Design Of Soft Robots Research Articles

Manta Ray Inspired Soft Robot Fish with Tough Hydrogels as Structural Elements.

The design of soft robots capable of navigation underwater has received tremendous research interest due to the robots' versatile applications in marine explorations. Inspired by marine animals such as jellyfish, scientists have developed various soft robotic fishes by using elastomers as the major material. However, elastomers have a hydrophobic network without embedded water, which is different from the gel-state body of the prototypes and results in high contrast to the surrounding environment and thus poor acoustic stealth. Here, we demonstrate a manta ray-inspired soft robot fish with tailored swimming motions by using tough and stiff hydrogels as the structural elements, as well as a dielectric elastomer as the actuating unit. The switching between actuated and relaxed states of this unit under wired power leads to the flapping of the pectoral fins and swimming of the gel fish. This robot fish has good stability and swims with a fast speed (∼10 cm/s) in freshwater and seawater over a wide temperature range (4-50 °C). The high water content (i.e., ∼70 wt %) of the robot fish affords good optical and acoustic stealth properties under water. The excellent mechanical properties of the gels also enable easy integration of other functional units/systems with the robot fish. As proof-of-concept examples, a temperature sensing system and a soft gripper are assembled, allowing the robot fish to monitor the local temperature, raise warning signals by lighting, and grab and transport an object on demand. Such a robot fish should find applications in environmental detection and execution tasks under water. This work should also be informative for the design of other soft actuators and robots with tough hydrogels as the building blocks.

SoRSS: A Soft Robot for Bio-Mimicking Stomach Anatomy and Motility.

A human stomach is an organ in the digestive system that breaks down foods by physiological digestion, including mechanical and chemical functions. The mechanical function is controlled by peristaltic waves generated over the stomach body, known as antral contraction waves (ACW). The stomach's physiological digestion is essential to sustain nutrition and health in humans. Replicating the digestion process in a robot provides a test environment as an alternative solution to in vivo testing, which is difficult in practice. Stomach robots made of rigid rods and metal cylinders are unrealistic replicas to contract and expand like biological examples. With soft robotics technology, it is possible to translate biological behavior into an engineering context. Soft robotics introduce potential methods to replicate peristaltic waves and achieve a soft-bodied stomach simulator. This work presents a soft robotic stomach simulator's (SoRSS) concept, design, and experimental validation. A pneumatic bellows actuation for linear elongation and a ring of bellows actuation for circular contraction are proposed first. Multi-ring actuators are then arranged to form an SoRSS that generates ACW and antral contracting pressure (ACP). The SoRSS satisfies the specification of human stomach anatomy and motility and finally undergoes experimental validation using videofluoroscopy with the outcomes presenting the ACW, ACP, and the digestion phases during the actuation process. Those are compared with other medical studies to validate SoRSS functionality.

A novel multi objective constraints based industrial gripper design with optimized stiffness for object grasping

Soft gripper design is a rising area of research due of its great possibilities in automation. One difficult problem in robot design is the ability to grasp a broader variety of items with variable stiffness, forms, and sizes in a single gripper. An ideal soft robotic gripper design with variable stiffness was designed in this research as a grasping model. Its distinctiveness is found in the methods utilized for modelling actuators and in the shifting stiffness characteristics of silicon soft gripper. When modelling the actuator in this case, multi-objective functions like gripping displacement and force transmission ratio are taken into account, and the actuator functions are controlled by the MDF (multiple degrees of freedom). The precise stiffness needed to grasp the item is then chosen using an adaptive optimization method. This enhanced weight-based horse herd (IHH) optimization method carries out the stiffness adjustment based on actuation pressure. Additionally, the suggested soft robotic gripper with variable stiffness employs the adaptive level set (ALS) technique to build the gripping force model. Additionally, several validations are offered in relation to the outcomes for item gripping by the suggested soft gripper. This shown that the results of the created soft gripper excelled those of other methods. The developed ABBIRB 1410 robot gripper type may enhance the work cycle in industrial applications and performs object grabbing with dependability and speed. The experimental validations show that the developed gripper model provides an enhanced object grasp with a range of curvatures, delivering a maximum pulling force of 121.07 kPa at 50 kpa, 119.15 kPa for patterned pulling, and 45.05 kPa for non-patterned pulling. The designed gripper type has a curve with a minimum size of 1.1 mm and a maximum size of 218 mm. Additionally, the soft gripper for industrial applications is examined with variously sized and weighted items. The suggested gripper model achieved an RMSE performance of 2.9 and a Pearson correlation of 0.993.

Soft Underwater Swimming Robots Based on Artificial Muscle

AbstractWith the increasing requirements of underwater missions and the rapid development of soft robotics technologies, soft underwater swimming robots have become a hot topic of research due to their low noise, high flexibility, and high environmental adaptability. In the past 10 years, research into soft underwater robots based on artificial muscle actuation has made considerable progress. Herein, a comprehensive survey on recent advances in soft underwater swimming robots based on different actuation methods is reviewed systematically, including pressure actuation, intelligent material actuation, and biomaterial actuation. First, for each type of actuation, the actuating principle, structural design, and swimming performance of soft underwater robots are introduced in detail. Then, according to the different swimming modes of underwater organisms, the aforementioned soft underwater robots are classified and compared. The results show that for different swimming tasks and application scenarios, the robot needs to realize the optimal design by reasonably selecting the actuating method and the swimming mode. This review summarizes the advanced information and critical technology in designing high‐performance soft underwater robots in the aspect of structural design, actuating methods, and swimming modes and offers an insightful outlook for the future development of soft robots.

Review on mechanic modeling methods and applications of muscles in soft actuations

The main function of muscles is to contract when receiving electrical signals from nerves, resulting in the movement or deformation of related bones and tissues. Muscles possess the characteristics of flexibility and high efficiency, which are suitable for distributed actuation and human-computer interaction. Recently, bionic actuators, including pneumatic actuators, cable-driven mechanisms, and shape memory alloys/polymers, have been widely used in soft robots. Fundamentally, studying the actuation mechanism of muscles and extracting a simplified model is of great significance for achieving bionic actuation. The core problem of muscle movement is to establish the relationship between length and tension of muscles. Various modeling methods have been proposed for describing mechanics of muscles including fitting methods based on experimental data and simplified theoretical models. Recently, the simulation of muscle contour comes into being with the development of image processing and animation. This paper introduces the development of modeling methods of muscle mechanics including experimental modeling methods and theoretical/simulation modeling methods. Besides, the advantages and disadvantages of these modeling methods and their applications are analysed. Therefore, it has guiding significance for the design of soft robots including pneumatic actuators, cable-driven actuators, etc.

Embodied Intelligence in soft robotics: joys and sorrows

Embodied intelligence and soft robotics are strictly interconnected, as soft bodyware is key to obtain emergent behaviours from external interactions. The overall advantages of embodied intelligence in robotics are balanced by additional challenges in robot design and control. A main contribution of embodied intelligence to robotics consists of simplifying principles for robot control, in terms of control parameters. At the same time, robot design becomes more complex, involving the complex dynamic interaction of the robot with the environment and the task. These two form the ecological niche where embodied intelligence is effective, but they also limit the robot task space. To what extent can we enlarge the ecological niche without missing the benefits of embodied intelligence? Emergent behaviours are what we expect to simplify control, but what level of controllability can we still achieve? And how far are we from a mathematical description of embodied intelligence, to the benefit of soft robot design and control? Few trade-offs between contrasting needs in the use of embodied intelligence in soft robotics are discussed here, in view of directions of future progress.

A Preliminary Study to Design and Evaluate Pneumatically Controlled Soft Robotic Actuators for a Repetitive Hand Rehabilitation Task.

A stroke is an infarction in the cortical region of the brain that often leads to isolated hand paresis. This common side effect renders individuals compromised in their ability to actively flex or extend the fingers of the affected hand. While there are currently published soft robotic glove designs, this article proposed a unique design that allows users to self-actuate their therapy due to the ability to re-extend the hand using a layer of resistive flexible steel. The results showed a consistently achieved average peak of 75° or greater for each finger while the subjects’ hands were at rest during multiple trials of pneumatic assisted flexion. During passive assisted testing, human subject testing on 10 participants showed that these participants were able to accomplish 80.75% of their normal active finger flexion range with the steel-layer-lined pneumatic glove and 87.07% with the unlined pneumatic glove on average when neglecting outliers. An addition of the steel layer lowered the blocked tip force by an average of 18.13% for all five fingers. These data show strong evidence that this glove would be appropriate to advance to human subject testing on those who do have post stroke hand impairments.

Inverse Design of Mechanical Metamaterials with Target Nonlinear Response via a Neural Accelerated Evolution Strategy.

Materials with target nonlinear mechanical response can support the design of innovative soft robots, wearable devices, footwear, and energy-absorbing systems, yet it is challenging to realize them. Here, mechanical metamaterials based on hinged quadrilaterals are used as a platform to realize target nonlinear mechanical responses. It is first shown that by changing the shape of the quadrilaterals, the amount of internal rotations induced by the applied compression can be tuned, and a wide range of mechanical responses is achieved. Next, a neural network is introduced that provides a computationally inexpensive relationship between the parameters describing the geometry and the corresponding stress-strain response. Finally, it is shown that by combining the neural network with an evolution strategy, one can efficiently identify geometries resulting in a wide range of target nonlinear mechanical responses and design optimized energy-absorbing systems, soft robots, and morphingstructures.

Design, Analysis, and Real-Time Simulation of a 3D Soft Robotic Snake.

Snakes are a remarkable source of inspiration for mobile search-and-rescue robots. Their unique slender body structure and multiple modes of locomotion are well-suited to movement in narrow passages and other difficult terrain. The design, manufacturing, modeling, and control techniques of soft robotics make it possible to imitate the structure, mechanical properties, and locomotion gaits of snakes, opening up new possibilities in robotics research. Building on our track record of contributions in this area, this article presents a soft robotic snake made of modules that can actively deform in three-dimensional (3D) and rigorously studies its performance under a range of conditions, including gait parameters, number of modules, and differences in the environment. A soft 3D-printed wave spring sheath is developed to support the robot modules, increasing the snake's performance in climbing steps threefold. Finally, we introduce a simulator and a numerical model to provide a real-time simulation of the soft robotic snake. With the help of the real-time simulator, it is possible to develop and test new locomotion gaits for the soft robotic snake within a short period of time, compared with experimental trial and error. As a result, the soft robotic snake presented in this article is able to locomote on different surfaces, perform different bioinspired and custom gaits, and climb over steps.

Design and Control Strategy of Soft Robot Based on Gas–Liquid Phase Transition Actuator

In this paper, a soft robot driven by a gas–liquid phase transition actuator with a new structure is designed; The soft robot is driven by the pressure generated by electrically induced ethanol phase transition. The gas–liquid phase transition drive was found to be able to generate a larger driving force by using only low voltage. Compared with the gas drive of a traditional soft robot, gas–liquid phase transition-driven soft robot does not require a complex circuit system and a huge external energy supply air pump, making its overall structure more compact. At the same time, because of the new structure of the actuator on the soft robot, the soft robot has good gas tightness and less recovery time. A reinforcement depth learning control strategy is also added so that the soft robot with this actuator could better grip objects of different sizes and weights.

CHIRAL GROWTH OF THIN BIOMATERIALS INDUCED BY ANISOTROPIC STRUCTURAL MECHANICS

Chiral growth is ubiquitous in nature and has always been of great interest in the field of biomimetic and man-made materials, but its formation mechanism is complex. In order to clarify this mechanism, with the help of the plate theory and the theory from differential geometry, we established a new theoretical model that can be used to describe the interaction between anisotropic elasticity and anisotropic residual stress of slender biomaterials and provide additional insight onto the mechanical mechanism of biomaterial’s morphological chiral growth. Based on these results, it appears that misfit of material properties and residual stresses may create various chiral morphologies, like helices and twisting belts. It is found here that the cooperative and competitive interactions between anisotropic elasticity and anisotropic residual stress can also give rise to chiral morphologies, and macro shapes, sizes, and handedness of chiral morphologies can be designed by residual stresses orientation angles and elastic parameters of biomaterials. This theoretical model is in good agreement with the recent experiments and can provide theoretical guidance for the design of medical-assisted soft robots.

Topology and Morphology Design of Spherically Reconfigurable Homogeneous Modular Soft Robots.

Imagine a swarm of terrestrial robots that can explore an environment, and, on completion of this task, reconfigure into a spherical ball and roll out. This dimensional change alters the dynamics of locomotion and can assist them in maneuvering variable terrains. The sphere-plane reconfiguration is equivalent to projecting a spherical shell onto a plane, an operation that is not possible without distortions. Fortunately, soft materials have the potential to adapt to this disparity of the Gaussian curvatures. Modular Soft Robots (MSoRos) have promise of achieving dimensional change by exploiting their continuum and deformable nature. However, the design of such soft robots has remained unexplored thus far. Here, for the first time, we present the topology and morphology design of MSoRos that are capable of reconfiguring between spherical and planar configurations. Our approach is based in geometry, where a platonic solid determines the number of modules required for plane-to-sphere reconfiguration and the radius of the resulting sphere, for example, four "tetrahedron-based" or six "cube-based" MSoRos are required for spherical reconfiguration. The methodology involves: (1) inverse orthographic projection of a "module-topology curve" onto the circumscribing sphere to generate the spherical topology; (2) azimuthal projection of the spherical topology onto a tangent plane at the center of the module resulting in the planar topology; and (3) adjusting the limb stiffness and curling ability by manipulating the geometry of cavities to realize a physical finite-width, Motor-Tendon Actuated MSoRo that can actuate between the sphere-plane configurations. The topology design is shown to be scale invariant, that is, the scaling of base platonic solid is reflected linearly in spherical and planar topologies. The module-topology curve is optimized for the reconfiguration and locomotion ability using an intramodular distortion metric that quantifies sphere-to-plane distortion. The geometry of the cavity optimizes for the limb stiffness and curling ability without compromising the actuator's structural integrity.

Co-Design of the Morphology and Actuation of Soft Robots for Locomotion

Abstract In recent years, the field of soft robotics has received considerable attention due to its potential in increasing the safety of human-robot interaction. The design of soft robots possesses great challenges. For example, the longstanding challenge of co-design morphology and actuation makes designing them by hand a trial-and-error process. Earlier work presented by the authors proposes a computational design synthesis (CDS) method for the automated design of virtual, soft locomotion robot morphologies. This work extends the CDS method for morphologies with the automated co-design of actuation. Two methods are considered. In the first method, the actuation of designs is described by parametric actuation curves (PACs) that model feedforward actuation patterns. For every morphology in the design process, a set of PACs is optimized that assumes symmetric and cyclic gaits. The second method, soft actor-critic (SAC) reinforcement learning, removes this assumption as well as models feedback control for comparison. Adding PAC optimization to the CDS method is shown to improve the performance of the resulting designs and to achieve better results within less design iterations. SAC is, however, deemed less effective, due to the need for design specific problem tuning for each new morphology. The SAC experiments also show that the best found soft robot gaits are symmetric and cyclic, although this is not a constraint in the SAC problem formulation, thus verifying the assumptions made in the PAC formulation. To validate the search space modeled in the co-design CDS method, a state-of-the-art soft robot is replicated and compared.

Modular Origami Soft Robot with the Perception of Interaction Force and Body Configuration

Bio‐inspired soft robots provide a promising solution for robots working in human‐centered scenarios and interacting with unstructured environments. However, the functional versatility and multimodal sensing of soft robots still need improvements. On one hand, the configuration of a soft robot is predefined during manufacturing; on the other hand, the multimodal perception of the deformable soft actuator is challenging. In this work, a reconfigurable and proprioceptive soft origami module is presented, where two kinds of basic actuation modes (i.e., extension and bending) are realized, and multimodal perception is enabled using a novel foldable self‐inductance sensor. As a result, the origami module can be reconfigured to assemble multifunctional robots that can measure interaction force, body configuration, and other environmental information. Dedicated experiments are performed to validate the performance of the proposed origami module. An intelligent gripper assembled using three origami modules is designed with the capabilities of grasping mode adjustment, grasping force measurement, and the grasping target's size measurement. An intelligent jellyfish is assembled using five origami modules, and equipped with buoyancy adjustment and underwater grasping capabilities. The proposed proprioceptive modular soft origami provides an effective solution for versatile and intelligent soft robot design.

Inflatable Origami: Multimodal Deformation via Multistability

AbstractInflatable structures have become essential components in the design of soft robots and deployable systems as they enable dramatic shape change from a single pressure inlet. This simplicity, however, often brings a strict limitation: unimodal deformation upon inflation. Here, multistability is embraced to design modular, inflatable structures that can switch between distinct deformation modes as a response to a single input signal. This system comprises bistable origami modules in which pressure is used to trigger a snap‐through transition between a state of deformation characterized by simple deployment to a state characterized by bending deformation. By assembling different modules and tuning their geometry to cause snapping at different pressure thresholds, structures capable of complex deformations that can be pre‐programmed and activated using only one pressure source are created. This approach puts forward multistability as a paradigm to eliminate a one‐to‐one relation between input signal and deformation mode in inflatable systems.

Design and locomotion analysis of modular soft robot

AbstractIn the paper, a novel modular soft robot that can crawl and turn is presented. The modular soft robot is composed of multiple drive modules connected in series, including one head module, one tail module and three body modules. Each module is actuated by the air chamber. Due to the nonlinear performance of the air chamber, the strain energy function of the air chamber is established. The relationship between the displacement of the air chamber expansion wall and the inflation pressure is obtained, and the manufacturing parameters of the air chamber are determined. By dividing the body of the robot into a series of continuous flexible models, the driving force and the friction force of the robot in locomotion are analyzed. An inflation and deflation control method is presented to complete the locomotion. According to the experiment, the crawling speed of the robot can reach 15.53 mm/s (0.03 body length per second). The turning speed of the robot can reach 1.273 °/s. The robot can crawl and turn on the rough blanket surface effectively. The robot can explore and move in a complex and changeable environment.

Verticalized-Tip Trajectory Tracking of a 3D-Printable Soft Continuum Robot: Enabling Surgical Blood Suction Automation

Soft-bodied robotic manipulators have great potential for use in minimally invasive surgery, owing to their advantages of high flexibility with infinite degrees of freedom (DOF). One of the potential applications is to perform blood suctioning, which is inevitable during the surgery. To attain higher efficiency in suctioning, the robotic tip should remain vertical while moving along on the work surface. Motivated by this application, this article presents a novel soft robot design and its control scheme to properly configure the tip of a two-segment soft robot while following a planned trajectory on the work surface. Aiming to reduce the incision size and the possibility of infection, a 3D-printed soft-bodied manipulator utilizing the cable-driven mechanism with a diameter of 9 mm was designed and fabricated. An additional DOF was added through a motorized insertion stage. The robot system was modeled using piecewise constant-curvature assumption, and an RGB-D vision was employed to enhance the accuracy of the kinematic-based controller. Performances of the tip positioning and verticalizing were evaluated via simulation, and further verified through experiments. The results confirm that the manipulator is capable of following different trajectories at various velocities while keeping its tip vertical. Compared to other similar works, our results are satisfactory with an root-mean-square error of trajectory tracking within 7 mm, and a maximum angular deviation of 6 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> . Fluid suction experiments were conducted to demonstrate its effectiveness for automated 3-D suction. This article offers a new tool to support the surgeons for surgical blood suction.

Design and modeling of a novel soft parallel robot driven by endoskeleton pneumatic artificial muscles

Design and modeling of a novel soft parallel robot driven by endoskeleton pneumatic artificial muscles

Design, Fabrication, and Testing of a Novel Ferrofluid Soft Capsule Robot

This article proposes a ferrofluid soft capsule robot (FSCR) with magnetic actuation for diagnostic and therapeutic medical applications inside the human stomach. A composite shell consisted of ferrofluid, permanent magnet rings, and soft elastomer is developed for the FSCR, which is actuated remotely by an external permanent magnet. The proposed FSCR presents two novel characteristics. First, the composite shell not only has a soft outer surface that reduces damage to contact tissue but also an improved magnetic circuit with a combination of the ferrofluid and permanent magnet rings makes the locomotion of the device more controllable and secure. Second, the FSCR is equipped with a specific oscillation module that enables advanced functions such as drug-releasing. Detailed structure design and fabrication of the FSCR are presented in this study. The surface rolling locomotion of the FSCR is modeled and evaluated by numerical simulations, as well as the drug-releasing function. In order to verify the simulation result, an FSCR prototype is manufactured to perform experimental validation. The analysis result demonstrates the feasibility and efficiency of the proposed FSCR for drug releasing inside a printed human stomach model.

Distributed Parameter Modeling and Boundary Control of an Octopus Tentacle-Inspired Soft Robot

Inspired by soft organisms in nature, engineers have been exploring the mechanical design of soft robots manufactured by compliant materials. However, some limitations still exist in the modeling and control of soft robots. This article studies a cable-driven soft robot with shape and bending motion inspired by an octopus tentacle. By the extended Hamilton's principle, the dynamic equation of the soft robot is derived in a distributed parameter system (DPS), which is governed by a partial differential equation. The boundary control strategy for the soft robot is developed via Lyapunov-based design to achieve distributed bending angle tracking. The stability analysis of the closed-loop system is presented using LaSalle's invariance principle to show that the total energies in the system, and hence, the distributed states of the system, remain bounded and tend asymptotically to the desired values. Some simulation results are applied to demonstrate the applicability and effectiveness of the employed model and control. This study will promote the application of DPS theory in soft robots.