper (CWG) that achieves concurrent enhancements in load capacity and object adaptability through innovative biomimetic structural design. The gripper incorporates a dual-layer pneumatic architecture: The primary structure comprises an elongated pneumatic chamber with an elastic coating layer, facilitating adaptive contour wrapping around target objects through a biomimetic coiling mechanism. An auxiliary end pneumatic chamber amplifies localized pressure postwrapping, ensuring optimal contact interface and grasping stability. By engineering contact layers with differential friction coefficients (higher inner layer versus lower outer layer), the gripper initiates a frictional self-locking effect during the wrapping process, thereby substantially improving grasping robustness. Experimental validation demonstrates that under pneumatic pressures of 0.1 MPa, the CWG effectively manipulates irregular objects spanning 25–120 mm in size, achieving a maximum payload capacity of 310 N. This research introduces a novel concept for soft grippers by using frictional self-locking to achieve a load capacity that far exceeds the actuation capability.

To test food, drug formulations, and medical devices, extensive research has focused on developing in vitro gastric simulators. Existing simulators range from rigid mechanical systems to flexible polymer-based designs, each with distinct limitations in replicating the stomach’s complex biomechanical properties. While soft pneumatic actuators provide a foundation for soft robotics-based systems, achieving biomimetic functionality requires control strategies that address both contraction motility precision and compliant interaction dynamics. In this study, we integrate admittance control with finite-time state-dependent Riccati equation (FT-SDRE) and propose a compliant and robust combined force and displacement control for a soft actuator used in robotic gastric simulator. This approach enables a more biomimetic simulation of smooth muscle in gastrointestinal (GI) system when the actuators contact the contents and can help reduce excessive stress on the soft actuator. A three-phase contact model is proposed to describe the force-deformation behavior of the actuator while interacting with the contents, followed by experimental validation. The novel admittance-controlled FT-SDRE enhances both safety and physiological realism in soft tissue interaction. Experimental validation was conducted using three objects: an irregular-shaped gelatin sample, a regular-shaped gelatin sample (same material, different geometry), and an air-filled latex balloon. Compared with nonadmittance FT-SDRE control, the admittance-controlled FT-SDRE reduced 11.19% to 38.46% average contact force according to different objects. Across all tests, the time spent above a force threshold was reduced by 35–39%, which highlights the potential of the proposed method to improve safety, adaptability, and biomimicry in next-generation in vitro gastric simulation platforms.

Fabric-based soft gloves, due to their safety, light weight, and compliance, exhibit promising potential in assisting individuals with hand impairments. However, most existing soft gloves focus solely on finger flexion and extension, with limited consideration for thumb assistance. This restricts their effectiveness in tasks requiring extensive workspace and dexterous manipulation. In this work, we present a new class of fabric-based soft glove with 15 degrees of freedom (DOFs), including finger flexion/extension, thumb abduction/adduction, thumb opposition/reposition, and finger abduction. The high-DOF fabric-based soft glove integrates bidirectional fabric-based pneumatic actuators (FPAs) for finger flexion/extension, X-crossing pneumatic artificial muscles (X-PAMs) for thumb assistance, and Y-shaped bladed FPAs for finger abduction. To enhance the thumb tip workspace, we optimize the X-PAM positioning by modeling thumb kinematics from an anatomical perspective. The experimental results show that the optimized passive workspace of the thumb, assisted by the glove, encompasses approximately 70% of its active workspace. Through our mirror control system, we further demonstrate the glove’s capability to perform complex gestures and versatile grasping tasks with various object geometries, sizes (0.1–11.5 cm), and masses (1.7–500.0 g). The glove supports both power and precision grasps, as well as fine manipulations.

Shape memory alloys (SMAs) or shape memory polymers (SMPs) enable soft actuators to achieve advanced adaptabilities applied in soft robotics. However, actuators that combine multiple shape memory materials struggle to achieve complex deformation effects and stiffness variations with effective control strategies. To achieve controllable, shape adaptation, and programmed deforming behavior, this study proposes an integrated control strategy for an SMA–SMP based programmable morphing structure used as an actuator in soft robotics. To achieve precise control over programming deformations and stiffness variation, a multi-target thermal sensing method (MTTSM) was proposed, integrated into an interaction-driven control framework. Based on MTTSM, the coordinated actuation between the SMA springs and the SMP structure is realized, enabling standby of preheating, stepping with programmed deformations, and dynamic stiffness changes. In addition, to achieve dynamic monitoring of deformed states, the co-training-based monitoring system is developed for collaboration, enabling the use of multisensor fusion for position estimation in the absence of end-effectors that can directly measure the deformed structure of the flexible body. In conclusion, the proposed integration strategy of MTTSM and the cotraining monitoring system offers a control solution for integrating multiple shape memory materials into morphing structures as smart actuators applied to soft robotic applications.

Multimodal soft grippers can adapt grasping strategies to diverse environments, yet integrating sensors under large, coupled deformations remains challenging. Inspired by the mechanosensation of sea anemones and their ability to swallow, this article presents a soft gripper that integrates eight toroidal optical waveguides to realize three modes—contacting, expansion, and swallowing—with continuous proprioceptive feedback. Deformation-induced optical attenuation, processed by machine-learning pipelines, enables perception of object shape, hardness, and surface texture. Experiments show a 0.04 N detection limit, a 0.006 N resolution, a 55 ms response time, and sensitivity >1.4 dB/N, with machine-learning classification achieving >89% accuracy. Mode-specific experiments demonstrate sensing across the entire soft gripper with integrated optical waveguides. The outer surface localizes contact after inflation, the inner surface provides circumferential contact sensing of irregular objects during swallowing; and the pedal interface at the base distinguishes surface hardness and texture, achieving perception on the outer, inner, and bottom interfaces. We also demonstrate multi-object swallowing that grasps and counts 1–4 transparent bottles in real-time and a breakfast task that switches grasping modes to grasp a bowl and cup, swallowing fragile items without damage. These results show that our design enables mode-switching interactive perception and expands opportunities for soft robotics in fragile product handling and laboratory automation.

Among various soft actuators, soft pneumatic actuators (SPAs) powered by pressurized gases have been widely adopted due to their structural simplicity, ease of fabrication, and ability to generate diverse and adaptable motions. However, conventional mechanical compressors and chemical reaction-based pneumatic sources that supply pressurized gas to these actuators often generate substantial acoustic noise and heat, limiting their practical use. In this study, we propose an electronics-free, near-silent, and low-heat pneumatic source that integrates endothermic–exothermic chemical reactions to balance heat generation while producing pressurized gas. By only using passive mechanical components that autonomously regulate the reaction process, the pneumatic source achieved a steady output pressure of 7 bar and a flow rate of 6 liters per minute through the chemical reactions between phosphoric acid and cesium bicarbonate. The proposed pneumatic source operated with minimal temperature rise (maximum 36°C) and low acoustic noise of 40 dBA, comparable to the ambient noise of a quiet residential environment. The proposed approach demonstrates an enthalpy-balanced acid–bicarbonate system for combining endothermic and exothermic reactions to achieve thermally balanced and noise-suppressed pneumatic operation. Therefore, the proposed concept can serve as a practical and versatile pneumatic source for driving a wide range of SPAs.

As robotic systems increasingly operate in unstructured, cluttered, and previously unseen environments, there is a growing need for manipulators that combine compliance, adaptability, and precise control. This work presents a real-time hybrid rigid–soft continuum manipulator system designed for robust open-world object reaching in such challenging environments. The system integrates vision-based perception and 3D scene reconstruction with shape-aware motion planning to generate safe trajectories. A learning-based controller drives the hybrid arm to arbitrary target poses, leveraging the flexibility of the soft segment while maintaining the precision of the rigid segment. The system operates without environment-specific retraining, enabling direct generalization to new scenes. Extensive real-world experiments demonstrate consistent reaching performance with errors below 2 cm across diverse cluttered setups, highlighting the potential of hybrid manipulators for adaptive and reliable operation in unstructured environments.

Soft eversion-based growing robots, also known as vine robots, are a subclass of soft continuum robots that navigate their environment through tip extension—an eversion-based growth mechanism inspired by climbing plants. A deeper understanding of the underlying physics and dynamics of this unique locomotion strategy is crucial for expanding the applicability of soft eversion-based growing robots in complex and constrained environments. Despite their potential, comprehensive dynamic models that capture the full system behavior, including internal pressure dynamics and the pneumatic supply system, remain limited. In this study, we develop a first-principles-based dynamic model of a pressure-driven soft eversion-based growing robot, incorporating both the internal pressure evolution and the flow dynamics of the pneumatic supply system. The proposed model is simulated and experimentally validated on custom-built soft eversion-based growing robots. The proposed model demonstrates excellent predictive capability, achieving a root mean square error (RMSE) of 0.066 m, corresponding to about 5.5% of the final everted length. These findings highlight the critical importance of integrating both pressure and flow dynamics in modeling soft eversion-based growing robots to enable improved control strategies and deeper insight into their physical behavior.

Shape memory alloys (SMAs) are highly suitable for flexible and soft robots due to their lightweight nature, high power density, and miniaturization potential. However, the design of SMA-based continuum bending joints for robotic applications is often restricted by the inherent trade-offs in their mechanical characteristics. In this work, we present an integrated multicomponent framework that encompasses four submodels, including bending angle, load-deflection stiffness, distal twisting angle, and output force for antagonistic SMA wire bending joints. The framework unifies all submodels under a common temperature input set and systematically clarifies their coupled relationships, providing quantitative insight into their trade-offs. A model-based optimal design methodology is then developed for the SMA bending joint, balancing the different mechanical performance metrics to deliver an optimal joint design that satisfies the task requirements. Experiments on the SMA bending joint with optimal design parameters validate the accuracy of various submodels. Two additional nonoptimal prototypes were experimentally evaluated against the optimized design, validating the feasibility of the proposed optimal design methodology. The integrated multicomponent modeling framework and optimal design methodology address the intricate coupling effects inherent in antagonistic SMA wires, minimizing the need for iterative prototyping and facilitating the adoption of SMA wires in flexible and soft robots.

Soft-legged mobile robots require actuators that can deliver both rapid extension and bending motions while generating high-output force to meet the demands of load-bearing and diverse locomotion tasks. This study introduces a bistable origami-inspired soft pneumatic actuator (BOSPA) featuring multiple deformation modes tailored for soft robotic locomotion. The actuator consists of a 3D-printed, inflatable soft Miura-origami tube structure with two parallel air chambers and strategically placed elastic rings in both horizontal and vertical orientations to enable bistability. By programming the driving air pressure of the chambers, the actuator achieves multiple deformation modes, including linear extension, bending, and coupled bending/extension motions with snap-through bistability transitions. To demonstrate the capabilities of the BOSPA, this study designed four soft robots employing different numbers of BOSPA with versatile locomotion modalities. The reversible and rapid linear jump-extension motion of the BOSPA enables a jumping robot to achieve continuous jumps reaching 0.65 body lengths (BL) at 1.25 Hz. A crawling robot using the same actuator achieves straight-line motion at 1.22 BL/s and can ascend inclined surfaces up to 14°. A tripod robot with three BOSPA realizes rolling locomotion by dynamically shifting its center of mass and can also perform peristaltic crawling or leg-propelled movement. A quadruped robot equipped with four BOSPA modules demonstrates rapid pacing and trotting gaits for effective obstacle traversal and can carry payloads up to 20 times the weight of its soft BOSPA legs, with a maximum load capacity of 2 kg.

Fluidic circuits offer an effective route to electronics-free control in soft robots. However, limited tunability of hysteresis in existing fluidic valves constrains their ability to exploit the analog characteristics of pressure inputs. As a result, many fluidic circuits rely on digital control with multiple external inputs, increasing system complexity. Here, we develop a hysteresis-guided pressure-threshold encoder (PTE) composed of hysteresis-tunable valves (HTVs) to convert a programmed pressure input into multiple digital outputs. By customizing the hysteresis behavior of the HTVs, the PTE provides a well-defined resolution for detecting variations in the input pressure. The PTE allows two modes of input-pressure programming: automated sequencing with an electronic device and manual sequencing with a mechanical pressure regulator. Integration of the PTE as an input module within digital fluidic circuits verifies its scalability and compatibility. Experimental demonstrations on soft joints and soft robotic hands confirm that the PTE enables multiactuator control using minimal inputs. Overall, this work provides an effective encoding method to reduce the number of external pressure lines from n to 2, providing a new approach for compact, electronics-free, and scalable control systems in soft robotics.

With the rapid development of soft robotics, there is a growing demand for compact, high-performance, and flexible actuators. Pneumatic actuators are particularly favored by researchers due to their high efficiency, low cost, and ease of fabrication. However, the existing pneumatic actuators are faced with challenges such as large volume, low actuating frequency, and insufficient propulsion. For the first time, this work presents a novel thin-plate pneumatic actuator based on prestressed principles, featuring an efficient energy storage and release mechanism. The actuator consists of a prestretched layer, a constrained layer, and a chamber (PCC), with a total thickness of less than 1 mm. Therefore, the elastic potential energy is preserved in the prestretched film within the actuator body, which enables high actuating frequency and large propulsion. Effects of key structural parameters on the propulsion of the PCC actuator are investigated by a mathematical model, finite element analysis, and experiments to further elucidate its energy storage and release mechanism. Moreover, the PCC actuator is applied to realize a soft gripper, a prestressed hinge, and a wireless jellyfish-like robot, whose performances are verified by experiments. Results demonstrate the high flexibility and rapid response of the soft gripper and prestressed hinge. In particular, the gripper is capable of stably gripping objects 40 times its weight for extended periods. In addition, the wireless jellyfish-like robot achieves an upward swimming speed of 58.03 mm/s, which is superior to the existing soft jellyfish-like robots of similar size. Overall, the PCC actuator features a lightweight structure and high energy storage capacity, providing significant potential for innovative applications in soft robotics.

Medical care in the gastrointestinal (GI) tract is a major global issue. Soft actuators are expected to solve associated issues such as poor accessibility and difficult operability within the GI tract. The actuators will be inserted into the body through the mouth or anus with a small diameter, perform various tasks in the GI tract with a large diameter, and finally be removed again. Therefore, deployability and retractivity are common requirements. Variable stiffness is also required to adjust or maintain forces on weak tissues. We proposed the new deployable and stiffness-variable miniature actuator consisting of a shape memory polymer bar and flexible channel part with water circulation, which is useful for medical applications in the GI tract. We established the design method of the actuator based on derived physical models and the fabrication method of prototypes. We evaluated the performances of thermal response, retractive deformation, and variable stiffness and confirmed the validity of the concept through the demonstration of continuous actuation, including deploying, retracting, and stiffness-varying. Furthermore, as a case study, we verified the feasibility of endoscopic submucosal dissection traction using prototypes and artificial materials. In the future, the actuator mechanism and design method may also contribute to the development of other medical tools interacting with delicate tissues in the GI tract.

Overhead industrial work frequently causes shoulder work-related musculoskeletal disorders. These tasks require not only localized muscle activation but also integrated central nervous system regulation for motor control. Although soft exoskeletons have demonstrated effectiveness in reducing peripheral musculoskeletal load, their impact on central nervous system regulation remains poorly understood. This study aimed to investigate the biomechanical benefits and corticomuscular coupling of a soft exoskeleton during industrial tasks. Fifteen healthy males performed standardized screwing and lifting tasks under exoskeleton-assisted and unassisted conditions. Multimodal physiological signals were acquired through: surface electromyography for muscle activation, functional near-infrared spectroscopy for cortex hemodynamics and ratings of perceived exertion for subjective perception. Corticomuscular coupling was analyzed based on hemodynamic and electromyographic metrics. The anterior deltoid activity decreased by 25.0% during lifting, while biceps brachii effort in screwing tasks was reduced by 46.1% and ratings of perceived exertion were mitigated during the early phase of screwing operations. Concurrently, wearing the exoskeleton during lifting significantly lowered cortical activation compared with the screwing tasks. The exoskeleton task-specifically enhanced corticomuscular coupling within sensorimotor pathways during precision screwing task, while reducing dorsolateral prefrontal pathways during lifting. Therefore, this study demonstrates that the soft shoulder exoskeleton has the potential to simultaneously provide biomechanical support and corticomuscular coupling adaptation, thereby enhancing motor control and mitigating work-related musculoskeletal disorders.

A core soft-robotics challenge for underwater locomotion is reconciling soft actuation’s compliance with the control tractability and robustness of rigid structures. We present SpineWave, a biomimetic robotic fish that adopts a compliant design within a hybrid soft–rigid architecture: rigid, additively manufactured vertebrae embed opposing magnets that provide passive magnetic compliance, enabling soft-like undulatory bending and impact tolerance while retaining a pressure-tolerant, analytically tractable backbone. Rather than manual tuning, we optimize a low-parameter central-pattern-generator (CPG) controller via hardware-in-the-loop efficient global optimization (EGO). The EGO-tuned gaits deliver a 38% increase in cruising speed and a 35% reduction in turning radius relative to pre-optimization baselines, and achieve 29% energy savings when exploiting vortex wakes, while maintaining stable body-wave propagation across modular morphologies. To our knowledge, SpineWave is the first fish robot to realize soft-like compliance and field robustness using an entirely rigid, magnetically coupled exoskeleton–endoskeleton. This combination of passive magnetic compliance and data-driven CPG optimization advances soft-robotic locomotion and offers a pressure-tolerant, modular platform for long-duration environmental monitoring and exploration.

In muscle tissues, muscle fibers generate active force, muscle spindles provide passive proprioceptive feedback, and connective tissues tightly bind their movements together, forming a reliable biological system. Inspired by this, we propose a single material fabrication method to monolithically print pneumatic proprioceptive actuators (MPPPAs). By leveraging the multifunctional properties of thermoplastic polyurethane (TPU), including inherent flexibility, fusibility, and translucency, and employing a desktop-level fused deposition modeling printer, airtight chambers and embedded optical waveguides are realized within a continuous printing process. Optimized printing parameters lead to fully densified chambers, resulting in a leakage rate of only 0.85% under 200 kPa and maintaining 462.55 kPa after 10 minutes from an initial 500 kPa. The optical waveguides exhibit robust proprioception, maintaining a stable signal over 5000 bending cycles with less than 0.5% drift. Mechanical tests confirm synchronized deformation and continuous structural integration across the monolithically co-printed actuator-sensor region, enabling MPPPAs to achieve reliable actuation-sensing performance with sensing errors below 1.82%. Demonstrations include precise surface contour measurement with the root mean square error of 0.16 mm and real-time gripping width estimation, validating the method’s effectiveness in fabricating compact and stable proprioceptive actuators. This research advances actuation-sensing integration in soft robotics, enabling streamlined fabrication and improved reliability for future intelligent systems.

Soft underwater grippers are well-suited for ecological sampling, providing flexibility in handling specimens of different sizes and shapes while reducing environmental impact through their compliance. Yet they are usually employed on big remotely operated vehicles, constraining their application by size, which can disturb aquatic habitats and limit their ability to access remote areas without shoreline access such as mountain and forest lakes. To support efficient underwater exploration, we designed, developed, and tested an aerially deployed underwater vehicle featuring a compact, lightweight soft gripper. This design reduces water disturbance and enables precise navigation in confined underwater environments, significantly expanding operational capabilities underwater. By analyzing the pod’s volume changes, buoyancy actuation, and propulsion mechanisms, we derive a simplified dynamic model to describe the underwater motion. We developed a control framework that decouples buoyancy, thrust, and yaw to enable independent control of underwater motion. Precise buoyancy control, essential for navigating interstices without causing ecological harm, was achieved with feedback control loops taking water depth as feedback, showing a rise time of under 5 s and a 10% settling time within 30 s. Yaw control, achieved via inertial measurement unit feedback, exhibited a rise time of less than 10 s with oscillations of 10%–25% around the set values. This system enhances underwater grasping, extends mission reach and efficiency, and helps minimize environmental disruption.

Navigating confined and complex environments, such as pipes, biological tissues, and collapsed debris, has remained a challenge for conventional robotic systems, which often struggle with maneuverability and adaptability. Soft toroidal robots offer a promising alternative, with a compact and lightweight toroidal shape that allows continuous movement without requiring bulky external equipment. However, the lack of a steering mechanism has limited their applicability in dynamic and complex terrains. To overcome this, we developed a steering mechanism that leverages the bistable characteristics inherent in the toroidal structure to enable curvature formation. By adjusting the position of the tail within the structure, the robot can change its direction of bending, enabling flexible and responsive steering. To achieve this bistable behavior, we utilized the orthotropic properties of ripstop nylon fabric, reducing the robot’s bending stiffness and enhancing its steering capabilities. Through theoretical modeling and experimental validation, we identified key design parameters, such as optimal operating pressure and steering device length. The proposed soft toroidal robot, with a diameter of 70 mm and a total length of 400 mm, achieves 1-degree of freedom (DOF) steering by exploiting this bistable deformation. Our experiments demonstrated its ability to navigate a T-shaped pipe and climb vertically in confined spaces, achieving a maximum curvature of 13.4 m⁻¹. These findings highlight the potential of soft toroidal robots for maneuvering through both confined and open environments with enhanced adaptability and efficiency.